Project import generated by Copybara.

GitOrigin-RevId: da3cb82c964457b1c719c915a48e545b980af64b
2020-04-06 21:28:19 -07:00 · 2020-04-06 19:14:13 -07:00 · 2020-03-20 15:28:51 -07:00 · 2020-03-10 18:14:25 -07:00 · 2020-03-02 10:35:07 -08:00 · 2020-02-10 14:13:25 -08:00
792 changed files with 106617 additions and 3798 deletions
@@ -3,7 +3,7 @@
 # Basic build settings
 build --jobs 128
 build --define='absl=1'
-build --cxxopt='-std=c++11'
+build --cxxopt='-std=c++14'
 build --copt='-Wno-sign-compare'
 build --copt='-Wno-unused-function'
 build --copt='-Wno-uninitialized'
@@ -12,14 +12,21 @@ build --copt='-Wno-comment'
 build --copt='-Wno-return-type'
 build --copt='-Wno-unused-local-typedefs'
 build --copt='-Wno-ignored-attributes'
-# Temporarily set the incompatiblity flag for Bazel 0.27.0 and above
-build --incompatible_disable_deprecated_attr_params=false
-build --incompatible_depset_is_not_iterable=false
+
+# Tensorflow needs remote repo
+build --experimental_repo_remote_exec

 # Sets the default Apple platform to macOS.
 build --apple_platform_type=macos

+# Allow debugging with XCODE
+build --apple_generate_dsym
+
 # Android configs.
+# Note: the documentation tells us to use @androidndk//:default_crosstool, but
+# the automatic configuration transition uses //external:android/crosstool.
+# Using it here works and spares us from having two different config_settings
+# for Android.
 build:android --crosstool_top=//external:android/crosstool
 build:android --host_crosstool_top=@bazel_tools//tools/cpp:toolchain
 build:android --linkopt=-landroid
@@ -30,10 +30,13 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
        unzip \
        python \
        python-pip \
+        python3-pip \
        libopencv-core-dev \
        libopencv-highgui-dev \
        libopencv-imgproc-dev \
        libopencv-video-dev \
+        libopencv-calib3d-dev \
+        libopencv-features2d-dev \
        software-properties-common && \
    add-apt-repository -y ppa:openjdk-r/ppa && \
    apt-get update && apt-get install -y openjdk-8-jdk && \
@@ -42,9 +45,10 @@ RUN apt-get update && apt-get install -y --no-install-recommends \

 RUN pip install --upgrade setuptools
 RUN pip install future
+RUN pip3 install six

 # Install bazel
-ARG BAZEL_VERSION=0.26.1
+ARG BAZEL_VERSION=2.0.0
 RUN mkdir /bazel && \
    wget --no-check-certificate -O /bazel/installer.sh "https://github.com/bazelbuild/bazel/releases/download/${BAZEL_VERSION}/b\
 azel-${BAZEL_VERSION}-installer-linux-x86_64.sh" && \
@@ -1,7 +1,7 @@
 ![MediaPipe](mediapipe/docs/images/mediapipe_small.png?raw=true "MediaPipe logo")
 =======================================================================

-[MediaPipe](http://mediapipe.dev) is a framework for building multimodal (eg. video, audio, any time series data) applied ML pipelines. With MediaPipe, a perception pipeline can be built as a graph of modular components, including, for instance, inference models (e.g., TensorFlow, TFLite) and media processing functions.
+[MediaPipe](http://mediapipe.dev) is a framework for building multimodal (eg. video, audio, any time series data), cross platform (i.e Android, iOS, web, edge devices) applied ML pipelines. With MediaPipe, a perception pipeline can be built as a graph of modular components, including, for instance, inference models (e.g., TensorFlow, TFLite) and media processing functions.

 ![Real-time Face Detection](mediapipe/docs/images/realtime_face_detection.gif)

@@ -9,21 +9,28 @@

 ## ML Solutions in MediaPipe

-* [Hand Tracking](mediapipe/docs/hand_tracking_mobile_gpu.md)
-* [Face Detection](mediapipe/docs/face_detection_mobile_gpu.md)
-* [Hair Segmentation](mediapipe/docs/hair_segmentation_mobile_gpu.md)
+* [Face Detection](mediapipe/docs/face_detection_mobile_gpu.md) [[Web Demo]](https://viz.mediapipe.dev/runner/demos/face_detection/face_detection.html)
+* [Multi-hand Tracking](mediapipe/docs/multi_hand_tracking_mobile_gpu.md)
+* [Hand Tracking](mediapipe/docs/hand_tracking_mobile_gpu.md) [[Web Demo]](https://viz.mediapipe.dev/runner/demos/hand_tracking/hand_tracking.html)
+* [Hair Segmentation](mediapipe/docs/hair_segmentation_mobile_gpu.md) [[Web Demo]](https://viz.mediapipe.dev/runner/demos/hair_segmentation/hair_segmentation.html)
 * [Object Detection](mediapipe/docs/object_detection_mobile_gpu.md)
+* [Object Detection and Tracking](mediapipe/docs/object_tracking_mobile_gpu.md)
+* [Objectron: 3D Object Detection and Tracking](mediapipe/docs/objectron_mobile_gpu.md)
+* [AutoFlip](mediapipe/docs/autoflip.md)

-![hand_tracking](mediapipe/docs/images/mobile/hand_tracking_3d_android_gpu_small.gif)
 ![face_detection](mediapipe/docs/images/mobile/face_detection_android_gpu_small.gif)
+![multi-hand_tracking](mediapipe/docs/images/mobile/multi_hand_tracking_android_gpu_small.gif)
+![hand_tracking](mediapipe/docs/images/mobile/hand_tracking_3d_android_gpu_small.gif)
 ![hair_segmentation](mediapipe/docs/images/mobile/hair_segmentation_android_gpu_small.gif)
-![object_detection](mediapipe/docs/images/mobile/object_detection_android_gpu_small.gif)
+![object_tracking](mediapipe/docs/images/mobile/object_tracking_android_gpu_small.gif)

 ## Installation
 Follow these [instructions](mediapipe/docs/install.md).

 ## Getting started
-See mobile and desktop [examples](mediapipe/docs/examples.md).
+See mobile, desktop and Google Coral [examples](mediapipe/docs/examples.md).
+
+Check out some web demos [[Edge detection]](https://viz.mediapipe.dev/runner/demos/edge_detection/edge_detection.html) [[Face detection]](https://viz.mediapipe.dev/runner/demos/face_detection/face_detection.html) [[Hand Tracking]](https://viz.mediapipe.dev/runner/demos/hand_tracking/hand_tracking.html)

 ## Documentation
 [MediaPipe Read-the-Docs](https://mediapipe.readthedocs.io/) or [docs.mediapipe.dev](https://docs.mediapipe.dev)
@@ -33,17 +40,33 @@ Check out the [Examples page](https://mediapipe.readthedocs.io/en/latest/example
 ## Visualizing MediaPipe graphs
 A web-based visualizer is hosted on [viz.mediapipe.dev](https://viz.mediapipe.dev/). Please also see instructions [here](mediapipe/docs/visualizer.md).

-## Community forum
-*  [Discuss](https://groups.google.com/forum/#!forum/mediapipe) - General community discussion around MediaPipe
+## Videos
+*  [YouTube Channel](https://www.youtube.com/channel/UCObqmpuSMx-usADtL_qdMAw)

 ## Publications
+* [MediaPipe Objectron: Real-time 3D Object Detection on Mobile Devices](https://mediapipe.page.link/objectron-aiblog)
+* [AutoFlip: An Open Source Framework for Intelligent Video Reframing](https://mediapipe.page.link/autoflip)
+* [Google Developer Blog: MediaPipe on the Web](https://mediapipe.page.link/webdevblog)
+* [Google Developer Blog: Object Detection and Tracking using MediaPipe](https://mediapipe.page.link/objecttrackingblog)
+* [On-Device, Real-Time Hand Tracking with MediaPipe](https://ai.googleblog.com/2019/08/on-device-real-time-hand-tracking-with.html)
 * [MediaPipe: A Framework for Building Perception Pipelines](https://arxiv.org/abs/1906.08172)

 ## Events
-[Open sourced at CVPR 2019](https://sites.google.com/corp/view/perception-cv4arvr/mediapipe) on June 17~20 in Long Beach, CA
+* [AI Nextcon 2020, 12-16 Feb 2020, Seattle](http://aisea20.xnextcon.com/)
+* [MediaPipe Madrid Meetup, 16 Dec 2019](https://www.meetup.com/Madrid-AI-Developers-Group/events/266329088/)
+* [MediaPipe London Meetup, Google 123 Building, 12 Dec 2019](https://www.meetup.com/London-AI-Tech-Talk/events/266329038)
+* [ML Conference, Berlin, 11 Dec 2019](https://mlconference.ai/machine-learning-advanced-development/mediapipe-building-real-time-cross-platform-mobile-web-edge-desktop-video-audio-ml-pipelines/)
+* [MediaPipe Berlin Meetup, Google Berlin, 11 Dec 2019](https://www.meetup.com/Berlin-AI-Tech-Talk/events/266328794/)
+* [The 3rd Workshop on YouTube-8M Large Scale Video Understanding Workshop](https://research.google.com/youtube8m/workshop2019/index.html) Seoul, Korea ICCV 2019
+* [AI DevWorld 2019](https://aidevworld.com) on Oct 10 in San Jose, California
+* [Google Industry Workshop at ICIP 2019](http://2019.ieeeicip.org/?action=page4&id=14#Google) [Presentation](https://docs.google.com/presentation/d/e/2PACX-1vRIBBbO_LO9v2YmvbHHEt1cwyqH6EjDxiILjuT0foXy1E7g6uyh4CesB2DkkEwlRDO9_lWfuKMZx98T/pub?start=false&loop=false&delayms=3000&slide=id.g556cc1a659_0_5) on Sept 24 in Taipei, Taiwan
+* [Open sourced at CVPR 2019](https://sites.google.com/corp/view/perception-cv4arvr/mediapipe) on June 17~20 in Long Beach, CA
+
+## Community forum
+*  [Discuss](https://groups.google.com/forum/#!forum/mediapipe) - General community discussion around MediaPipe

 ## Alpha Disclaimer
-MediaPipe is currently in alpha for v0.6. We are still making breaking API changes and expect to get to stable API by v1.0.
+MediaPipe is currently in alpha for v0.7. We are still making breaking API changes and expect to get to stable API by v1.0.

 ## Contributing
 We welcome contributions. Please follow these [guidelines](./CONTRIBUTING.md).
@@ -2,27 +2,32 @@ workspace(name = "mediapipe")

 load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")

-skylib_version = "0.8.0"
+skylib_version = "0.9.0"
 http_archive(
    name = "bazel_skylib",
    type = "tar.gz",
-    url = "https://github.com/bazelbuild/bazel-skylib/releases/download/{}/bazel-skylib.{}.tar.gz".format (skylib_version, skylib_version),
-    sha256 = "2ef429f5d7ce7111263289644d233707dba35e39696377ebab8b0bc701f7818e",
+    url = "https://github.com/bazelbuild/bazel-skylib/releases/download/{}/bazel_skylib-{}.tar.gz".format (skylib_version, skylib_version),
+    sha256 = "1dde365491125a3db70731e25658dfdd3bc5dbdfd11b840b3e987ecf043c7ca0",
 )
 load("@bazel_skylib//lib:versions.bzl", "versions")
-versions.check(minimum_bazel_version = "0.24.1")
+versions.check(minimum_bazel_version = "2.0.0")

-# ABSL cpp library.
+
+# ABSL cpp library lts_2020_02_25
 http_archive(
    name = "com_google_absl",
-    # Head commit on 2019-04-12.
-    # TODO: Switch to the latest absl version when the problem gets
-    # fixed.
    urls = [
-        "https://github.com/abseil/abseil-cpp/archive/a02f62f456f2c4a7ecf2be3104fe0c6e16fbad9a.tar.gz",
+        "https://github.com/abseil/abseil-cpp/archive/20200225.tar.gz",
    ],
-    sha256 = "d437920d1434c766d22e85773b899c77c672b8b4865d5dc2cd61a29fdff3cf03",
-    strip_prefix = "abseil-cpp-a02f62f456f2c4a7ecf2be3104fe0c6e16fbad9a",
+    # Remove after https://github.com/abseil/abseil-cpp/issues/326 is solved.
+    patches = [
+        "@//third_party:com_google_absl_f863b622fe13612433fdf43f76547d5edda0c93001.diff"
+    ],
+    patch_args = [
+        "-p1",
+    ],
+    strip_prefix = "abseil-cpp-20200225",
+    sha256 = "728a813291bdec2aa46eab8356ace9f75ac2ed9dfe2df5ab603c4e6c09f1c353"
 )

 http_archive(
@@ -72,6 +77,14 @@ http_archive(
    ],
 )

+# easyexif
+http_archive(
+    name = "easyexif",
+    url = "https://github.com/mayanklahiri/easyexif/archive/master.zip",
+    strip_prefix = "easyexif-master",
+    build_file = "@//third_party:easyexif.BUILD",
+)
+
 # libyuv
 http_archive(
    name = "libyuv",
@@ -79,11 +92,13 @@ http_archive(
    build_file = "@//third_party:libyuv.BUILD",
 )

+# Note: protobuf-javalite is no longer released as a separate download, it's included in the main Java download.
+# ...but the Java download is currently broken, so we use the "source" download.
 http_archive(
    name = "com_google_protobuf_javalite",
-    sha256 = "79d102c61e2a479a0b7e5fc167bcfaa4832a0c6aad4a75fa7da0480564931bcc",
-    strip_prefix = "protobuf-384989534b2246d413dbcd750744faab2607b516",
-    urls = ["https://github.com/google/protobuf/archive/384989534b2246d413dbcd750744faab2607b516.zip"],
+    sha256 = "a79d19dcdf9139fa4b81206e318e33d245c4c9da1ffed21c87288ed4380426f9",
+    strip_prefix = "protobuf-3.11.4",
+    urls = ["https://github.com/protocolbuffers/protobuf/archive/v3.11.4.tar.gz"],
 )

 http_archive(
@@ -103,32 +118,42 @@ http_archive(
    ],
 )

-# 2019-08-15
-_TENSORFLOW_GIT_COMMIT = "67def62936e28f97c16182dfcc467d8d1cae02b4"
-_TENSORFLOW_SHA256= "ddd4e3c056e7c0ff2ef29133b30fa62781dfbf8a903e99efb91a02d292fa9562"
+# 2020-04-01
+_TENSORFLOW_GIT_COMMIT = "805e47cea96c7e8c6fccf494d40a2392dc99fdd8"
+_TENSORFLOW_SHA256= "9ee3ae604c2e1345ac60345becee6d659364721513f9cb8652eb2e7138320ca5"
 http_archive(
    name = "org_tensorflow",
    urls = [
      "https://mirror.bazel.build/github.com/tensorflow/tensorflow/archive/%s.tar.gz" % _TENSORFLOW_GIT_COMMIT,
      "https://github.com/tensorflow/tensorflow/archive/%s.tar.gz" % _TENSORFLOW_GIT_COMMIT,
    ],
-    strip_prefix = "tensorflow-%s" % _TENSORFLOW_GIT_COMMIT,
-    sha256 = _TENSORFLOW_SHA256,
    patches = [
-        "@//third_party:tensorflow_065c20bf79253257c87bd4614bb9a7fdef015cbb.diff",
-        "@//third_party:tensorflow_f67fcbefce906cd419e4657f0d41e21019b71abd.diff",
+        "@//third_party:org_tensorflow_compatibility_fixes.diff",
+        "@//third_party:org_tensorflow_protobuf_updates.diff",
    ],
    patch_args = [
        "-p1",
    ],
+    strip_prefix = "tensorflow-%s" % _TENSORFLOW_GIT_COMMIT,
+    sha256 = _TENSORFLOW_SHA256,
 )

 load("@org_tensorflow//tensorflow:workspace.bzl", "tf_workspace")
 tf_workspace(tf_repo_name = "org_tensorflow")

-# Please run
-# $ sudo apt-get install libopencv-core-dev libopencv-highgui-dev \
-#                        libopencv-imgproc-dev libopencv-video-dev
+http_archive(
+    name = "ceres_solver",
+    url = "https://github.com/ceres-solver/ceres-solver/archive/1.14.0.zip",
+    patches = [
+        "@//third_party:ceres_solver_9bf9588988236279e1262f75d7f4d85711dfa172.diff"
+    ],
+    patch_args = [
+        "-p1",
+    ],
+    strip_prefix = "ceres-solver-1.14.0",
+    sha256 = "5ba6d0db4e784621fda44a50c58bb23b0892684692f0c623e2063f9c19f192f1"
+)
+
 new_local_repository(
    name = "linux_opencv",
    build_file = "@//third_party:opencv_linux.BUILD",
@@ -141,7 +166,6 @@ new_local_repository(
    path = "/usr"
 )

-# Please run $ brew install opencv@3
 new_local_repository(
    name = "macos_opencv",
    build_file = "@//third_party:opencv_macos.BUILD",
@@ -156,11 +180,10 @@ new_local_repository(

 http_archive(
    name = "android_opencv",
-    sha256 = "056b849842e4fa8751d09edbb64530cfa7a63c84ccd232d0ace330e27ba55d0b",
    build_file = "@//third_party:opencv_android.BUILD",
    strip_prefix = "OpenCV-android-sdk",
    type = "zip",
-    url = "https://github.com/opencv/opencv/releases/download/4.1.0/opencv-4.1.0-android-sdk.zip",
+    url = "https://github.com/opencv/opencv/releases/download/3.4.3/opencv-3.4.3-android-sdk.zip",
 )

 # After OpenCV 3.2.0, the pre-compiled opencv2.framework has google protobuf symbols, which will
@@ -175,74 +198,6 @@ http_archive(
    url = "https://github.com/opencv/opencv/releases/download/3.2.0/opencv-3.2.0-ios-framework.zip",
 )

-RULES_JVM_EXTERNAL_TAG = "2.2"
-RULES_JVM_EXTERNAL_SHA = "f1203ce04e232ab6fdd81897cf0ff76f2c04c0741424d192f28e65ae752ce2d6"
-
-http_archive(
-    name = "rules_jvm_external",
-    strip_prefix = "rules_jvm_external-%s" % RULES_JVM_EXTERNAL_TAG,
-    sha256 = RULES_JVM_EXTERNAL_SHA,
-    url = "https://github.com/bazelbuild/rules_jvm_external/archive/%s.zip" % RULES_JVM_EXTERNAL_TAG,
-)
-
-load("@rules_jvm_external//:defs.bzl", "maven_install")
-
-maven_install(
-    artifacts = [
-        "androidx.annotation:annotation:aar:1.1.0",
-        "androidx.appcompat:appcompat:aar:1.1.0-rc01",
-        "androidx.constraintlayout:constraintlayout:aar:1.1.3",
-        "androidx.core:core:aar:1.1.0-rc03",
-        "androidx.legacy:legacy-support-v4:aar:1.0.0",
-        "androidx.recyclerview:recyclerview:aar:1.1.0-beta02",
-        "com.google.android.material:material:aar:1.0.0-rc01",
-    ],
-    repositories = ["https://dl.google.com/dl/android/maven2"],
-)
-
-maven_server(
-    name = "google_server",
-    url = "https://dl.google.com/dl/android/maven2",
-)
-
-maven_jar(
-    name = "androidx_lifecycle",
-    artifact = "androidx.lifecycle:lifecycle-common:2.0.0",
-    sha1 = "e070ffae07452331bc5684734fce6831d531785c",
-    server = "google_server",
-)
-
-maven_jar(
-     name = "androidx_concurrent_futures",
-     artifact = "androidx.concurrent:concurrent-futures:1.0.0-alpha03",
-     sha1 = "b528df95c7e2fefa2210c0c742bf3e491c1818ae",
-     server = "google_server",
-)
-
-maven_jar(
-    name = "com_google_guava_android",
-    artifact = "com.google.guava:guava:27.0.1-android",
-    sha1 = "b7e1c37f66ef193796ccd7ea6e80c2b05426182d",
-)
-
-maven_jar(
-    name = "com_google_common_flogger",
-    artifact = "com.google.flogger:flogger:0.3.1",
-    sha1 = "585030fe1ec709760cbef997a459729fb965df0e",
-)
-
-maven_jar(
-    name = "com_google_common_flogger_system_backend",
-    artifact = "com.google.flogger:flogger-system-backend:0.3.1",
-    sha1 = "287b569d76abcd82f9de87fe41829fbc7ebd8ac9",
-)
-
-maven_jar(
-    name = "com_google_code_findbugs",
-    artifact = "com.google.code.findbugs:jsr305:3.0.2",
-    sha1 = "25ea2e8b0c338a877313bd4672d3fe056ea78f0d",
-)
-
 # You may run setup_android.sh to install Android SDK and NDK.
 android_ndk_repository(
    name = "androidndk",
@@ -254,14 +209,13 @@ android_sdk_repository(

 # iOS basic build deps.

-load("@bazel_tools//tools/build_defs/repo:git.bzl", "git_repository")
-
-git_repository(
+http_archive(
    name = "build_bazel_rules_apple",
-    remote = "https://github.com/bazelbuild/rules_apple.git",
-    tag = "0.18.0",
+    sha256 = "7a7afdd4869bb201c9352eed2daf37294d42b093579b70423490c1b4d4f6ce42",
+    url = "https://github.com/bazelbuild/rules_apple/releases/download/0.19.0/rules_apple.0.19.0.tar.gz",
    patches = [
-        "@//third_party:rules_apple_c0863d0596ae6b769a29fa3fb72ff036444fd249.diff",
+        # Bypass checking ios unit test runner when building MP ios applications.
+        "@//third_party:build_bazel_rules_apple_bypass_test_runner_check.diff"
    ],
    patch_args = [
        "-p1",
@@ -298,3 +252,50 @@ http_archive(
    strip_prefix = "google-toolbox-for-mac-2.2.1",
    build_file = "@//third_party:google_toolbox_for_mac.BUILD",
 )
+
+# Maven dependencies.
+
+RULES_JVM_EXTERNAL_TAG = "3.2"
+RULES_JVM_EXTERNAL_SHA = "82262ff4223c5fda6fb7ff8bd63db8131b51b413d26eb49e3131037e79e324af"
+
+http_archive(
+    name = "rules_jvm_external",
+    strip_prefix = "rules_jvm_external-%s" % RULES_JVM_EXTERNAL_TAG,
+    sha256 = RULES_JVM_EXTERNAL_SHA,
+    url = "https://github.com/bazelbuild/rules_jvm_external/archive/%s.zip" % RULES_JVM_EXTERNAL_TAG,
+)
+
+load("@rules_jvm_external//:defs.bzl", "maven_install")
+
+# Important: there can only be one maven_install rule. Add new maven deps here.
+maven_install(
+    name = "maven",
+    artifacts = [
+        "junit:junit:4.12",
+        "androidx.test.espresso:espresso-core:3.1.1",
+        "org.hamcrest:hamcrest-library:1.3",
+        "androidx.concurrent:concurrent-futures:1.0.0-alpha03",
+        "androidx.lifecycle:lifecycle-common:2.2.0",
+        "androidx.annotation:annotation:aar:1.1.0",
+        "androidx.appcompat:appcompat:aar:1.1.0-rc01",
+        "androidx.camera:camera-core:aar:1.0.0-alpha06",
+        "androidx.camera:camera-camera2:aar:1.0.0-alpha06",
+        "androidx.constraintlayout:constraintlayout:aar:1.1.3",
+        "androidx.core:core:aar:1.1.0-rc03",
+        "androidx.legacy:legacy-support-v4:aar:1.0.0",
+        "androidx.recyclerview:recyclerview:aar:1.1.0-beta02",
+        "com.google.android.material:material:aar:1.0.0-rc01",
+        "com.google.code.findbugs:jsr305:3.0.2",
+        "com.google.flogger:flogger-system-backend:0.3.1",
+        "com.google.flogger:flogger:0.3.1",
+        "com.google.guava:guava:27.0.1-android",
+    ],
+    repositories = [
+        "https://jcenter.bintray.com",
+        "https://maven.google.com",
+        "https://dl.google.com/dl/android/maven2",
+        "https://repo1.maven.org/maven2",
+    ],
+    fetch_sources = True,
+    version_conflict_policy = "pinned",
+)
@@ -14,6 +14,9 @@

 licenses(["notice"])  # Apache 2.0

+# Note: yes, these need to use "//external:android/crosstool", not
+# @androidndk//:default_crosstool.
+
 config_setting(
    name = "android",
    values = {"crosstool_top": "//external:android/crosstool"},
@@ -9,6 +9,7 @@
    "mediapipe/examples/ios/facedetectiongpu/BUILD",
    "mediapipe/examples/ios/handdetectiongpu/BUILD",
    "mediapipe/examples/ios/handtrackinggpu/BUILD",
+    "mediapipe/examples/ios/multihandtrackinggpu/BUILD",
    "mediapipe/examples/ios/objectdetectioncpu/BUILD",
    "mediapipe/examples/ios/objectdetectiongpu/BUILD"
  ],
@@ -18,6 +19,7 @@
    "//mediapipe/examples/ios/facedetectiongpu:FaceDetectionGpuApp",
    "//mediapipe/examples/ios/handdetectiongpu:HandDetectionGpuApp",
    "//mediapipe/examples/ios/handtrackinggpu:HandTrackingGpuApp",
+    "//mediapipe/examples/ios/multihandtrackinggpu:MultiHandTrackingGpuApp",
    "//mediapipe/examples/ios/objectdetectioncpu:ObjectDetectionCpuApp",
    "//mediapipe/examples/ios/objectdetectiongpu:ObjectDetectionGpuApp",
    "//mediapipe/objc:mediapipe_framework_ios"
@@ -84,6 +86,8 @@
    "mediapipe/examples/ios/handdetectiongpu/Base.lproj",
    "mediapipe/examples/ios/handtrackinggpu",
    "mediapipe/examples/ios/handtrackinggpu/Base.lproj",
+    "mediapipe/examples/ios/multihandtrackinggpu",
+    "mediapipe/examples/ios/multihandtrackinggpu/Base.lproj",
    "mediapipe/examples/ios/objectdetectioncpu",
    "mediapipe/examples/ios/objectdetectioncpu/Base.lproj",
    "mediapipe/examples/ios/objectdetectiongpu",
@@ -16,6 +16,7 @@
    "mediapipe/examples/ios/facedetectiongpu",
    "mediapipe/examples/ios/handdetectiongpu",
    "mediapipe/examples/ios/handtrackinggpu",
+    "mediapipe/examples/ios/multihandtrackinggpu",
    "mediapipe/examples/ios/objectdetectioncpu",
    "mediapipe/examples/ios/objectdetectiongpu"
  ],
@@ -113,8 +113,15 @@ class SpectrogramCalculator : public CalculatorBase {
  ::mediapipe::Status Close(CalculatorContext* cc) override;

 private:
-  Timestamp CurrentOutputTimestamp() {
-    // Current output timestamp is the *center* of the next frame to be
+  Timestamp CurrentOutputTimestamp(CalculatorContext* cc) {
+    if (use_local_timestamp_) {
+      return cc->InputTimestamp();
+    }
+    return CumulativeOutputTimestamp();
+  }
+
+  Timestamp CumulativeOutputTimestamp() {
+    // Cumulative output timestamp is the *center* of the next frame to be
    // emitted, hence delayed by half a window duration compared to relevant
    // input timestamp.
    return initial_input_timestamp_ +
@@ -141,6 +148,7 @@ class SpectrogramCalculator : public CalculatorBase {
      const OutputMatrixType postprocess_output_fn(const OutputMatrixType&),
      CalculatorContext* cc);

+  bool use_local_timestamp_;
  double input_sample_rate_;
  bool pad_final_packet_;
  int frame_duration_samples_;
@@ -173,6 +181,8 @@ const float SpectrogramCalculator::kLnPowerToDb = 4.342944819032518;
  SpectrogramCalculatorOptions spectrogram_options =
      cc->Options<SpectrogramCalculatorOptions>();

+  use_local_timestamp_ = spectrogram_options.use_local_timestamp();
+
  if (spectrogram_options.frame_duration_seconds() <= 0.0) {
    ::mediapipe::InvalidArgumentErrorBuilder(MEDIAPIPE_LOC)
        << "Invalid or missing frame_duration_seconds.\n"
@@ -351,11 +361,11 @@ template <class OutputMatrixType>
        << "Inconsistent number of spectrogram channels.";
    if (allow_multichannel_input_) {
      cc->Outputs().Index(0).Add(spectrogram_matrices.release(),
-                                 CurrentOutputTimestamp());
+                                 CurrentOutputTimestamp(cc));
    } else {
      cc->Outputs().Index(0).Add(
          new OutputMatrixType(spectrogram_matrices->at(0)),
-          CurrentOutputTimestamp());
+          CurrentOutputTimestamp(cc));
    }
    cumulative_completed_frames_ += output_vectors.size();
  }
@@ -66,4 +66,11 @@ message SpectrogramCalculatorOptions {
  // uniformly regardless of output type (i.e., even dBs are multiplied, not
  // offset).
  optional double output_scale = 7 [default = 1.0];
+
+  // If use_local_timestamp is true, the output packet's timestamp is based on
+  // the last sample of the packet and it's inferred from the latest input
+  // packet's timestamp.  If false, the output packet's timestamp is based on
+  // the cumulative timestamping, which is inferred from the intial input
+  // timestamp and the cumulative number of samples.
+  optional bool use_local_timestamp = 8 [default = false];
 }
@@ -13,12 +13,12 @@
 # limitations under the License.
 #

+load("//mediapipe/framework/port:build_config.bzl", "mediapipe_cc_proto_library")
+
 licenses(["notice"])  # Apache 2.0

 package(default_visibility = ["//visibility:private"])

-load("//mediapipe/framework/port:build_config.bzl", "mediapipe_cc_proto_library")
-
 proto_library(
    name = "concatenate_vector_calculator_proto",
    srcs = ["concatenate_vector_calculator.proto"],
@@ -26,6 +26,13 @@ proto_library(
    deps = ["//mediapipe/framework:calculator_proto"],
 )

+proto_library(
+    name = "dequantize_byte_array_calculator_proto",
+    srcs = ["dequantize_byte_array_calculator.proto"],
+    visibility = ["//visibility:public"],
+    deps = ["//mediapipe/framework:calculator_proto"],
+)
+
 proto_library(
    name = "packet_cloner_calculator_proto",
    srcs = ["packet_cloner_calculator.proto"],
@@ -40,6 +47,13 @@ proto_library(
    deps = ["//mediapipe/framework:calculator_proto"],
 )

+proto_library(
+    name = "packet_thinner_calculator_proto",
+    srcs = ["packet_thinner_calculator.proto"],
+    visibility = ["//visibility:public"],
+    deps = ["//mediapipe/framework:calculator_proto"],
+)
+
 proto_library(
    name = "split_vector_calculator_proto",
    srcs = ["split_vector_calculator.proto"],
@@ -72,6 +86,22 @@ proto_library(
    ],
 )

+proto_library(
+    name = "constant_side_packet_calculator_proto",
+    srcs = ["constant_side_packet_calculator.proto"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_proto",
+    ],
+)
+
+proto_library(
+    name = "clip_vector_size_calculator_proto",
+    srcs = ["clip_vector_size_calculator.proto"],
+    visibility = ["//visibility:public"],
+    deps = ["//mediapipe/framework:calculator_proto"],
+)
+
 mediapipe_cc_proto_library(
    name = "packet_cloner_calculator_cc_proto",
    srcs = ["packet_cloner_calculator.proto"],
@@ -88,6 +118,14 @@ mediapipe_cc_proto_library(
    deps = [":packet_resampler_calculator_proto"],
 )

+mediapipe_cc_proto_library(
+    name = "packet_thinner_calculator_cc_proto",
+    srcs = ["packet_thinner_calculator.proto"],
+    cc_deps = ["//mediapipe/framework:calculator_cc_proto"],
+    visibility = ["//visibility:public"],
+    deps = [":packet_thinner_calculator_proto"],
+)
+
 mediapipe_cc_proto_library(
    name = "split_vector_calculator_cc_proto",
    srcs = ["split_vector_calculator.proto"],
@@ -104,6 +142,22 @@ mediapipe_cc_proto_library(
    deps = [":concatenate_vector_calculator_proto"],
 )

+mediapipe_cc_proto_library(
+    name = "clip_vector_size_calculator_cc_proto",
+    srcs = ["clip_vector_size_calculator.proto"],
+    cc_deps = ["//mediapipe/framework:calculator_cc_proto"],
+    visibility = ["//visibility:public"],
+    deps = [":clip_vector_size_calculator_proto"],
+)
+
+mediapipe_cc_proto_library(
+    name = "dequantize_byte_array_calculator_cc_proto",
+    srcs = ["dequantize_byte_array_calculator.proto"],
+    cc_deps = ["//mediapipe/framework:calculator_cc_proto"],
+    visibility = ["//visibility:public"],
+    deps = [":dequantize_byte_array_calculator_proto"],
+)
+
 mediapipe_cc_proto_library(
    name = "quantize_float_vector_calculator_cc_proto",
    srcs = ["quantize_float_vector_calculator.proto"],
@@ -128,6 +182,14 @@ mediapipe_cc_proto_library(
    deps = [":gate_calculator_proto"],
 )

+mediapipe_cc_proto_library(
+    name = "constant_side_packet_calculator_cc_proto",
+    srcs = ["constant_side_packet_calculator.proto"],
+    cc_deps = ["//mediapipe/framework:calculator_cc_proto"],
+    visibility = ["//visibility:public"],
+    deps = [":constant_side_packet_calculator_proto"],
+)
+
 cc_library(
    name = "add_header_calculator",
    srcs = ["add_header_calculator.cc"],
@@ -135,6 +197,7 @@ cc_library(
    deps = [
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/port:logging",
+        "//mediapipe/framework/port:status",
    ],
    alwayslink = 1,
 )
@@ -154,6 +217,71 @@ cc_test(
    ],
 )

+cc_library(
+    name = "begin_loop_calculator",
+    srcs = ["begin_loop_calculator.cc"],
+    hdrs = ["begin_loop_calculator.h"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_context",
+        "//mediapipe/framework:calculator_contract",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:collection_item_id",
+        "//mediapipe/framework:packet",
+        "//mediapipe/framework/formats:detection_cc_proto",
+        "//mediapipe/framework/formats:landmark_cc_proto",
+        "//mediapipe/framework/formats:matrix",
+        "//mediapipe/framework/formats:rect_cc_proto",
+        "//mediapipe/framework/port:integral_types",
+        "//mediapipe/framework/port:ret_check",
+        "//mediapipe/framework/port:status",
+        "@com_google_absl//absl/memory",
+    ],
+    alwayslink = 1,
+)
+
+cc_library(
+    name = "end_loop_calculator",
+    srcs = ["end_loop_calculator.cc"],
+    hdrs = ["end_loop_calculator.h"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_context",
+        "//mediapipe/framework:calculator_contract",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:collection_item_id",
+        "//mediapipe/framework:packet",
+        "//mediapipe/framework/formats:classification_cc_proto",
+        "//mediapipe/framework/formats:landmark_cc_proto",
+        "//mediapipe/framework/formats:rect_cc_proto",
+        "//mediapipe/framework/port:integral_types",
+        "//mediapipe/framework/port:ret_check",
+        "//mediapipe/framework/port:status",
+        "//mediapipe/util:render_data_cc_proto",
+        "@org_tensorflow//tensorflow/lite:framework",
+    ],
+    alwayslink = 1,
+)
+
+cc_test(
+    name = "begin_end_loop_calculator_graph_test",
+    srcs = ["begin_end_loop_calculator_graph_test.cc"],
+    deps = [
+        ":begin_loop_calculator",
+        ":end_loop_calculator",
+        ":gate_calculator",
+        "//mediapipe/framework:calculator_context",
+        "//mediapipe/framework:calculator_contract",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:packet",
+        "//mediapipe/framework/port:gtest_main",
+        "//mediapipe/framework/port:integral_types",
+        "//mediapipe/framework/port:parse_text_proto",
+        "//mediapipe/framework/port:status",
+        "@com_google_absl//absl/memory",
+    ],
+)
+
 cc_library(
    name = "concatenate_vector_calculator",
    srcs = ["concatenate_vector_calculator.cc"],
@@ -193,6 +321,50 @@ cc_test(
    srcs = ["concatenate_vector_calculator_test.cc"],
    deps = [
        ":concatenate_vector_calculator",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:calculator_runner",
+        "//mediapipe/framework:timestamp",
+        "//mediapipe/framework/port:gtest_main",
+        "//mediapipe/framework/port:parse_text_proto",
+        "//mediapipe/framework/port:status",
+        "@com_google_absl//absl/strings",
+    ],
+)
+
+cc_library(
+    name = "clip_vector_size_calculator",
+    srcs = ["clip_vector_size_calculator.cc"],
+    hdrs = ["clip_vector_size_calculator.h"],
+    visibility = ["//visibility:public"],
+    deps = [
+        ":clip_vector_size_calculator_cc_proto",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/formats:detection_cc_proto",
+        "//mediapipe/framework/formats:rect_cc_proto",
+        "//mediapipe/framework/port:ret_check",
+        "//mediapipe/framework/port:status",
+        "@org_tensorflow//tensorflow/lite:framework",
+    ],
+    alwayslink = 1,
+)
+
+cc_library(
+    name = "clip_detection_vector_size_calculator",
+    srcs = ["clip_detection_vector_size_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        ":clip_vector_size_calculator",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/formats:detection_cc_proto",
+    ],
+    alwayslink = 1,
+)
+
+cc_test(
+    name = "clip_vector_size_calculator_test",
+    srcs = ["clip_vector_size_calculator_test.cc"],
+    deps = [
+        ":clip_vector_size_calculator",
        "//mediapipe/calculators/core:packet_resampler_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:calculator_runner",
@@ -285,7 +457,7 @@ cc_library(
        "//visibility:public",
    ],
    deps = [
-        "//mediapipe/calculators/core:packet_cloner_calculator_cc_proto",
+        ":packet_cloner_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "@com_google_absl//absl/strings",
    ],
@@ -316,6 +488,37 @@ cc_test(
    ],
 )

+cc_library(
+    name = "packet_thinner_calculator",
+    srcs = ["packet_thinner_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/calculators/core:packet_thinner_calculator_cc_proto",
+        "//mediapipe/framework:calculator_context",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/formats:video_stream_header",
+        "//mediapipe/framework/port:integral_types",
+        "//mediapipe/framework/port:logging",
+        "//mediapipe/framework/port:status",
+    ],
+    alwayslink = 1,
+)
+
+cc_test(
+    name = "packet_thinner_calculator_test",
+    srcs = ["packet_thinner_calculator_test.cc"],
+    deps = [
+        ":packet_thinner_calculator",
+        "//mediapipe/calculators/core:packet_thinner_calculator_cc_proto",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:calculator_runner",
+        "//mediapipe/framework/formats:video_stream_header",
+        "//mediapipe/framework/port:gtest_main",
+        "//mediapipe/framework/port:integral_types",
+        "@com_google_absl//absl/strings",
+    ],
+)
+
 cc_library(
    name = "pass_through_calculator",
    srcs = ["pass_through_calculator.cc"],
@@ -387,6 +590,48 @@ cc_library(
    alwayslink = 1,
 )

+cc_library(
+    name = "string_to_int_calculator",
+    srcs = ["string_to_int_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/port:integral_types",
+        "//mediapipe/framework/port:status",
+        "@com_google_absl//absl/strings",
+    ],
+    alwayslink = 1,
+)
+
+cc_library(
+    name = "side_packet_to_stream_calculator",
+    srcs = ["side_packet_to_stream_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/port:logging",
+        "//mediapipe/framework/port:ret_check",
+        "//mediapipe/framework/port:status",
+    ],
+    alwayslink = 1,
+)
+
+cc_test(
+    name = "side_packet_to_stream_calculator_test",
+    srcs = ["side_packet_to_stream_calculator_test.cc"],
+    deps = [
+        ":side_packet_to_stream_calculator",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/port:gtest_main",
+        "//mediapipe/framework/port:integral_types",
+        "//mediapipe/framework/port:parse_text_proto",
+        "//mediapipe/framework/port:status",
+        "//mediapipe/framework/tool:options_util",
+        "@com_google_absl//absl/memory",
+        "@com_google_absl//absl/strings",
+    ],
+)
+
 cc_test(
    name = "immediate_mux_calculator_test",
    srcs = ["immediate_mux_calculator_test.cc"],
@@ -411,6 +656,7 @@ cc_test(
 cc_library(
    name = "packet_resampler_calculator",
    srcs = ["packet_resampler_calculator.cc"],
+    hdrs = ["packet_resampler_calculator.h"],
    visibility = [
        "//visibility:public",
    ],
@@ -434,17 +680,17 @@ cc_library(
 cc_test(
    name = "packet_resampler_calculator_test",
    timeout = "short",
-    srcs = ["packet_resampler_calculator_test.cc"],
+    srcs = [
+        "packet_resampler_calculator_test.cc",
+    ],
    deps = [
        ":packet_resampler_calculator",
        "//mediapipe/calculators/core:packet_resampler_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:calculator_runner",
-        "//mediapipe/framework:timestamp",
        "//mediapipe/framework/formats:video_stream_header",
        "//mediapipe/framework/port:gtest_main",
        "//mediapipe/framework/port:parse_text_proto",
-        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/strings",
    ],
 )
@@ -453,15 +699,17 @@ cc_test(
    name = "previous_loopback_calculator_test",
    srcs = ["previous_loopback_calculator_test.cc"],
    deps = [
+        ":gate_calculator",
+        ":make_pair_calculator",
+        ":pass_through_calculator",
        ":previous_loopback_calculator",
-        "//mediapipe/calculators/core:make_pair_calculator",
-        "//mediapipe/calculators/core:pass_through_calculator",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:calculator_runner",
        "//mediapipe/framework:timestamp",
        "//mediapipe/framework/port:gtest_main",
        "//mediapipe/framework/port:integral_types",
        "//mediapipe/framework/port:parse_text_proto",
+        "//mediapipe/framework/port:status",
        "//mediapipe/framework/stream_handler:immediate_input_stream_handler",
        "//mediapipe/framework/tool:sink",
        "@com_google_absl//absl/time",
@@ -529,14 +777,23 @@ cc_library(
    visibility = ["//visibility:public"],
    deps = [
        ":split_vector_calculator_cc_proto",
+        "//mediapipe/framework/formats:detection_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/formats:landmark_cc_proto",
+        "//mediapipe/framework/formats:rect_cc_proto",
+        "//mediapipe/framework/formats:matrix",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "//mediapipe/util:resource_util",
        "@org_tensorflow//tensorflow/lite:framework",
        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
-    ],
+    ] + select({
+        "//mediapipe/gpu:disable_gpu": [],
+        "//mediapipe:ios": [],
+        "//conditions:default": [
+            "@org_tensorflow//tensorflow/lite/delegates/gpu/gl:gl_buffer",
+        ],
+    }),
    alwayslink = 1,
 )

@@ -558,6 +815,32 @@ cc_test(
    ],
 )

+cc_library(
+    name = "dequantize_byte_array_calculator",
+    srcs = ["dequantize_byte_array_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        ":dequantize_byte_array_calculator_cc_proto",
+        "//mediapipe/framework:calculator_context",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/port:status",
+    ],
+    alwayslink = 1,
+)
+
+cc_test(
+    name = "dequantize_byte_array_calculator_test",
+    srcs = ["dequantize_byte_array_calculator_test.cc"],
+    deps = [
+        ":dequantize_byte_array_calculator",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:calculator_runner",
+        "//mediapipe/framework/port:gtest_main",
+        "//mediapipe/framework/port:parse_text_proto",
+        "//mediapipe/framework/port:status",
+    ],
+)
+
 cc_library(
    name = "quantize_float_vector_calculator",
    srcs = ["quantize_float_vector_calculator.cc"],
@@ -694,3 +977,56 @@ cc_test(
        "//mediapipe/framework/port:status",
    ],
 )
+
+cc_library(
+    name = "stream_to_side_packet_calculator",
+    srcs = ["stream_to_side_packet_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:timestamp",
+        "//mediapipe/framework/port:status",
+    ],
+    alwayslink = 1,
+)
+
+cc_test(
+    name = "stream_to_side_packet_calculator_test",
+    srcs = ["stream_to_side_packet_calculator_test.cc"],
+    deps = [
+        ":stream_to_side_packet_calculator",
+        "//mediapipe/framework:calculator_runner",
+        "//mediapipe/framework:packet",
+        "//mediapipe/framework:timestamp",
+        "//mediapipe/framework/port:gtest_main",
+        "//mediapipe/framework/port:status",
+        "@com_google_absl//absl/memory",
+    ],
+)
+
+cc_library(
+    name = "constant_side_packet_calculator",
+    srcs = ["constant_side_packet_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        ":constant_side_packet_calculator_cc_proto",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:collection_item_id",
+        "//mediapipe/framework/port:ret_check",
+        "//mediapipe/framework/port:status",
+    ],
+    alwayslink = 1,
+)
+
+cc_test(
+    name = "constant_side_packet_calculator_test",
+    srcs = ["constant_side_packet_calculator_test.cc"],
+    deps = [
+        ":constant_side_packet_calculator",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/port:gtest_main",
+        "//mediapipe/framework/port:parse_text_proto",
+        "//mediapipe/framework/port:status",
+        "@com_google_absl//absl/strings",
+    ],
+)
@@ -13,11 +13,12 @@
 // limitations under the License.

 #include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/port/canonical_errors.h"
 #include "mediapipe/framework/port/logging.h"

 namespace mediapipe {

-// Attach the header from one stream to another stream.
+// Attach the header from a stream or side input to another stream.
 //
 // The header stream (tag HEADER) must not have any packets in it.
 //
@@ -25,17 +26,53 @@ namespace mediapipe {
 // calculator to not need a header or to accept a separate stream with
 // a header, that would be more future proof.
 //
+// Example usage 1:
+// node {
+//   calculator: "AddHeaderCalculator"
+//   input_stream: "DATA:audio"
+//   input_stream: "HEADER:audio_header"
+//   output_stream: "audio_with_header"
+// }
+//
+// Example usage 2:
+// node {
+//   calculator: "AddHeaderCalculator"
+//   input_stream: "DATA:audio"
+//   input_side_packet: "HEADER:audio_header"
+//   output_stream: "audio_with_header"
+// }
+//
 class AddHeaderCalculator : public CalculatorBase {
 public:
  static ::mediapipe::Status GetContract(CalculatorContract* cc) {
-    cc->Inputs().Tag("HEADER").SetNone();
+    bool has_side_input = false;
+    bool has_header_stream = false;
+    if (cc->InputSidePackets().HasTag("HEADER")) {
+      cc->InputSidePackets().Tag("HEADER").SetAny();
+      has_side_input = true;
+    }
+    if (cc->Inputs().HasTag("HEADER")) {
+      cc->Inputs().Tag("HEADER").SetNone();
+      has_header_stream = true;
+    }
+    if (has_side_input == has_header_stream) {
+      return mediapipe::InvalidArgumentError(
+          "Header must be provided via exactly one of side input and input "
+          "stream");
+    }
    cc->Inputs().Tag("DATA").SetAny();
    cc->Outputs().Index(0).SetSameAs(&cc->Inputs().Tag("DATA"));
    return ::mediapipe::OkStatus();
  }

  ::mediapipe::Status Open(CalculatorContext* cc) override {
-    const Packet& header = cc->Inputs().Tag("HEADER").Header();
+    Packet header;
+    if (cc->InputSidePackets().HasTag("HEADER")) {
+      header = cc->InputSidePackets().Tag("HEADER");
+    }
+    if (cc->Inputs().HasTag("HEADER")) {
+      header = cc->Inputs().Tag("HEADER").Header();
+    }
    if (!header.IsEmpty()) {
      cc->Outputs().Index(0).SetHeader(header);
    }
@@ -14,8 +14,10 @@

 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/calculator_runner.h"
+#include "mediapipe/framework/port/canonical_errors.h"
 #include "mediapipe/framework/port/gmock.h"
 #include "mediapipe/framework/port/gtest.h"
+#include "mediapipe/framework/port/status.h"
 #include "mediapipe/framework/port/status_matchers.h"
 #include "mediapipe/framework/timestamp.h"
 #include "mediapipe/framework/tool/validate_type.h"
@@ -24,7 +26,7 @@ namespace mediapipe {

 class AddHeaderCalculatorTest : public ::testing::Test {};

-TEST_F(AddHeaderCalculatorTest, Works) {
+TEST_F(AddHeaderCalculatorTest, HeaderStream) {
  CalculatorGraphConfig::Node node;
  node.set_calculator("AddHeaderCalculator");
  node.add_input_stream("HEADER:header_stream");
@@ -96,4 +98,62 @@ TEST_F(AddHeaderCalculatorTest, NoPacketsOnHeaderStream) {
  ASSERT_FALSE(runner.Run().ok());
 }

+TEST_F(AddHeaderCalculatorTest, InputSidePacket) {
+  CalculatorGraphConfig::Node node;
+  node.set_calculator("AddHeaderCalculator");
+  node.add_input_stream("DATA:data_stream");
+  node.add_output_stream("merged_stream");
+  node.add_input_side_packet("HEADER:header");
+
+  CalculatorRunner runner(node);
+
+  // Set header and add 5 packets.
+  runner.MutableSidePackets()->Tag("HEADER") =
+      Adopt(new std::string("my_header"));
+  for (int i = 0; i < 5; ++i) {
+    Packet packet = Adopt(new int(i)).At(Timestamp(i * 1000));
+    runner.MutableInputs()->Tag("DATA").packets.push_back(packet);
+  }
+
+  // Run calculator.
+  MP_ASSERT_OK(runner.Run());
+
+  ASSERT_EQ(1, runner.Outputs().NumEntries());
+
+  // Test output.
+  EXPECT_EQ(std::string("my_header"),
+            runner.Outputs().Index(0).header.Get<std::string>());
+  const std::vector<Packet>& output_packets = runner.Outputs().Index(0).packets;
+  ASSERT_EQ(5, output_packets.size());
+  for (int i = 0; i < 5; ++i) {
+    const int val = output_packets[i].Get<int>();
+    EXPECT_EQ(i, val);
+    EXPECT_EQ(Timestamp(i * 1000), output_packets[i].Timestamp());
+  }
+}
+
+TEST_F(AddHeaderCalculatorTest, UsingBothSideInputAndStream) {
+  CalculatorGraphConfig::Node node;
+  node.set_calculator("AddHeaderCalculator");
+  node.add_input_stream("HEADER:header_stream");
+  node.add_input_stream("DATA:data_stream");
+  node.add_output_stream("merged_stream");
+  node.add_input_side_packet("HEADER:header");
+
+  CalculatorRunner runner(node);
+
+  // Set both headers and add 5 packets.
+  runner.MutableSidePackets()->Tag("HEADER") =
+      Adopt(new std::string("my_header"));
+  runner.MutableSidePackets()->Tag("HEADER") =
+      Adopt(new std::string("my_header"));
+  for (int i = 0; i < 5; ++i) {
+    Packet packet = Adopt(new int(i)).At(Timestamp(i * 1000));
+    runner.MutableInputs()->Tag("DATA").packets.push_back(packet);
+  }
+
+  // Run should fail because header can only be provided one way.
+  EXPECT_EQ(runner.Run().code(), ::mediapipe::InvalidArgumentError("").code());
+}
+
 }  // namespace mediapipe
@@ -0,0 +1,448 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <string>
+#include <vector>
+
+#include "absl/memory/memory.h"
+#include "mediapipe/calculators/core/begin_loop_calculator.h"
+#include "mediapipe/calculators/core/end_loop_calculator.h"
+#include "mediapipe/framework/calculator_contract.h"
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/packet.h"
+#include "mediapipe/framework/port/gmock.h"
+#include "mediapipe/framework/port/gtest.h"
+#include "mediapipe/framework/port/integral_types.h"
+#include "mediapipe/framework/port/parse_text_proto.h"
+#include "mediapipe/framework/port/status_matchers.h"  // NOLINT
+
+namespace mediapipe {
+namespace {
+
+MATCHER_P2(PacketOfIntsEq, timestamp, value, "") {
+  Timestamp actual_timestamp = arg.Timestamp();
+  const auto& actual_value = arg.template Get<std::vector<int>>();
+  return testing::Value(actual_timestamp, testing::Eq(timestamp)) &&
+         testing::Value(actual_value, testing::ElementsAreArray(value));
+}
+
+typedef BeginLoopCalculator<std::vector<int>> BeginLoopIntegerCalculator;
+REGISTER_CALCULATOR(BeginLoopIntegerCalculator);
+
+class IncrementCalculator : public CalculatorBase {
+ public:
+  static ::mediapipe::Status GetContract(CalculatorContract* cc) {
+    cc->Inputs().Index(0).Set<int>();
+    cc->Outputs().Index(0).Set<int>();
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Open(CalculatorContext* cc) override {
+    cc->SetOffset(TimestampDiff(0));
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Process(CalculatorContext* cc) override {
+    const int& input_int = cc->Inputs().Index(0).Get<int>();
+    auto output_int = absl::make_unique<int>(input_int + 1);
+    cc->Outputs().Index(0).Add(output_int.release(), cc->InputTimestamp());
+    return ::mediapipe::OkStatus();
+  }
+};
+
+REGISTER_CALCULATOR(IncrementCalculator);
+
+typedef EndLoopCalculator<std::vector<int>> EndLoopIntegersCalculator;
+REGISTER_CALCULATOR(EndLoopIntegersCalculator);
+
+class BeginEndLoopCalculatorGraphTest : public ::testing::Test {
+ protected:
+  void SetUp() override {
+    auto graph_config = ParseTextProtoOrDie<CalculatorGraphConfig>(
+        R"(
+          num_threads: 4
+          input_stream: "ints"
+          node {
+            calculator: "BeginLoopIntegerCalculator"
+            input_stream: "ITERABLE:ints"
+            output_stream: "ITEM:int"
+            output_stream: "BATCH_END:timestamp"
+          }
+          node {
+            calculator: "IncrementCalculator"
+            input_stream: "int"
+            output_stream: "int_plus_one"
+          }
+          node {
+            calculator: "EndLoopIntegersCalculator"
+            input_stream: "ITEM:int_plus_one"
+            input_stream: "BATCH_END:timestamp"
+            output_stream: "ITERABLE:ints_plus_one"
+          }
+        )");
+    tool::AddVectorSink("ints_plus_one", &graph_config, &output_packets_);
+    MP_ASSERT_OK(graph_.Initialize(graph_config));
+    MP_ASSERT_OK(graph_.StartRun({}));
+  }
+
+  void SendPacketOfInts(Timestamp timestamp, std::vector<int> ints) {
+    MP_ASSERT_OK(graph_.AddPacketToInputStream(
+        "ints", MakePacket<std::vector<int>>(std::move(ints)).At(timestamp)));
+  }
+
+  CalculatorGraph graph_;
+  std::vector<Packet> output_packets_;
+};
+
+TEST_F(BeginEndLoopCalculatorGraphTest, InputStreamForIterableIsEmpty) {
+  MP_ASSERT_OK(graph_.WaitUntilIdle());
+
+  // EndLoopCalc will forward the timestamp bound because there are no packets
+  // to process.
+  ASSERT_EQ(0, output_packets_.size());
+
+  MP_ASSERT_OK(graph_.CloseAllPacketSources());
+  MP_ASSERT_OK(graph_.WaitUntilDone());
+}
+
+TEST_F(BeginEndLoopCalculatorGraphTest, SingleEmptyVector) {
+  SendPacketOfInts(Timestamp(0), {});
+  MP_ASSERT_OK(graph_.WaitUntilIdle());
+
+  // EndLoopCalc will forward the timestamp bound because there are no elements
+  // in collection to output.
+  EXPECT_TRUE(output_packets_.empty());
+
+  MP_ASSERT_OK(graph_.CloseAllPacketSources());
+  MP_ASSERT_OK(graph_.WaitUntilDone());
+}
+
+TEST_F(BeginEndLoopCalculatorGraphTest, SingleNonEmptyVector) {
+  Timestamp input_timestamp = Timestamp(0);
+  SendPacketOfInts(input_timestamp, {0, 1, 2});
+  MP_ASSERT_OK(graph_.WaitUntilIdle());
+
+  EXPECT_THAT(output_packets_,
+              testing::ElementsAre(
+                  PacketOfIntsEq(input_timestamp, std::vector<int>{1, 2, 3})));
+
+  MP_ASSERT_OK(graph_.CloseAllPacketSources());
+  MP_ASSERT_OK(graph_.WaitUntilDone());
+}
+
+TEST_F(BeginEndLoopCalculatorGraphTest, MultipleVectors) {
+  Timestamp input_timestamp0 = Timestamp(0);
+  SendPacketOfInts(input_timestamp0, {0, 1});
+
+  Timestamp input_timestamp1 = Timestamp(1);
+  SendPacketOfInts(input_timestamp1, {});
+
+  Timestamp input_timestamp2 = Timestamp(2);
+  SendPacketOfInts(input_timestamp2, {2, 3});
+
+  MP_ASSERT_OK(graph_.CloseAllPacketSources());
+  MP_ASSERT_OK(graph_.WaitUntilDone());
+
+  // At input_timestamp1, EndLoopCalc will forward timestamp bound as there are
+  // no elements in vector to process.
+  EXPECT_THAT(output_packets_,
+              testing::ElementsAre(
+                  PacketOfIntsEq(input_timestamp0, std::vector<int>{1, 2}),
+                  PacketOfIntsEq(input_timestamp2, std::vector<int>{3, 4})));
+}
+
+// Passes non empty vector through or outputs empty vector in case of timestamp
+// bound update.
+class PassThroughOrEmptyVectorCalculator : public CalculatorBase {
+ public:
+  static ::mediapipe::Status GetContract(CalculatorContract* cc) {
+    cc->SetProcessTimestampBounds(true);
+    cc->Inputs().Index(0).Set<std::vector<int>>();
+    cc->Outputs().Index(0).Set<std::vector<int>>();
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Open(CalculatorContext* cc) override {
+    cc->SetOffset(TimestampDiff(0));
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Process(CalculatorContext* cc) override {
+    if (!cc->Inputs().Index(0).IsEmpty()) {
+      cc->Outputs().Index(0).AddPacket(cc->Inputs().Index(0).Value());
+    } else {
+      cc->Outputs().Index(0).AddPacket(
+          MakePacket<std::vector<int>>(std::vector<int>())
+              .At(cc->InputTimestamp()));
+    }
+    return ::mediapipe::OkStatus();
+  }
+};
+
+REGISTER_CALCULATOR(PassThroughOrEmptyVectorCalculator);
+
+class BeginEndLoopCalculatorGraphProcessingEmptyPacketsTest
+    : public ::testing::Test {
+ protected:
+  void SetUp() override {
+    auto graph_config = ParseTextProtoOrDie<CalculatorGraphConfig>(
+        R"(
+          num_threads: 4
+          input_stream: "ints"
+          input_stream: "force_ints_to_be_timestamp_bound_update"
+          node {
+            calculator: "GateCalculator"
+            input_stream: "ints"
+            input_stream: "DISALLOW:force_ints_to_be_timestamp_bound_update"
+            output_stream: "ints_passed_through"
+          }
+          node {
+            calculator: "BeginLoopIntegerCalculator"
+            input_stream: "ITERABLE:ints_passed_through"
+            output_stream: "ITEM:int"
+            output_stream: "BATCH_END:timestamp"
+          }
+          node {
+            calculator: "IncrementCalculator"
+            input_stream: "int"
+            output_stream: "int_plus_one"
+          }
+          node {
+            calculator: "EndLoopIntegersCalculator"
+            input_stream: "ITEM:int_plus_one"
+            input_stream: "BATCH_END:timestamp"
+            output_stream: "ITERABLE:ints_plus_one"
+          }
+          node {
+            calculator: "PassThroughOrEmptyVectorCalculator"
+            input_stream: "ints_plus_one"
+            output_stream: "ints_plus_one_passed_through"
+          }
+        )");
+    tool::AddVectorSink("ints_plus_one_passed_through", &graph_config,
+                        &output_packets_);
+    MP_ASSERT_OK(graph_.Initialize(graph_config));
+    MP_ASSERT_OK(graph_.StartRun({}));
+  }
+
+  void SendPacketOfIntsOrBound(Timestamp timestamp, std::vector<int> ints) {
+    // All "ints" packets which are empty are forced to be just timestamp
+    // bound updates for begin loop calculator.
+    bool force_ints_to_be_timestamp_bound_update = ints.empty();
+    MP_ASSERT_OK(graph_.AddPacketToInputStream(
+        "force_ints_to_be_timestamp_bound_update",
+        MakePacket<bool>(force_ints_to_be_timestamp_bound_update)
+            .At(timestamp)));
+    MP_ASSERT_OK(graph_.AddPacketToInputStream(
+        "ints", MakePacket<std::vector<int>>(std::move(ints)).At(timestamp)));
+  }
+
+  CalculatorGraph graph_;
+  std::vector<Packet> output_packets_;
+};
+
+TEST_F(BeginEndLoopCalculatorGraphProcessingEmptyPacketsTest,
+       SingleEmptyVector) {
+  SendPacketOfIntsOrBound(Timestamp(0), {});
+  MP_ASSERT_OK(graph_.WaitUntilIdle());
+
+  EXPECT_THAT(output_packets_, testing::ElementsAre(PacketOfIntsEq(
+                                   Timestamp(0), std::vector<int>{})));
+
+  MP_ASSERT_OK(graph_.CloseAllPacketSources());
+  MP_ASSERT_OK(graph_.WaitUntilDone());
+}
+
+TEST_F(BeginEndLoopCalculatorGraphProcessingEmptyPacketsTest,
+       SingleNonEmptyVector) {
+  SendPacketOfIntsOrBound(Timestamp(0), {0, 1, 2});
+  MP_ASSERT_OK(graph_.WaitUntilIdle());
+
+  EXPECT_THAT(output_packets_, testing::ElementsAre(PacketOfIntsEq(
+                                   Timestamp(0), std::vector<int>{1, 2, 3})));
+
+  MP_ASSERT_OK(graph_.CloseAllPacketSources());
+  MP_ASSERT_OK(graph_.WaitUntilDone());
+}
+
+TEST_F(BeginEndLoopCalculatorGraphProcessingEmptyPacketsTest, MultipleVectors) {
+  SendPacketOfIntsOrBound(Timestamp(0), {});
+  // Waiting until idle to guarantee all timestamp bound updates are processed
+  // individually. (Timestamp bounds updates occur in the provide config only
+  // if input is an empty vector.)
+  MP_ASSERT_OK(graph_.WaitUntilIdle());
+
+  SendPacketOfIntsOrBound(Timestamp(1), {0, 1});
+  SendPacketOfIntsOrBound(Timestamp(2), {});
+  // Waiting until idle to guarantee all timestamp bound updates are processed
+  // individually. (Timestamp bounds updates occur in the provide config only
+  // if input is an empty vector.)
+  MP_ASSERT_OK(graph_.WaitUntilIdle());
+
+  SendPacketOfIntsOrBound(Timestamp(3), {2, 3});
+  SendPacketOfIntsOrBound(Timestamp(4), {});
+  // Waiting until idle to guarantee all timestamp bound updates are processed
+  // individually. (Timestamp bounds updates occur in the provide config only
+  // if input is an empty vector.)
+  MP_ASSERT_OK(graph_.WaitUntilIdle());
+
+  MP_ASSERT_OK(graph_.CloseAllPacketSources());
+  MP_ASSERT_OK(graph_.WaitUntilDone());
+
+  EXPECT_THAT(
+      output_packets_,
+      testing::ElementsAre(PacketOfIntsEq(Timestamp(0), std::vector<int>{}),
+                           PacketOfIntsEq(Timestamp(1), std::vector<int>{1, 2}),
+                           PacketOfIntsEq(Timestamp(2), std::vector<int>{}),
+                           PacketOfIntsEq(Timestamp(3), std::vector<int>{3, 4}),
+                           PacketOfIntsEq(Timestamp(4), std::vector<int>{})));
+}
+
+class MultiplierCalculator : public CalculatorBase {
+ public:
+  static ::mediapipe::Status GetContract(CalculatorContract* cc) {
+    cc->Inputs().Index(0).Set<int>();
+    cc->Inputs().Index(1).Set<int>();
+    cc->Outputs().Index(0).Set<int>();
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Open(CalculatorContext* cc) override {
+    cc->SetOffset(TimestampDiff(0));
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Process(CalculatorContext* cc) override {
+    const int& input_int = cc->Inputs().Index(0).Get<int>();
+    const int& multiplier_int = cc->Inputs().Index(1).Get<int>();
+    auto output_int = absl::make_unique<int>(input_int * multiplier_int);
+    cc->Outputs().Index(0).Add(output_int.release(), cc->InputTimestamp());
+    return ::mediapipe::OkStatus();
+  }
+};
+
+REGISTER_CALCULATOR(MultiplierCalculator);
+
+class BeginEndLoopCalculatorGraphWithClonedInputsTest : public ::testing::Test {
+ protected:
+  void SetUp() override {
+    auto graph_config = ParseTextProtoOrDie<CalculatorGraphConfig>(
+        R"(
+          num_threads: 4
+          input_stream: "ints"
+          input_stream: "multiplier"
+          node {
+            calculator: "BeginLoopIntegerCalculator"
+            input_stream: "ITERABLE:ints"
+            input_stream: "CLONE:multiplier"
+            output_stream: "ITEM:int_at_loop"
+            output_stream: "CLONE:multiplier_cloned_at_loop"
+            output_stream: "BATCH_END:timestamp"
+          }
+          node {
+            calculator: "MultiplierCalculator"
+            input_stream: "int_at_loop"
+            input_stream: "multiplier_cloned_at_loop"
+            output_stream: "multiplied_int_at_loop"
+          }
+          node {
+            calculator: "EndLoopIntegersCalculator"
+            input_stream: "ITEM:multiplied_int_at_loop"
+            input_stream: "BATCH_END:timestamp"
+            output_stream: "ITERABLE:multiplied_ints"
+          }
+        )");
+    tool::AddVectorSink("multiplied_ints", &graph_config, &output_packets_);
+    MP_ASSERT_OK(graph_.Initialize(graph_config));
+    MP_ASSERT_OK(graph_.StartRun({}));
+  }
+
+  void SendPackets(Timestamp timestamp, int multiplier, std::vector<int> ints) {
+    MP_ASSERT_OK(graph_.AddPacketToInputStream(
+        "ints", MakePacket<std::vector<int>>(std::move(ints)).At(timestamp)));
+    MP_ASSERT_OK(graph_.AddPacketToInputStream(
+        "multiplier", MakePacket<int>(multiplier).At(timestamp)));
+  }
+
+  void SendMultiplier(Timestamp timestamp, int multiplier) {
+    MP_ASSERT_OK(graph_.AddPacketToInputStream(
+        "multiplier", MakePacket<int>(multiplier).At(timestamp)));
+  }
+
+  CalculatorGraph graph_;
+  std::vector<Packet> output_packets_;
+};
+
+TEST_F(BeginEndLoopCalculatorGraphWithClonedInputsTest,
+       InputStreamForIterableIsEmpty) {
+  Timestamp input_timestamp = Timestamp(42);
+  SendMultiplier(input_timestamp, /*multiplier=*/2);
+  MP_ASSERT_OK(graph_.WaitUntilIdle());
+
+  // EndLoopCalc will forward the timestamp bound because there are no packets
+  // to process.
+  ASSERT_EQ(0, output_packets_.size());
+
+  MP_ASSERT_OK(graph_.CloseAllPacketSources());
+  MP_ASSERT_OK(graph_.WaitUntilDone());
+}
+
+TEST_F(BeginEndLoopCalculatorGraphWithClonedInputsTest, SingleEmptyVector) {
+  SendPackets(Timestamp(0), /*multiplier=*/2, /*ints=*/{});
+  MP_ASSERT_OK(graph_.WaitUntilIdle());
+
+  // EndLoopCalc will forward the timestamp bound because there are no elements
+  // in collection to output.
+  EXPECT_TRUE(output_packets_.empty());
+
+  MP_ASSERT_OK(graph_.CloseAllPacketSources());
+  MP_ASSERT_OK(graph_.WaitUntilDone());
+}
+
+TEST_F(BeginEndLoopCalculatorGraphWithClonedInputsTest, SingleNonEmptyVector) {
+  Timestamp input_timestamp = Timestamp(42);
+  SendPackets(input_timestamp, /*multiplier=*/2, /*ints=*/{0, 1, 2});
+  MP_ASSERT_OK(graph_.WaitUntilIdle());
+
+  EXPECT_THAT(output_packets_,
+              testing::ElementsAre(
+                  PacketOfIntsEq(input_timestamp, std::vector<int>{0, 2, 4})));
+
+  MP_ASSERT_OK(graph_.CloseAllPacketSources());
+  MP_ASSERT_OK(graph_.WaitUntilDone());
+}
+
+TEST_F(BeginEndLoopCalculatorGraphWithClonedInputsTest, MultipleVectors) {
+  Timestamp input_timestamp0 = Timestamp(42);
+  SendPackets(input_timestamp0, /*multiplier=*/2, /*ints=*/{0, 1});
+
+  Timestamp input_timestamp1 = Timestamp(43);
+  SendPackets(input_timestamp1, /*multiplier=*/2, /*ints=*/{});
+
+  Timestamp input_timestamp2 = Timestamp(44);
+  SendPackets(input_timestamp2, /*multiplier=*/3, /*ints=*/{2, 3});
+
+  MP_ASSERT_OK(graph_.CloseAllPacketSources());
+  MP_ASSERT_OK(graph_.WaitUntilDone());
+
+  // At input_timestamp1, EndLoopCalc will forward timestamp bound as there are
+  // no elements in vector to process.
+  EXPECT_THAT(output_packets_,
+              testing::ElementsAre(
+                  PacketOfIntsEq(input_timestamp0, std::vector<int>{0, 2}),
+                  PacketOfIntsEq(input_timestamp2, std::vector<int>{6, 9})));
+}
+
+}  // namespace
+}  // namespace mediapipe
@@ -0,0 +1,45 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "mediapipe/calculators/core/begin_loop_calculator.h"
+
+#include <vector>
+
+#include "mediapipe/framework/formats/detection.pb.h"
+#include "mediapipe/framework/formats/landmark.pb.h"
+#include "mediapipe/framework/formats/matrix.h"
+#include "mediapipe/framework/formats/rect.pb.h"
+
+namespace mediapipe {
+
+// A calculator to process std::vector<NormalizedLandmarkList>.
+typedef BeginLoopCalculator<std::vector<::mediapipe::NormalizedLandmarkList>>
+    BeginLoopNormalizedLandmarkListVectorCalculator;
+REGISTER_CALCULATOR(BeginLoopNormalizedLandmarkListVectorCalculator);
+
+// A calculator to process std::vector<NormalizedRect>.
+typedef BeginLoopCalculator<std::vector<::mediapipe::NormalizedRect>>
+    BeginLoopNormalizedRectCalculator;
+REGISTER_CALCULATOR(BeginLoopNormalizedRectCalculator);
+
+// A calculator to process std::vector<Detection>.
+typedef BeginLoopCalculator<std::vector<::mediapipe::Detection>>
+    BeginLoopDetectionCalculator;
+REGISTER_CALCULATOR(BeginLoopDetectionCalculator);
+
+// A calculator to process std::vector<Matrix>.
+typedef BeginLoopCalculator<std::vector<Matrix>> BeginLoopMatrixCalculator;
+REGISTER_CALCULATOR(BeginLoopMatrixCalculator);
+
+}  // namespace mediapipe
@@ -0,0 +1,165 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#ifndef MEDIAPIPE_CALCULATORS_CORE_BEGIN_LOOP_CALCULATOR_H_
+#define MEDIAPIPE_CALCULATORS_CORE_BEGIN_LOOP_CALCULATOR_H_
+
+#include "absl/memory/memory.h"
+#include "mediapipe/framework/calculator_context.h"
+#include "mediapipe/framework/calculator_contract.h"
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/collection_item_id.h"
+#include "mediapipe/framework/packet.h"
+#include "mediapipe/framework/port/integral_types.h"
+#include "mediapipe/framework/port/ret_check.h"
+#include "mediapipe/framework/port/status.h"
+
+namespace mediapipe {
+
+// Calculator for implementing loops on iterable collections inside a MediaPipe
+// graph.
+//
+// It is designed to be used like:
+//
+// node {
+//   calculator:    "BeginLoopWithIterableCalculator"
+//   input_stream:  "ITERABLE:input_iterable"      # IterableT @ext_ts
+//   output_stream: "ITEM:input_element"           # ItemT     @loop_internal_ts
+//   output_stream: "BATCH_END:ext_ts"             # Timestamp @loop_internal_ts
+// }
+//
+// node {
+//   calculator:    "ElementToBlaConverterSubgraph"
+//   input_stream:  "ITEM:input_to_loop_body"      # ItemT     @loop_internal_ts
+//   output_stream: "BLA:output_of_loop_body"      # ItemU     @loop_internal_ts
+// }
+//
+// node {
+//   calculator:    "EndLoopWithOutputCalculator"
+//   input_stream:  "ITEM:output_of_loop_body"     # ItemU     @loop_internal_ts
+//   input_stream:  "BATCH_END:ext_ts"             # Timestamp @loop_internal_ts
+//   output_stream: "OUTPUT:aggregated_result"     # IterableU @ext_ts
+// }
+//
+// Input streams tagged with "CLONE" are cloned to the corresponding output
+// streams at loop timestamps. This ensures that a MediaPipe graph or sub-graph
+// can run multiple times, once per element in the "ITERABLE" for each pakcet
+// clone of the packets in the "CLONE" input streams.
+template <typename IterableT>
+class BeginLoopCalculator : public CalculatorBase {
+  using ItemT = typename IterableT::value_type;
+
+ public:
+  static ::mediapipe::Status GetContract(CalculatorContract* cc) {
+    // The below enables processing of timestamp bound updates, and that enables
+    // correct timestamp propagation by the companion EndLoopCalculator.
+    //
+    // For instance, Process() function will be still invoked even if upstream
+    // calculator has updated timestamp bound for ITERABLE input instead of
+    // providing actual value.
+    cc->SetProcessTimestampBounds(true);
+
+    // A non-empty packet in the optional "TICK" input stream wakes up the
+    // calculator.
+    // DEPRECATED as timestamp bound updates are processed by default in this
+    // calculator.
+    if (cc->Inputs().HasTag("TICK")) {
+      cc->Inputs().Tag("TICK").SetAny();
+    }
+
+    // An iterable collection in the input stream.
+    RET_CHECK(cc->Inputs().HasTag("ITERABLE"));
+    cc->Inputs().Tag("ITERABLE").Set<IterableT>();
+
+    // An element from the collection.
+    RET_CHECK(cc->Outputs().HasTag("ITEM"));
+    cc->Outputs().Tag("ITEM").Set<ItemT>();
+
+    RET_CHECK(cc->Outputs().HasTag("BATCH_END"));
+    cc->Outputs()
+        .Tag("BATCH_END")
+        .Set<Timestamp>(
+            // A flush signal to the corresponding EndLoopCalculator for it to
+            // emit the aggregated result with the timestamp contained in this
+            // flush signal packet.
+        );
+
+    // Input streams tagged with "CLONE" are cloned to the corresponding
+    // "CLONE" output streams at loop timestamps.
+    RET_CHECK(cc->Inputs().NumEntries("CLONE") ==
+              cc->Outputs().NumEntries("CLONE"));
+    if (cc->Inputs().NumEntries("CLONE") > 0) {
+      for (int i = 0; i < cc->Inputs().NumEntries("CLONE"); ++i) {
+        cc->Inputs().Get("CLONE", i).SetAny();
+        cc->Outputs().Get("CLONE", i).SetSameAs(&cc->Inputs().Get("CLONE", i));
+      }
+    }
+
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Process(CalculatorContext* cc) final {
+    Timestamp last_timestamp = loop_internal_timestamp_;
+    if (!cc->Inputs().Tag("ITERABLE").IsEmpty()) {
+      const IterableT& collection =
+          cc->Inputs().Tag("ITERABLE").template Get<IterableT>();
+      for (const auto& item : collection) {
+        cc->Outputs().Tag("ITEM").AddPacket(
+            MakePacket<ItemT>(item).At(loop_internal_timestamp_));
+        ForwardClonePackets(cc, loop_internal_timestamp_);
+        ++loop_internal_timestamp_;
+      }
+    }
+
+    // The collection was empty and nothing was processed.
+    if (last_timestamp == loop_internal_timestamp_) {
+      // Increment loop_internal_timestamp_ because it is used up now.
+      ++loop_internal_timestamp_;
+      for (auto it = cc->Outputs().begin(); it < cc->Outputs().end(); ++it) {
+        it->SetNextTimestampBound(loop_internal_timestamp_);
+      }
+    }
+
+    // The for loop processing the input collection already incremented
+    // loop_internal_timestamp_. To emit BATCH_END packet along the last
+    // non-BATCH_END packet, decrement by one.
+    cc->Outputs()
+        .Tag("BATCH_END")
+        .AddPacket(MakePacket<Timestamp>(cc->InputTimestamp())
+                       .At(Timestamp(loop_internal_timestamp_ - 1)));
+
+    return ::mediapipe::OkStatus();
+  }
+
+ private:
+  void ForwardClonePackets(CalculatorContext* cc, Timestamp output_timestamp) {
+    if (cc->Inputs().NumEntries("CLONE") > 0) {
+      for (int i = 0; i < cc->Inputs().NumEntries("CLONE"); ++i) {
+        if (!cc->Inputs().Get("CLONE", i).IsEmpty()) {
+          auto input_packet = cc->Inputs().Get("CLONE", i).Value();
+          cc->Outputs()
+              .Get("CLONE", i)
+              .AddPacket(std::move(input_packet).At(output_timestamp));
+        }
+      }
+    }
+  }
+
+  // Fake timestamps generated per element in collection.
+  Timestamp loop_internal_timestamp_ = Timestamp(0);
+};
+
+}  // namespace mediapipe
+
+#endif  // MEDIAPIPE_CALCULATORS_CORE_BEGIN_LOOP_CALCULATOR_H_
@@ -0,0 +1,26 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <vector>
+
+#include "mediapipe/calculators/core/clip_vector_size_calculator.h"
+#include "mediapipe/framework/formats/detection.pb.h"
+
+namespace mediapipe {
+
+typedef ClipVectorSizeCalculator<::mediapipe::Detection>
+    ClipDetectionVectorSizeCalculator;
+REGISTER_CALCULATOR(ClipDetectionVectorSizeCalculator);
+
+}  // namespace mediapipe
@@ -0,0 +1,33 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "mediapipe/calculators/core/clip_vector_size_calculator.h"
+
+#include <vector>
+
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/formats/detection.pb.h"
+#include "mediapipe/framework/formats/rect.pb.h"
+
+namespace mediapipe {
+
+typedef ClipVectorSizeCalculator<::mediapipe::NormalizedRect>
+    ClipNormalizedRectVectorSizeCalculator;
+REGISTER_CALCULATOR(ClipNormalizedRectVectorSizeCalculator);
+
+typedef ClipVectorSizeCalculator<::mediapipe::Detection>
+    ClipDetectionVectorSizeCalculator;
+REGISTER_CALCULATOR(ClipDetectionVectorSizeCalculator);
+
+}  // namespace mediapipe
@@ -0,0 +1,148 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#ifndef MEDIAPIPE_CALCULATORS_CORE_CLIP_VECTOR_SIZE_CALCULATOR_H_
+#define MEDIAPIPE_CALCULATORS_CORE_CLIP_VECTOR_SIZE_CALCULATOR_H_
+
+#include <type_traits>
+#include <vector>
+
+#include "mediapipe/calculators/core/clip_vector_size_calculator.pb.h"
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/port/canonical_errors.h"
+#include "mediapipe/framework/port/ret_check.h"
+#include "mediapipe/framework/port/status.h"
+
+namespace mediapipe {
+
+// Clips the size of the input vector of type T to a specified max_vec_size.
+// In a graph it will be used as:
+// node {
+//   calculator: "ClipIntVectorSizeCalculator"
+//   input_stream: "input_vector"
+//   output_stream: "output_vector"
+//   options {
+//     [mediapipe.ClipIntVectorSizeCalculatorOptions.ext] {
+//       max_vec_size: 5
+//     }
+//   }
+// }
+// Optionally, you can pass in a side packet that will override `max_vec_size`
+// that is specified in the options.
+template <typename T>
+class ClipVectorSizeCalculator : public CalculatorBase {
+ public:
+  static ::mediapipe::Status GetContract(CalculatorContract* cc) {
+    RET_CHECK(cc->Inputs().NumEntries() == 1);
+    RET_CHECK(cc->Outputs().NumEntries() == 1);
+
+    if (cc->Options<::mediapipe::ClipVectorSizeCalculatorOptions>()
+            .max_vec_size() < 1) {
+      return ::mediapipe::InternalError(
+          "max_vec_size should be greater than or equal to 1.");
+    }
+
+    cc->Inputs().Index(0).Set<std::vector<T>>();
+    cc->Outputs().Index(0).Set<std::vector<T>>();
+    // Optional input side packet that determines `max_vec_size`.
+    if (cc->InputSidePackets().NumEntries() > 0) {
+      cc->InputSidePackets().Index(0).Set<int>();
+    }
+
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Open(CalculatorContext* cc) override {
+    cc->SetOffset(TimestampDiff(0));
+    max_vec_size_ = cc->Options<::mediapipe::ClipVectorSizeCalculatorOptions>()
+                        .max_vec_size();
+    // Override `max_vec_size` if passed as side packet.
+    if (cc->InputSidePackets().NumEntries() > 0 &&
+        !cc->InputSidePackets().Index(0).IsEmpty()) {
+      max_vec_size_ = cc->InputSidePackets().Index(0).Get<int>();
+    }
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Process(CalculatorContext* cc) override {
+    if (max_vec_size_ < 1) {
+      return ::mediapipe::InternalError(
+          "max_vec_size should be greater than or equal to 1.");
+    }
+    if (cc->Inputs().Index(0).IsEmpty()) {
+      return ::mediapipe::OkStatus();
+    }
+
+    return ClipVectorSize<T>(std::is_copy_constructible<T>(), cc);
+  }
+
+  template <typename U>
+  ::mediapipe::Status ClipVectorSize(std::true_type, CalculatorContext* cc) {
+    auto output = absl::make_unique<std::vector<U>>();
+    const std::vector<U>& input_vector =
+        cc->Inputs().Index(0).Get<std::vector<U>>();
+    if (max_vec_size_ >= input_vector.size()) {
+      output->insert(output->end(), input_vector.begin(), input_vector.end());
+    } else {
+      for (int i = 0; i < max_vec_size_; ++i) {
+        output->push_back(input_vector[i]);
+      }
+    }
+    cc->Outputs().Index(0).Add(output.release(), cc->InputTimestamp());
+    return ::mediapipe::OkStatus();
+  }
+
+  template <typename U>
+  ::mediapipe::Status ClipVectorSize(std::false_type, CalculatorContext* cc) {
+    return ConsumeAndClipVectorSize<T>(std::is_move_constructible<U>(), cc);
+  }
+
+  template <typename U>
+  ::mediapipe::Status ConsumeAndClipVectorSize(std::true_type,
+                                               CalculatorContext* cc) {
+    auto output = absl::make_unique<std::vector<U>>();
+    ::mediapipe::StatusOr<std::unique_ptr<std::vector<U>>> input_status =
+        cc->Inputs().Index(0).Value().Consume<std::vector<U>>();
+
+    if (input_status.ok()) {
+      std::unique_ptr<std::vector<U>> input_vector =
+          std::move(input_status).ValueOrDie();
+      auto begin_it = input_vector->begin();
+      auto end_it = input_vector->end();
+      if (max_vec_size_ < input_vector->size()) {
+        end_it = input_vector->begin() + max_vec_size_;
+      }
+      output->insert(output->end(), std::make_move_iterator(begin_it),
+                     std::make_move_iterator(end_it));
+    } else {
+      return input_status.status();
+    }
+    cc->Outputs().Index(0).Add(output.release(), cc->InputTimestamp());
+    return ::mediapipe::OkStatus();
+  }
+
+  template <typename U>
+  ::mediapipe::Status ConsumeAndClipVectorSize(std::false_type,
+                                               CalculatorContext* cc) {
+    return ::mediapipe::InternalError(
+        "Cannot copy or move input vectors and clip their size.");
+  }
+
+ private:
+  int max_vec_size_ = 0;
+};
+
+}  // namespace mediapipe
+
+#endif  // MEDIAPIPE_CALCULATORS_CORE_CLIP_VECTOR_SIZE_CALCULATOR_H_
@@ -0,0 +1,28 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+syntax = "proto2";
+
+package mediapipe;
+
+import "mediapipe/framework/calculator.proto";
+
+message ClipVectorSizeCalculatorOptions {
+  extend CalculatorOptions {
+    optional ClipVectorSizeCalculatorOptions ext = 274674998;
+  }
+
+  // Maximum size of output vector.
+  optional int32 max_vec_size = 1 [default = 1];
+}
@@ -0,0 +1,206 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "mediapipe/calculators/core/clip_vector_size_calculator.h"
+
+#include <memory>
+#include <string>
+#include <vector>
+
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/calculator_runner.h"
+#include "mediapipe/framework/port/gmock.h"
+#include "mediapipe/framework/port/gtest.h"
+#include "mediapipe/framework/port/parse_text_proto.h"
+#include "mediapipe/framework/port/status_matchers.h"  // NOLINT
+
+namespace mediapipe {
+
+typedef ClipVectorSizeCalculator<int> TestClipIntVectorSizeCalculator;
+REGISTER_CALCULATOR(TestClipIntVectorSizeCalculator);
+
+void AddInputVector(const std::vector<int>& input, int64 timestamp,
+                    CalculatorRunner* runner) {
+  runner->MutableInputs()->Index(0).packets.push_back(
+      MakePacket<std::vector<int>>(input).At(Timestamp(timestamp)));
+}
+
+TEST(TestClipIntVectorSizeCalculatorTest, EmptyVectorInput) {
+  CalculatorGraphConfig::Node node_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig::Node>(R"(
+        calculator: "TestClipIntVectorSizeCalculator"
+        input_stream: "input_vector"
+        output_stream: "output_vector"
+        options {
+          [mediapipe.ClipVectorSizeCalculatorOptions.ext] { max_vec_size: 1 }
+        }
+      )");
+  CalculatorRunner runner(node_config);
+
+  std::vector<int> input = {};
+  AddInputVector(input, /*timestamp=*/1, &runner);
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<Packet>& outputs = runner.Outputs().Index(0).packets;
+  EXPECT_EQ(1, outputs.size());
+  EXPECT_EQ(Timestamp(1), outputs[0].Timestamp());
+  EXPECT_TRUE(outputs[0].Get<std::vector<int>>().empty());
+}
+
+TEST(TestClipIntVectorSizeCalculatorTest, OneTimestamp) {
+  CalculatorGraphConfig::Node node_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig::Node>(R"(
+        calculator: "TestClipIntVectorSizeCalculator"
+        input_stream: "input_vector"
+        output_stream: "output_vector"
+        options {
+          [mediapipe.ClipVectorSizeCalculatorOptions.ext] { max_vec_size: 2 }
+        }
+      )");
+  CalculatorRunner runner(node_config);
+
+  std::vector<int> input = {0, 1, 2, 3};
+  AddInputVector(input, /*timestamp=*/1, &runner);
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<Packet>& outputs = runner.Outputs().Index(0).packets;
+  EXPECT_EQ(1, outputs.size());
+  EXPECT_EQ(Timestamp(1), outputs[0].Timestamp());
+  const std::vector<int>& output = outputs[0].Get<std::vector<int>>();
+  EXPECT_EQ(2, output.size());
+  std::vector<int> expected_vector = {0, 1};
+  EXPECT_EQ(expected_vector, output);
+}
+
+TEST(TestClipIntVectorSizeCalculatorTest, TwoInputsAtTwoTimestamps) {
+  CalculatorGraphConfig::Node node_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig::Node>(R"(
+        calculator: "TestClipIntVectorSizeCalculator"
+        input_stream: "input_vector"
+        output_stream: "output_vector"
+        options {
+          [mediapipe.ClipVectorSizeCalculatorOptions.ext] { max_vec_size: 3 }
+        }
+      )");
+  CalculatorRunner runner(node_config);
+
+  {
+    std::vector<int> input = {0, 1, 2, 3};
+    AddInputVector(input, /*timestamp=*/1, &runner);
+  }
+  {
+    std::vector<int> input = {2, 3, 4, 5};
+    AddInputVector(input, /*timestamp=*/2, &runner);
+  }
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<Packet>& outputs = runner.Outputs().Index(0).packets;
+  EXPECT_EQ(2, outputs.size());
+  {
+    EXPECT_EQ(Timestamp(1), outputs[0].Timestamp());
+    const std::vector<int>& output = outputs[0].Get<std::vector<int>>();
+    EXPECT_EQ(3, output.size());
+    std::vector<int> expected_vector = {0, 1, 2};
+    EXPECT_EQ(expected_vector, output);
+  }
+  {
+    EXPECT_EQ(Timestamp(2), outputs[1].Timestamp());
+    const std::vector<int>& output = outputs[1].Get<std::vector<int>>();
+    EXPECT_EQ(3, output.size());
+    std::vector<int> expected_vector = {2, 3, 4};
+    EXPECT_EQ(expected_vector, output);
+  }
+}
+
+typedef ClipVectorSizeCalculator<std::unique_ptr<int>>
+    TestClipUniqueIntPtrVectorSizeCalculator;
+REGISTER_CALCULATOR(TestClipUniqueIntPtrVectorSizeCalculator);
+
+TEST(TestClipUniqueIntPtrVectorSizeCalculatorTest, ConsumeOneTimestamp) {
+  /* Note: We don't use CalculatorRunner for this test because it keeps copies
+   * of input packets, so packets sent to the graph don't have sole ownership.
+   * The test needs to send packets that own the data.
+   */
+  CalculatorGraphConfig graph_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig>(R"(
+        input_stream: "input_vector"
+        node {
+          calculator: "TestClipUniqueIntPtrVectorSizeCalculator"
+          input_stream: "input_vector"
+          output_stream: "output_vector"
+          options {
+            [mediapipe.ClipVectorSizeCalculatorOptions.ext] { max_vec_size: 3 }
+          }
+        }
+      )");
+
+  std::vector<Packet> outputs;
+  tool::AddVectorSink("output_vector", &graph_config, &outputs);
+
+  CalculatorGraph graph;
+  MP_EXPECT_OK(graph.Initialize(graph_config));
+  MP_EXPECT_OK(graph.StartRun({}));
+
+  // input1 : {0, 1, 2, 3, 4, 5}
+  auto input_vector = absl::make_unique<std::vector<std::unique_ptr<int>>>(6);
+  for (int i = 0; i < 6; ++i) {
+    input_vector->at(i) = absl::make_unique<int>(i);
+  }
+
+  MP_EXPECT_OK(graph.AddPacketToInputStream(
+      "input_vector", Adopt(input_vector.release()).At(Timestamp(1))));
+
+  MP_EXPECT_OK(graph.WaitUntilIdle());
+  MP_EXPECT_OK(graph.CloseAllPacketSources());
+  MP_EXPECT_OK(graph.WaitUntilDone());
+
+  EXPECT_EQ(1, outputs.size());
+  EXPECT_EQ(Timestamp(1), outputs[0].Timestamp());
+  const std::vector<std::unique_ptr<int>>& result =
+      outputs[0].Get<std::vector<std::unique_ptr<int>>>();
+  EXPECT_EQ(3, result.size());
+  for (int i = 0; i < 3; ++i) {
+    const std::unique_ptr<int>& v = result[i];
+    EXPECT_EQ(i, *v);
+  }
+}
+
+TEST(TestClipIntVectorSizeCalculatorTest, SidePacket) {
+  CalculatorGraphConfig::Node node_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig::Node>(R"(
+        calculator: "TestClipIntVectorSizeCalculator"
+        input_stream: "input_vector"
+        input_side_packet: "max_vec_size"
+        output_stream: "output_vector"
+        options {
+          [mediapipe.ClipVectorSizeCalculatorOptions.ext] { max_vec_size: 1 }
+        }
+      )");
+  CalculatorRunner runner(node_config);
+  // This should override the default of 1 set in the options.
+  runner.MutableSidePackets()->Index(0) = Adopt(new int(2));
+  std::vector<int> input = {0, 1, 2, 3};
+  AddInputVector(input, /*timestamp=*/1, &runner);
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<Packet>& outputs = runner.Outputs().Index(0).packets;
+  EXPECT_EQ(1, outputs.size());
+  EXPECT_EQ(Timestamp(1), outputs[0].Timestamp());
+  const std::vector<int>& output = outputs[0].Get<std::vector<int>>();
+  EXPECT_EQ(2, output.size());
+  std::vector<int> expected_vector = {0, 1};
+  EXPECT_EQ(expected_vector, output);
+}
+
+}  // namespace mediapipe
@@ -19,7 +19,7 @@
 #include "mediapipe/framework/formats/landmark.pb.h"
 #include "tensorflow/lite/interpreter.h"

-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
 #include "tensorflow/lite/delegates/gpu/gl/gl_buffer.h"
 #endif  //  !MEDIAPIPE_DISABLE_GPU

@@ -35,6 +35,16 @@ namespace mediapipe {
 typedef ConcatenateVectorCalculator<float> ConcatenateFloatVectorCalculator;
 REGISTER_CALCULATOR(ConcatenateFloatVectorCalculator);

+// Example config:
+// node {
+//   calculator: "ConcatenateInt32VectorCalculator"
+//   input_stream: "int32_vector_1"
+//   input_stream: "int32_vector_2"
+//   output_stream: "concatenated_int32_vector"
+// }
+typedef ConcatenateVectorCalculator<int32> ConcatenateInt32VectorCalculator;
+REGISTER_CALCULATOR(ConcatenateInt32VectorCalculator);
+
 // Example config:
 // node {
 //   calculator: "ConcatenateTfLiteTensorVectorCalculator"
@@ -50,7 +60,7 @@ typedef ConcatenateVectorCalculator<::mediapipe::NormalizedLandmark>
    ConcatenateLandmarkVectorCalculator;
 REGISTER_CALCULATOR(ConcatenateLandmarkVectorCalculator);

-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
 typedef ConcatenateVectorCalculator<::tflite::gpu::gl::GlBuffer>
    ConcatenateGlBufferVectorCalculator;
 REGISTER_CALCULATOR(ConcatenateGlBufferVectorCalculator);
@@ -0,0 +1,116 @@
+// Copyright 2020 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <string>
+
+#include "mediapipe/calculators/core/constant_side_packet_calculator.pb.h"
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/collection_item_id.h"
+#include "mediapipe/framework/port/canonical_errors.h"
+#include "mediapipe/framework/port/ret_check.h"
+#include "mediapipe/framework/port/status.h"
+
+namespace mediapipe {
+
+// Generates an output side packet or multiple output side packets according to
+// the specified options.
+//
+// Example configs:
+// node {
+//   calculator: "ConstantSidePacketCalculator"
+//   output_side_packet: "PACKET:packet"
+//   options: {
+//     [mediapipe.ConstantSidePacketCalculatorOptions.ext]: {
+//       packet { int_value: 2 }
+//     }
+//   }
+// }
+//
+// node {
+//   calculator: "ConstantSidePacketCalculator"
+//   output_side_packet: "PACKET:0:int_packet"
+//   output_side_packet: "PACKET:1:bool_packet"
+//   options: {
+//     [mediapipe.ConstantSidePacketCalculatorOptions.ext]: {
+//       packet { int_value: 2 }
+//       packet { bool_value: true }
+//     }
+//   }
+// }
+class ConstantSidePacketCalculator : public CalculatorBase {
+ public:
+  static ::mediapipe::Status GetContract(CalculatorContract* cc) {
+    const auto& options = cc->Options().GetExtension(
+        ::mediapipe::ConstantSidePacketCalculatorOptions::ext);
+    RET_CHECK_EQ(cc->OutputSidePackets().NumEntries(kPacketTag),
+                 options.packet_size())
+        << "Number of output side packets has to be same as number of packets "
+           "configured in options.";
+
+    int index = 0;
+    for (CollectionItemId id = cc->OutputSidePackets().BeginId(kPacketTag);
+         id != cc->OutputSidePackets().EndId(kPacketTag); ++id, ++index) {
+      const auto& packet_options = options.packet(index);
+      auto& packet = cc->OutputSidePackets().Get(id);
+      if (packet_options.has_int_value()) {
+        packet.Set<int>();
+      } else if (packet_options.has_float_value()) {
+        packet.Set<float>();
+      } else if (packet_options.has_bool_value()) {
+        packet.Set<bool>();
+      } else if (packet_options.has_string_value()) {
+        packet.Set<std::string>();
+      } else {
+        return ::mediapipe::InvalidArgumentError(
+            "None of supported values were specified in options.");
+      }
+    }
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Open(CalculatorContext* cc) override {
+    const auto& options = cc->Options().GetExtension(
+        ::mediapipe::ConstantSidePacketCalculatorOptions::ext);
+    int index = 0;
+    for (CollectionItemId id = cc->OutputSidePackets().BeginId(kPacketTag);
+         id != cc->OutputSidePackets().EndId(kPacketTag); ++id, ++index) {
+      auto& packet = cc->OutputSidePackets().Get(id);
+      const auto& packet_options = options.packet(index);
+      if (packet_options.has_int_value()) {
+        packet.Set(MakePacket<int>(packet_options.int_value()));
+      } else if (packet_options.has_float_value()) {
+        packet.Set(MakePacket<float>(packet_options.float_value()));
+      } else if (packet_options.has_bool_value()) {
+        packet.Set(MakePacket<bool>(packet_options.bool_value()));
+      } else if (packet_options.has_string_value()) {
+        packet.Set(MakePacket<std::string>(packet_options.string_value()));
+      } else {
+        return ::mediapipe::InvalidArgumentError(
+            "None of supported values were specified in options.");
+      }
+    }
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Process(CalculatorContext* cc) override {
+    return ::mediapipe::OkStatus();
+  }
+
+ private:
+  static constexpr const char* kPacketTag = "PACKET";
+};
+
+REGISTER_CALCULATOR(ConstantSidePacketCalculator);
+
+}  // namespace mediapipe
@@ -0,0 +1,36 @@
+// Copyright 2020 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+syntax = "proto2";
+
+package mediapipe;
+
+import "mediapipe/framework/calculator.proto";
+
+message ConstantSidePacketCalculatorOptions {
+  extend CalculatorOptions {
+    optional ConstantSidePacketCalculatorOptions ext = 291214597;
+  }
+
+  message ConstantSidePacket {
+    oneof value {
+      int32 int_value = 1;
+      float float_value = 2;
+      bool bool_value = 3;
+      string string_value = 4;
+    }
+  }
+
+  repeated ConstantSidePacket packet = 1;
+}
@@ -0,0 +1,196 @@
+// Copyright 2020 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <string>
+
+#include "absl/strings/string_view.h"
+#include "absl/strings/substitute.h"
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/port/gmock.h"
+#include "mediapipe/framework/port/gtest.h"
+#include "mediapipe/framework/port/parse_text_proto.h"
+#include "mediapipe/framework/port/status.h"
+#include "mediapipe/framework/port/status_matchers.h"
+
+namespace mediapipe {
+
+template <typename T>
+void DoTestSingleSidePacket(absl::string_view packet_spec,
+                            const T& expected_value) {
+  static constexpr absl::string_view graph_config_template = R"(
+        node {
+          calculator: "ConstantSidePacketCalculator"
+          output_side_packet: "PACKET:packet"
+          options: {
+            [mediapipe.ConstantSidePacketCalculatorOptions.ext]: {
+              packet $0
+            }
+          }
+        }
+      )";
+  CalculatorGraphConfig graph_config =
+      ::mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(
+          absl::Substitute(graph_config_template, packet_spec));
+  CalculatorGraph graph;
+  MP_ASSERT_OK(graph.Initialize(graph_config));
+  MP_ASSERT_OK(graph.StartRun({}));
+  MP_ASSERT_OK(graph.WaitUntilIdle());
+
+  MP_ASSERT_OK(graph.GetOutputSidePacket("packet"));
+  auto actual_value =
+      graph.GetOutputSidePacket("packet").ValueOrDie().template Get<T>();
+  EXPECT_EQ(actual_value, expected_value);
+}
+
+TEST(ConstantSidePacketCalculatorTest, EveryPossibleType) {
+  DoTestSingleSidePacket("{ int_value: 2 }", 2);
+  DoTestSingleSidePacket("{ float_value: 6.5f }", 6.5f);
+  DoTestSingleSidePacket("{ bool_value: true }", true);
+  DoTestSingleSidePacket<std::string>(R"({ string_value: "str" })", "str");
+}
+
+TEST(ConstantSidePacketCalculatorTest, MultiplePackets) {
+  CalculatorGraphConfig graph_config =
+      ::mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(R"(
+        node {
+          calculator: "ConstantSidePacketCalculator"
+          output_side_packet: "PACKET:0:int_packet"
+          output_side_packet: "PACKET:1:float_packet"
+          output_side_packet: "PACKET:2:bool_packet"
+          output_side_packet: "PACKET:3:string_packet"
+          output_side_packet: "PACKET:4:another_string_packet"
+          output_side_packet: "PACKET:5:another_int_packet"
+          options: {
+            [mediapipe.ConstantSidePacketCalculatorOptions.ext]: {
+              packet { int_value: 256 }
+              packet { float_value: 0.5f }
+              packet { bool_value: false }
+              packet { string_value: "string" }
+              packet { string_value: "another string" }
+              packet { int_value: 128 }
+            }
+          }
+        }
+      )");
+  CalculatorGraph graph;
+  MP_ASSERT_OK(graph.Initialize(graph_config));
+  MP_ASSERT_OK(graph.StartRun({}));
+  MP_ASSERT_OK(graph.WaitUntilIdle());
+
+  MP_ASSERT_OK(graph.GetOutputSidePacket("int_packet"));
+  EXPECT_EQ(graph.GetOutputSidePacket("int_packet").ValueOrDie().Get<int>(),
+            256);
+  MP_ASSERT_OK(graph.GetOutputSidePacket("float_packet"));
+  EXPECT_EQ(graph.GetOutputSidePacket("float_packet").ValueOrDie().Get<float>(),
+            0.5f);
+  MP_ASSERT_OK(graph.GetOutputSidePacket("bool_packet"));
+  EXPECT_FALSE(
+      graph.GetOutputSidePacket("bool_packet").ValueOrDie().Get<bool>());
+  MP_ASSERT_OK(graph.GetOutputSidePacket("string_packet"));
+  EXPECT_EQ(graph.GetOutputSidePacket("string_packet")
+                .ValueOrDie()
+                .Get<std::string>(),
+            "string");
+  MP_ASSERT_OK(graph.GetOutputSidePacket("another_string_packet"));
+  EXPECT_EQ(graph.GetOutputSidePacket("another_string_packet")
+                .ValueOrDie()
+                .Get<std::string>(),
+            "another string");
+  MP_ASSERT_OK(graph.GetOutputSidePacket("another_int_packet"));
+  EXPECT_EQ(
+      graph.GetOutputSidePacket("another_int_packet").ValueOrDie().Get<int>(),
+      128);
+}
+
+TEST(ConstantSidePacketCalculatorTest, ProcessingPacketsWithCorrectTagOnly) {
+  CalculatorGraphConfig graph_config =
+      ::mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(R"(
+        node {
+          calculator: "ConstantSidePacketCalculator"
+          output_side_packet: "PACKET:0:int_packet"
+          output_side_packet: "no_tag0"
+          output_side_packet: "PACKET:1:float_packet"
+          output_side_packet: "INCORRECT_TAG:0:name1"
+          output_side_packet: "PACKET:2:bool_packet"
+          output_side_packet: "PACKET:3:string_packet"
+          output_side_packet: "no_tag2"
+          output_side_packet: "INCORRECT_TAG:1:name2"
+          options: {
+            [mediapipe.ConstantSidePacketCalculatorOptions.ext]: {
+              packet { int_value: 256 }
+              packet { float_value: 0.5f }
+              packet { bool_value: false }
+              packet { string_value: "string" }
+            }
+          }
+        }
+      )");
+  CalculatorGraph graph;
+  MP_ASSERT_OK(graph.Initialize(graph_config));
+  MP_ASSERT_OK(graph.StartRun({}));
+  MP_ASSERT_OK(graph.WaitUntilIdle());
+
+  MP_ASSERT_OK(graph.GetOutputSidePacket("int_packet"));
+  EXPECT_EQ(graph.GetOutputSidePacket("int_packet").ValueOrDie().Get<int>(),
+            256);
+  MP_ASSERT_OK(graph.GetOutputSidePacket("float_packet"));
+  EXPECT_EQ(graph.GetOutputSidePacket("float_packet").ValueOrDie().Get<float>(),
+            0.5f);
+  MP_ASSERT_OK(graph.GetOutputSidePacket("bool_packet"));
+  EXPECT_FALSE(
+      graph.GetOutputSidePacket("bool_packet").ValueOrDie().Get<bool>());
+  MP_ASSERT_OK(graph.GetOutputSidePacket("string_packet"));
+  EXPECT_EQ(graph.GetOutputSidePacket("string_packet")
+                .ValueOrDie()
+                .Get<std::string>(),
+            "string");
+}
+
+TEST(ConstantSidePacketCalculatorTest, IncorrectConfig_MoreOptionsThanPackets) {
+  CalculatorGraphConfig graph_config =
+      ::mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(R"(
+        node {
+          calculator: "ConstantSidePacketCalculator"
+          output_side_packet: "PACKET:int_packet"
+          options: {
+            [mediapipe.ConstantSidePacketCalculatorOptions.ext]: {
+              packet { int_value: 256 }
+              packet { float_value: 0.5f }
+            }
+          }
+        }
+      )");
+  CalculatorGraph graph;
+  EXPECT_FALSE(graph.Initialize(graph_config).ok());
+}
+
+TEST(ConstantSidePacketCalculatorTest, IncorrectConfig_MorePacketsThanOptions) {
+  CalculatorGraphConfig graph_config =
+      ::mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(R"(
+        node {
+          calculator: "ConstantSidePacketCalculator"
+          output_side_packet: "PACKET:0:int_packet"
+          output_side_packet: "PACKET:1:float_packet"
+          options: {
+            [mediapipe.ConstantSidePacketCalculatorOptions.ext]: {
+              packet { int_value: 256 }
+            }
+          }
+        }
+      )");
+  CalculatorGraph graph;
+  EXPECT_FALSE(graph.Initialize(graph_config).ok());
+}
+
+}  // namespace mediapipe
@@ -0,0 +1,90 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <cfloat>
+
+#include "mediapipe/calculators/core/dequantize_byte_array_calculator.pb.h"
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/port/canonical_errors.h"
+#include "mediapipe/framework/port/status.h"
+
+// Dequantizes a byte array to a vector of floats.
+//
+// Example config:
+//   node {
+//     calculator: "DequantizeByteArrayCalculator"
+//     input_stream: "ENCODED:encoded"
+//     output_stream: "FLOAT_VECTOR:float_vector"
+//     options {
+//       [mediapipe.DequantizeByteArrayCalculatorOptions.ext]: {
+//         max_quantized_value: 2
+//         min_quantized_value: -2
+//       }
+//     }
+//   }
+namespace mediapipe {
+
+class DequantizeByteArrayCalculator : public CalculatorBase {
+ public:
+  static ::mediapipe::Status GetContract(CalculatorContract* cc) {
+    cc->Inputs().Tag("ENCODED").Set<std::string>();
+    cc->Outputs().Tag("FLOAT_VECTOR").Set<std::vector<float>>();
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Open(CalculatorContext* cc) final {
+    const auto options =
+        cc->Options<::mediapipe::DequantizeByteArrayCalculatorOptions>();
+    if (!options.has_max_quantized_value() ||
+        !options.has_min_quantized_value()) {
+      return ::mediapipe::InvalidArgumentError(
+          "Both max_quantized_value and min_quantized_value must be provided "
+          "in DequantizeByteArrayCalculatorOptions.");
+    }
+    float max_quantized_value = options.max_quantized_value();
+    float min_quantized_value = options.min_quantized_value();
+    if (max_quantized_value < min_quantized_value + FLT_EPSILON) {
+      return ::mediapipe::InvalidArgumentError(
+          "max_quantized_value must be greater than min_quantized_value.");
+    }
+    float range = max_quantized_value - min_quantized_value;
+    scalar_ = range / 255.0;
+    bias_ = (range / 512.0) + min_quantized_value;
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Process(CalculatorContext* cc) final {
+    const std::string& encoded =
+        cc->Inputs().Tag("ENCODED").Value().Get<std::string>();
+    std::vector<float> float_vector;
+    float_vector.reserve(encoded.length());
+    for (int i = 0; i < encoded.length(); ++i) {
+      float_vector.push_back(
+          static_cast<unsigned char>(encoded.at(i)) * scalar_ + bias_);
+    }
+    cc->Outputs()
+        .Tag("FLOAT_VECTOR")
+        .AddPacket(MakePacket<std::vector<float>>(float_vector)
+                       .At(cc->InputTimestamp()));
+    return ::mediapipe::OkStatus();
+  }
+
+ private:
+  float scalar_;
+  float bias_;
+};
+
+REGISTER_CALCULATOR(DequantizeByteArrayCalculator);
+
+}  // namespace mediapipe
@@ -0,0 +1,28 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+syntax = "proto2";
+
+package mediapipe;
+
+import "mediapipe/framework/calculator.proto";
+
+message DequantizeByteArrayCalculatorOptions {
+  extend CalculatorOptions {
+    optional DequantizeByteArrayCalculatorOptions ext = 272316343;
+  }
+
+  optional float max_quantized_value = 1;
+  optional float min_quantized_value = 2;
+}
@@ -0,0 +1,137 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <string>
+#include <vector>
+
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/calculator_runner.h"
+#include "mediapipe/framework/port/gmock.h"
+#include "mediapipe/framework/port/gtest.h"
+#include "mediapipe/framework/port/parse_text_proto.h"
+#include "mediapipe/framework/port/status.h"
+#include "mediapipe/framework/port/status_matchers.h"  // NOLINT
+
+namespace mediapipe {
+
+TEST(QuantizeFloatVectorCalculatorTest, WrongConfig) {
+  CalculatorGraphConfig::Node node_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig::Node>(R"(
+        calculator: "DequantizeByteArrayCalculator"
+        input_stream: "ENCODED:encoded"
+        output_stream: "FLOAT_VECTOR:float_vector"
+        options {
+          [mediapipe.DequantizeByteArrayCalculatorOptions.ext]: {
+            max_quantized_value: 2
+          }
+        }
+      )");
+  CalculatorRunner runner(node_config);
+  std::string empty_string;
+  runner.MutableInputs()->Tag("ENCODED").packets.push_back(
+      MakePacket<std::string>(empty_string).At(Timestamp(0)));
+  auto status = runner.Run();
+  EXPECT_FALSE(status.ok());
+  EXPECT_THAT(
+      status.message(),
+      testing::HasSubstr(
+          "Both max_quantized_value and min_quantized_value must be provided"));
+}
+
+TEST(QuantizeFloatVectorCalculatorTest, WrongConfig2) {
+  CalculatorGraphConfig::Node node_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig::Node>(R"(
+        calculator: "DequantizeByteArrayCalculator"
+        input_stream: "ENCODED:encoded"
+        output_stream: "FLOAT_VECTOR:float_vector"
+        options {
+          [mediapipe.DequantizeByteArrayCalculatorOptions.ext]: {
+            max_quantized_value: -2
+            min_quantized_value: 2
+          }
+        }
+      )");
+  CalculatorRunner runner(node_config);
+  std::string empty_string;
+  runner.MutableInputs()->Tag("ENCODED").packets.push_back(
+      MakePacket<std::string>(empty_string).At(Timestamp(0)));
+  auto status = runner.Run();
+  EXPECT_FALSE(status.ok());
+  EXPECT_THAT(
+      status.message(),
+      testing::HasSubstr(
+          "max_quantized_value must be greater than min_quantized_value"));
+}
+
+TEST(QuantizeFloatVectorCalculatorTest, WrongConfig3) {
+  CalculatorGraphConfig::Node node_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig::Node>(R"(
+        calculator: "DequantizeByteArrayCalculator"
+        input_stream: "ENCODED:encoded"
+        output_stream: "FLOAT_VECTOR:float_vector"
+        options {
+          [mediapipe.DequantizeByteArrayCalculatorOptions.ext]: {
+            max_quantized_value: 1
+            min_quantized_value: 1
+          }
+        }
+      )");
+  CalculatorRunner runner(node_config);
+  std::string empty_string;
+  runner.MutableInputs()->Tag("ENCODED").packets.push_back(
+      MakePacket<std::string>(empty_string).At(Timestamp(0)));
+  auto status = runner.Run();
+  EXPECT_FALSE(status.ok());
+  EXPECT_THAT(
+      status.message(),
+      testing::HasSubstr(
+          "max_quantized_value must be greater than min_quantized_value"));
+}
+
+TEST(DequantizeByteArrayCalculatorTest, TestDequantization) {
+  CalculatorGraphConfig::Node node_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig::Node>(R"(
+        calculator: "DequantizeByteArrayCalculator"
+        input_stream: "ENCODED:encoded"
+        output_stream: "FLOAT_VECTOR:float_vector"
+        options {
+          [mediapipe.DequantizeByteArrayCalculatorOptions.ext]: {
+            max_quantized_value: 2
+            min_quantized_value: -2
+          }
+        }
+      )");
+  CalculatorRunner runner(node_config);
+  unsigned char input[4] = {0x7F, 0xFF, 0x00, 0x01};
+  runner.MutableInputs()->Tag("ENCODED").packets.push_back(
+      MakePacket<std::string>(
+          std::string(reinterpret_cast<char const*>(input), 4))
+          .At(Timestamp(0)));
+  auto status = runner.Run();
+  MP_ASSERT_OK(runner.Run());
+  const std::vector<Packet>& outputs =
+      runner.Outputs().Tag("FLOAT_VECTOR").packets;
+  EXPECT_EQ(1, outputs.size());
+  const std::vector<float>& result = outputs[0].Get<std::vector<float>>();
+  ASSERT_FALSE(result.empty());
+  EXPECT_EQ(4, result.size());
+  EXPECT_NEAR(0, result[0], 0.01);
+  EXPECT_NEAR(2, result[1], 0.01);
+  EXPECT_NEAR(-2, result[2], 0.01);
+  EXPECT_NEAR(-1.976, result[3], 0.01);
+
+  EXPECT_EQ(Timestamp(0), outputs[0].Timestamp());
+}
+
+}  // namespace mediapipe
@@ -0,0 +1,49 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "mediapipe/calculators/core/end_loop_calculator.h"
+
+#include <vector>
+
+#include "mediapipe/framework/formats/classification.pb.h"
+#include "mediapipe/framework/formats/landmark.pb.h"
+#include "mediapipe/framework/formats/rect.pb.h"
+#include "mediapipe/util/render_data.pb.h"
+#include "tensorflow/lite/interpreter.h"
+
+namespace mediapipe {
+
+typedef EndLoopCalculator<std::vector<::mediapipe::NormalizedRect>>
+    EndLoopNormalizedRectCalculator;
+REGISTER_CALCULATOR(EndLoopNormalizedRectCalculator);
+
+typedef EndLoopCalculator<std::vector<::mediapipe::NormalizedLandmarkList>>
+    EndLoopNormalizedLandmarkListVectorCalculator;
+REGISTER_CALCULATOR(EndLoopNormalizedLandmarkListVectorCalculator);
+
+typedef EndLoopCalculator<std::vector<bool>> EndLoopBooleanCalculator;
+REGISTER_CALCULATOR(EndLoopBooleanCalculator);
+
+typedef EndLoopCalculator<std::vector<::mediapipe::RenderData>>
+    EndLoopRenderDataCalculator;
+REGISTER_CALCULATOR(EndLoopRenderDataCalculator);
+
+typedef EndLoopCalculator<std::vector<::mediapipe::ClassificationList>>
+    EndLoopClassificationListCalculator;
+REGISTER_CALCULATOR(EndLoopClassificationListCalculator);
+
+typedef EndLoopCalculator<std::vector<TfLiteTensor>> EndLoopTensorCalculator;
+REGISTER_CALCULATOR(EndLoopTensorCalculator);
+
+}  // namespace mediapipe
@@ -0,0 +1,106 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#ifndef MEDIAPIPE_CALCULATORS_CORE_END_LOOP_CALCULATOR_H_
+#define MEDIAPIPE_CALCULATORS_CORE_END_LOOP_CALCULATOR_H_
+
+#include "mediapipe/framework/calculator_context.h"
+#include "mediapipe/framework/calculator_contract.h"
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/collection_item_id.h"
+#include "mediapipe/framework/port/integral_types.h"
+#include "mediapipe/framework/port/ret_check.h"
+#include "mediapipe/framework/port/status.h"
+
+namespace mediapipe {
+
+// Calculator for completing the processing of loops on iterable collections
+// inside a MediaPipe graph. The EndLoopCalculator collects all input packets
+// from ITEM input_stream into a collection and upon receiving the flush signal
+// from the "BATCH_END" tagged input stream, it emits the aggregated results
+// at the original timestamp contained in the "BATCH_END" input stream.
+//
+// It is designed to be used like:
+//
+// node {
+//   calculator:    "BeginLoopWithIterableCalculator"
+//   input_stream:  "ITERABLE:input_iterable"      # IterableT @ext_ts
+//   output_stream: "ITEM:input_element"           # ItemT     @loop_internal_ts
+//   output_stream: "BATCH_END:ext_ts"             # Timestamp @loop_internal_ts
+// }
+//
+// node {
+//   calculator:    "ElementToBlaConverterSubgraph"
+//   input_stream:  "ITEM:input_to_loop_body"      # ItemT     @loop_internal_ts
+//   output_stream: "BLA:output_of_loop_body"      # ItemU     @loop_internal_ts
+// }
+//
+// node {
+//   calculator:    "EndLoopWithOutputCalculator"
+//   input_stream:  "ITEM:output_of_loop_body"     # ItemU     @loop_internal_ts
+//   input_stream:  "BATCH_END:ext_ts"             # Timestamp @loop_internal_ts
+//   output_stream: "OUTPUT:aggregated_result"     # IterableU @ext_ts
+// }
+template <typename IterableT>
+class EndLoopCalculator : public CalculatorBase {
+  using ItemT = typename IterableT::value_type;
+
+ public:
+  static ::mediapipe::Status GetContract(CalculatorContract* cc) {
+    RET_CHECK(cc->Inputs().HasTag("BATCH_END"))
+        << "Missing BATCH_END tagged input_stream.";
+    cc->Inputs().Tag("BATCH_END").Set<Timestamp>();
+
+    RET_CHECK(cc->Inputs().HasTag("ITEM"));
+    cc->Inputs().Tag("ITEM").Set<ItemT>();
+
+    RET_CHECK(cc->Outputs().HasTag("ITERABLE"));
+    cc->Outputs().Tag("ITERABLE").Set<IterableT>();
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Process(CalculatorContext* cc) override {
+    if (!cc->Inputs().Tag("ITEM").IsEmpty()) {
+      if (!input_stream_collection_) {
+        input_stream_collection_.reset(new IterableT);
+      }
+      input_stream_collection_->push_back(
+          cc->Inputs().Tag("ITEM").template Get<ItemT>());
+    }
+
+    if (!cc->Inputs().Tag("BATCH_END").Value().IsEmpty()) {  // flush signal
+      Timestamp loop_control_ts =
+          cc->Inputs().Tag("BATCH_END").template Get<Timestamp>();
+      if (input_stream_collection_) {
+        cc->Outputs()
+            .Tag("ITERABLE")
+            .Add(input_stream_collection_.release(), loop_control_ts);
+      } else {
+        // Since there is no collection, inform downstream calculators to not
+        // expect any packet by updating the timestamp bounds.
+        cc->Outputs()
+            .Tag("ITERABLE")
+            .SetNextTimestampBound(Timestamp(loop_control_ts.Value() + 1));
+      }
+    }
+    return ::mediapipe::OkStatus();
+  }
+
+ private:
+  std::unique_ptr<IterableT> input_stream_collection_;
+};
+
+}  // namespace mediapipe
+
+#endif  // MEDIAPIPE_CALCULATORS_CORE_END_LOOP_CALCULATOR_H_
@@ -12,25 +12,17 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.

-#include <cstdlib>
-#include <memory>
-#include <string>
+#include "mediapipe/calculators/core/packet_resampler_calculator.h"

-#include "absl/strings/str_cat.h"
-#include "mediapipe/calculators/core/packet_resampler_calculator.pb.h"
-#include "mediapipe/framework/calculator_framework.h"
-#include "mediapipe/framework/collection_item_id.h"
-#include "mediapipe/framework/deps/mathutil.h"
-#include "mediapipe/framework/deps/random_base.h"
-#include "mediapipe/framework/formats/video_stream_header.h"
-#include "mediapipe/framework/port/integral_types.h"
-#include "mediapipe/framework/port/logging.h"
-#include "mediapipe/framework/port/ret_check.h"
-#include "mediapipe/framework/port/status.h"
-#include "mediapipe/framework/port/status_macros.h"
-#include "mediapipe/framework/tool/options_util.h"
+#include <memory>

 namespace {
+// Reflect an integer against the lower and upper bound of an interval.
+int64 ReflectBetween(int64 ts, int64 ts_min, int64 ts_max) {
+  if (ts < ts_min) return 2 * ts_min - ts - 1;
+  if (ts >= ts_max) return 2 * ts_max - ts - 1;
+  return ts;
+}

 // Creates a secure random number generator for use in ProcessWithJitter.
 // If no secure random number generator can be constructed, the jitter
@@ -45,114 +37,7 @@ std::unique_ptr<RandomBase> CreateSecureRandom(const std::string& seed) {

 namespace mediapipe {

-// This calculator is used to normalize the frequency of the packets
-// out of a stream. Given a desired frame rate, packets are going to be
-// removed or added to achieve it.
-//
-// The jitter feature is disabled by default. To enable it, you need to
-// implement CreateSecureRandom(const std::string&).
-//
-// The data stream may be either specified as the only stream (by index)
-// or as the stream with tag "DATA".
-//
-// The input and output streams may be accompanied by a VIDEO_HEADER
-// stream.  This stream includes a VideoHeader at Timestamp::PreStream().
-// The input VideoHeader on the VIDEO_HEADER stream will always be updated
-// with the resampler frame rate no matter what the options value for
-// output_header is before being output on the output VIDEO_HEADER stream.
-// If the input VideoHeader is not available, then only the frame rate
-// value will be set in the output.
-//
-// Related:
-//   packet_downsampler_calculator.cc: skips packets regardless of timestamps.
-class PacketResamplerCalculator : public CalculatorBase {
- public:
-  static ::mediapipe::Status GetContract(CalculatorContract* cc);
-
-  ::mediapipe::Status Open(CalculatorContext* cc) override;
-  ::mediapipe::Status Close(CalculatorContext* cc) override;
-  ::mediapipe::Status Process(CalculatorContext* cc) override;
-
- private:
-  // Logic for Process() when jitter_ != 0.0.
-  ::mediapipe::Status ProcessWithJitter(CalculatorContext* cc);
-
-  // Logic for Process() when jitter_ == 0.0.
-  ::mediapipe::Status ProcessWithoutJitter(CalculatorContext* cc);
-
-  // Given the current count of periods that have passed, this returns
-  // the next valid timestamp of the middle point of the next period:
-  //    if count is 0, it returns the first_timestamp_.
-  //    if count is 1, it returns the first_timestamp_ + period (corresponding
-  //       to the first tick using exact fps)
-  // e.g. for frame_rate=30 and first_timestamp_=0:
-  //    0: 0
-  //    1: 33333
-  //    2: 66667
-  //    3: 100000
-  //
-  // Can only be used if jitter_ equals zero.
-  Timestamp PeriodIndexToTimestamp(int64 index) const;
-
-  // Given a Timestamp, finds the closest sync Timestamp based on
-  // first_timestamp_ and the desired fps.
-  //
-  // Can only be used if jitter_ equals zero.
-  int64 TimestampToPeriodIndex(Timestamp timestamp) const;
-
-  // Outputs a packet if it is in range (start_time_, end_time_).
-  void OutputWithinLimits(CalculatorContext* cc, const Packet& packet) const;
-
-  // The timestamp of the first packet received.
-  Timestamp first_timestamp_;
-
-  // Number of frames per second (desired output frequency).
-  double frame_rate_;
-
-  // Inverse of frame_rate_.
-  int64 frame_time_usec_;
-
-  // Number of periods that have passed (= #packets sent to the output).
-  //
-  // Can only be used if jitter_ equals zero.
-  int64 period_count_;
-
-  // The last packet that was received.
-  Packet last_packet_;
-
-  VideoHeader video_header_;
-  // The "DATA" input stream.
-  CollectionItemId input_data_id_;
-  // The "DATA" output stream.
-  CollectionItemId output_data_id_;
-
-  // Indicator whether to flush last packet even if its timestamp is greater
-  // than the final stream timestamp.  Set to false when jitter_ is non-zero.
-  bool flush_last_packet_;
-
-  // Jitter-related variables.
-  std::unique_ptr<RandomBase> random_;
-  double jitter_ = 0.0;
-  Timestamp next_output_timestamp_;
-
-  // If specified, output timestamps are aligned with base_timestamp.
-  // Otherwise, they are aligned with the first input timestamp.
-  Timestamp base_timestamp_;
-
-  // If specified, only outputs at/after start_time are included.
-  Timestamp start_time_;
-
-  // If specified, only outputs before end_time are included.
-  Timestamp end_time_;
-
-  // If set, the output timestamps nearest to start_time and end_time
-  // are included in the output, even if the nearest timestamp is not
-  // between start_time and end_time.
-  bool round_limits_;
-};
-
 REGISTER_CALCULATOR(PacketResamplerCalculator);
-
 namespace {
 // Returns a TimestampDiff (assuming microseconds) corresponding to the
 // given time in seconds.
@@ -203,6 +88,7 @@ TimestampDiff TimestampDiffFromSeconds(double seconds) {

  flush_last_packet_ = resampler_options.flush_last_packet();
  jitter_ = resampler_options.jitter();
+  jitter_with_reflection_ = resampler_options.jitter_with_reflection();

  input_data_id_ = cc->Inputs().GetId("DATA", 0);
  if (!input_data_id_.IsValid()) {
@@ -233,6 +119,9 @@ TimestampDiff TimestampDiffFromSeconds(double seconds) {
      << Timestamp::kTimestampUnitsPerSecond;

  frame_time_usec_ = static_cast<int64>(1000000.0 / frame_rate_);
+  jitter_usec_ = static_cast<int64>(1000000.0 * jitter_ / frame_rate_);
+  RET_CHECK_LE(jitter_usec_, frame_time_usec_);
+
  video_header_.frame_rate = frame_rate_;

  if (resampler_options.output_header() !=
@@ -272,7 +161,10 @@ TimestampDiff TimestampDiffFromSeconds(double seconds) {
          "SecureRandom is not available.  With \"jitter\" specified, "
          "PacketResamplerCalculator processing cannot proceed.");
    }
+    packet_reservoir_random_ = CreateSecureRandom(seed);
  }
+  packet_reservoir_ =
+      std::make_unique<PacketReservoir>(packet_reservoir_random_.get());
  return ::mediapipe::OkStatus();
 }

@@ -287,6 +179,14 @@ TimestampDiff TimestampDiffFromSeconds(double seconds) {
    }
  }
  if (jitter_ != 0.0 && random_ != nullptr) {
+    // Packet reservior is used to make sure there's an output for every period,
+    // e.g. partial period at the end of the stream.
+    if (packet_reservoir_->IsEnabled() &&
+        (first_timestamp_ == Timestamp::Unset() ||
+         (cc->InputTimestamp() - next_output_timestamp_min_).Value() >= 0)) {
+      auto curr_packet = cc->Inputs().Get(input_data_id_).Value();
+      packet_reservoir_->AddSample(curr_packet);
+    }
    MP_RETURN_IF_ERROR(ProcessWithJitter(cc));
  } else {
    MP_RETURN_IF_ERROR(ProcessWithoutJitter(cc));
@@ -295,6 +195,40 @@ TimestampDiff TimestampDiffFromSeconds(double seconds) {
  return ::mediapipe::OkStatus();
 }

+void PacketResamplerCalculator::InitializeNextOutputTimestampWithJitter() {
+  next_output_timestamp_min_ = first_timestamp_;
+  if (jitter_with_reflection_) {
+    next_output_timestamp_ =
+        first_timestamp_ + random_->UnbiasedUniform64(frame_time_usec_);
+    return;
+  }
+  next_output_timestamp_ =
+      first_timestamp_ + frame_time_usec_ * random_->RandFloat();
+}
+
+void PacketResamplerCalculator::UpdateNextOutputTimestampWithJitter() {
+  packet_reservoir_->Clear();
+  if (jitter_with_reflection_) {
+    next_output_timestamp_min_ += frame_time_usec_;
+    Timestamp next_output_timestamp_max_ =
+        next_output_timestamp_min_ + frame_time_usec_;
+
+    next_output_timestamp_ += frame_time_usec_ +
+                              random_->UnbiasedUniform64(2 * jitter_usec_ + 1) -
+                              jitter_usec_;
+    next_output_timestamp_ = Timestamp(ReflectBetween(
+        next_output_timestamp_.Value(), next_output_timestamp_min_.Value(),
+        next_output_timestamp_max_.Value()));
+    CHECK_GE(next_output_timestamp_, next_output_timestamp_min_);
+    CHECK_LT(next_output_timestamp_, next_output_timestamp_max_);
+    return;
+  }
+  packet_reservoir_->Disable();
+  next_output_timestamp_ +=
+      frame_time_usec_ *
+      ((1.0 - jitter_) + 2.0 * jitter_ * random_->RandFloat());
+}
+
 ::mediapipe::Status PacketResamplerCalculator::ProcessWithJitter(
    CalculatorContext* cc) {
  RET_CHECK_GT(cc->InputTimestamp(), Timestamp::PreStream());
@@ -302,29 +236,37 @@ TimestampDiff TimestampDiffFromSeconds(double seconds) {

  if (first_timestamp_ == Timestamp::Unset()) {
    first_timestamp_ = cc->InputTimestamp();
-    next_output_timestamp_ =
-        first_timestamp_ + frame_time_usec_ * random_->RandFloat();
+    InitializeNextOutputTimestampWithJitter();
+    if (first_timestamp_ == next_output_timestamp_) {
+      OutputWithinLimits(
+          cc,
+          cc->Inputs().Get(input_data_id_).Value().At(next_output_timestamp_));
+      UpdateNextOutputTimestampWithJitter();
+    }
    return ::mediapipe::OkStatus();
  }

-  LOG_IF(WARNING, frame_time_usec_ <
-                      (cc->InputTimestamp() - last_packet_.Timestamp()).Value())
-      << "Adding jitter is meaningless when upsampling.";
+  if (frame_time_usec_ <
+      (cc->InputTimestamp() - last_packet_.Timestamp()).Value()) {
+    LOG_FIRST_N(WARNING, 2)
+        << "Adding jitter is not very useful when upsampling.";
+  }

-  const int64 curr_diff =
-      (next_output_timestamp_ - cc->InputTimestamp()).Value();
-  const int64 last_diff =
-      (next_output_timestamp_ - last_packet_.Timestamp()).Value();
-  if (curr_diff * last_diff > 0) {
-    return ::mediapipe::OkStatus();
+  while (true) {
+    const int64 last_diff =
+        (next_output_timestamp_ - last_packet_.Timestamp()).Value();
+    RET_CHECK_GT(last_diff, 0);
+    const int64 curr_diff =
+        (next_output_timestamp_ - cc->InputTimestamp()).Value();
+    if (curr_diff > 0) {
+      break;
+    }
+    OutputWithinLimits(cc, (std::abs(curr_diff) > last_diff
+                                ? last_packet_
+                                : cc->Inputs().Get(input_data_id_).Value())
+                               .At(next_output_timestamp_));
+    UpdateNextOutputTimestampWithJitter();
  }
-  OutputWithinLimits(cc, (std::abs(curr_diff) > std::abs(last_diff)
-                              ? last_packet_
-                              : cc->Inputs().Get(input_data_id_).Value())
-                             .At(next_output_timestamp_));
-  next_output_timestamp_ +=
-      frame_time_usec_ *
-      ((1.0 - jitter_) + 2.0 * jitter_ * random_->RandFloat());
  return ::mediapipe::OkStatus();
 }

@@ -405,6 +347,9 @@ TimestampDiff TimestampDiffFromSeconds(double seconds) {
    OutputWithinLimits(cc,
                       last_packet_.At(PeriodIndexToTimestamp(period_count_)));
  }
+  if (!packet_reservoir_->IsEmpty()) {
+    OutputWithinLimits(cc, packet_reservoir_->GetSample());
+  }
  return ::mediapipe::OkStatus();
 }

@@ -0,0 +1,205 @@
+#ifndef MEDIAPIPE_CALCULATORS_CORE_PACKET_RESAMPLER_CALCULATOR_H_
+#define MEDIAPIPE_CALCULATORS_CORE_PACKET_RESAMPLER_CALCULATOR_H_
+
+#include <cstdlib>
+#include <memory>
+#include <string>
+
+#include "absl/strings/str_cat.h"
+#include "mediapipe/calculators/core/packet_resampler_calculator.pb.h"
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/collection_item_id.h"
+#include "mediapipe/framework/deps/mathutil.h"
+#include "mediapipe/framework/deps/random_base.h"
+#include "mediapipe/framework/formats/video_stream_header.h"
+#include "mediapipe/framework/port/integral_types.h"
+#include "mediapipe/framework/port/logging.h"
+#include "mediapipe/framework/port/ret_check.h"
+#include "mediapipe/framework/port/status.h"
+#include "mediapipe/framework/port/status_macros.h"
+#include "mediapipe/framework/tool/options_util.h"
+
+namespace mediapipe {
+
+class PacketReservoir {
+ public:
+  PacketReservoir(RandomBase* rng) : rng_(rng) {}
+  // Replace candidate with current packet with 1/count_ probability.
+  void AddSample(Packet sample) {
+    if (rng_->UnbiasedUniform(++count_) == 0) {
+      reservoir_ = sample;
+    }
+  }
+  bool IsEnabled() { return rng_ && enabled_; }
+  void Disable() {
+    if (enabled_) enabled_ = false;
+  }
+  void Clear() { count_ = 0; }
+  bool IsEmpty() { return count_ == 0; }
+  Packet GetSample() { return reservoir_; }
+
+ private:
+  RandomBase* rng_;
+  bool enabled_ = true;
+  int32 count_ = 0;
+  Packet reservoir_;
+};
+
+// This calculator is used to normalize the frequency of the packets
+// out of a stream. Given a desired frame rate, packets are going to be
+// removed or added to achieve it.
+//
+// If jitter_ is specified:
+//   - The first packet is chosen randomly (uniform distribution) among frames
+//     that correspond to timestamps [0, 1/frame_rate).  Let the chosen packet
+//     correspond to timestamp t.
+//   - The next packet is chosen randomly (uniform distribution) among frames
+//     that correspond to [t+(1-jitter)/frame_rate, t+(1+jitter)/frame_rate].
+//     - if jitter_with_reflection_ is true, the timestamp will be reflected
+//       against the boundaries of [t_0 + (k-1)/frame_rate, t_0 + k/frame_rate)
+//       so that its marginal distribution is uniform within this interval.
+//       In the formula, t_0 is the timestamp of the first sampled
+//       packet, and the k is the packet index.
+//       See paper (https://arxiv.org/abs/2002.01147) for details.
+//   - t is updated and the process is repeated.
+//   - Note that seed is specified as input side packet for reproducibility of
+//     the resampling.  For Cloud ML Video Intelligence API, the hash of the
+//     input video should serve this purpose.  For YouTube, either video ID or
+//     content hex ID of the input video should do.
+//
+// If jitter_ is not specified:
+//   - The first packet defines the first_timestamp of the output stream,
+//     so it is always emitted.
+//   - If more packets are emitted, they will have timestamp equal to
+//     round(first_timestamp + k * period) , where k is a positive
+//     integer and the period is defined by the frame rate.
+//     Example: first_timestamp=0, fps=30, then the output stream
+//              will have timestamps: 0, 33333, 66667, 100000, etc...
+//   - The packets selected for the output stream are the ones closer
+//     to the exact middle point (33333.33, 66666.67 in our previous
+//     example). In case of ties, later packets are chosen.
+//   - 'Empty' periods happen when there are no packets for a long time
+//     (greater than a period). In this case, we send a copy of the last
+//     packet received before the empty period.
+// The jitter feature is disabled by default. To enable it, you need to
+// implement CreateSecureRandom(const std::string&).
+//
+// The data stream may be either specified as the only stream (by index)
+// or as the stream with tag "DATA".
+//
+// The input and output streams may be accompanied by a VIDEO_HEADER
+// stream.  This stream includes a VideoHeader at Timestamp::PreStream().
+// The input VideoHeader on the VIDEO_HEADER stream will always be updated
+// with the resampler frame rate no matter what the options value for
+// output_header is before being output on the output VIDEO_HEADER stream.
+// If the input VideoHeader is not available, then only the frame rate
+// value will be set in the output.
+//
+// Related:
+//   packet_downsampler_calculator.cc: skips packets regardless of timestamps.
+class PacketResamplerCalculator : public CalculatorBase {
+ public:
+  static ::mediapipe::Status GetContract(CalculatorContract* cc);
+
+  ::mediapipe::Status Open(CalculatorContext* cc) override;
+  ::mediapipe::Status Close(CalculatorContext* cc) override;
+  ::mediapipe::Status Process(CalculatorContext* cc) override;
+
+ private:
+  // Calculates the first sampled timestamp that incorporates a jittering
+  // offset.
+  void InitializeNextOutputTimestampWithJitter();
+  // Calculates the next sampled timestamp that incorporates a jittering offset.
+  void UpdateNextOutputTimestampWithJitter();
+
+  // Logic for Process() when jitter_ != 0.0.
+  ::mediapipe::Status ProcessWithJitter(CalculatorContext* cc);
+
+  // Logic for Process() when jitter_ == 0.0.
+  ::mediapipe::Status ProcessWithoutJitter(CalculatorContext* cc);
+
+  // Given the current count of periods that have passed, this returns
+  // the next valid timestamp of the middle point of the next period:
+  //    if count is 0, it returns the first_timestamp_.
+  //    if count is 1, it returns the first_timestamp_ + period (corresponding
+  //       to the first tick using exact fps)
+  // e.g. for frame_rate=30 and first_timestamp_=0:
+  //    0: 0
+  //    1: 33333
+  //    2: 66667
+  //    3: 100000
+  //
+  // Can only be used if jitter_ equals zero.
+  Timestamp PeriodIndexToTimestamp(int64 index) const;
+
+  // Given a Timestamp, finds the closest sync Timestamp based on
+  // first_timestamp_ and the desired fps.
+  //
+  // Can only be used if jitter_ equals zero.
+  int64 TimestampToPeriodIndex(Timestamp timestamp) const;
+
+  // Outputs a packet if it is in range (start_time_, end_time_).
+  void OutputWithinLimits(CalculatorContext* cc, const Packet& packet) const;
+
+  // The timestamp of the first packet received.
+  Timestamp first_timestamp_;
+
+  // Number of frames per second (desired output frequency).
+  double frame_rate_;
+
+  // Inverse of frame_rate_.
+  int64 frame_time_usec_;
+
+  // Number of periods that have passed (= #packets sent to the output).
+  //
+  // Can only be used if jitter_ equals zero.
+  int64 period_count_;
+
+  // The last packet that was received.
+  Packet last_packet_;
+
+  VideoHeader video_header_;
+  // The "DATA" input stream.
+  CollectionItemId input_data_id_;
+  // The "DATA" output stream.
+  CollectionItemId output_data_id_;
+
+  // Indicator whether to flush last packet even if its timestamp is greater
+  // than the final stream timestamp.  Set to false when jitter_ is non-zero.
+  bool flush_last_packet_;
+
+  // Jitter-related variables.
+  std::unique_ptr<RandomBase> random_;
+  double jitter_ = 0.0;
+  bool jitter_with_reflection_;
+  int64 jitter_usec_;
+  Timestamp next_output_timestamp_;
+  // If jittering_with_reflection_ is true, next_output_timestamp_ will be
+  // kept within the interval
+  // [next_output_timestamp_min_, next_output_timestamp_min_ + frame_time_usec_)
+  Timestamp next_output_timestamp_min_;
+
+  // If specified, output timestamps are aligned with base_timestamp.
+  // Otherwise, they are aligned with the first input timestamp.
+  Timestamp base_timestamp_;
+
+  // If specified, only outputs at/after start_time are included.
+  Timestamp start_time_;
+
+  // If specified, only outputs before end_time are included.
+  Timestamp end_time_;
+
+  // If set, the output timestamps nearest to start_time and end_time
+  // are included in the output, even if the nearest timestamp is not
+  // between start_time and end_time.W
+  bool round_limits_;
+
+  // packet reservior used for sampling random packet out of partial
+  // period when jitter is enabled
+  std::unique_ptr<PacketReservoir> packet_reservoir_;
+  // random number generator used in packet_reservior_.
+  std::unique_ptr<RandomBase> packet_reservoir_random_;
+};
+
+}  // namespace mediapipe
+#endif  // MEDIAPIPE_CALCULATORS_CORE_PACKET_RESAMPLER_CALCULATOR_H_
@@ -66,6 +66,7 @@ message PacketResamplerCalculatorOptions {
  // pseudo-random number generator does its job and the number of frames is
  // sufficiently large, the average frame rate will be close to this value.
  optional double jitter = 4;
+  optional bool jitter_with_reflection = 9 [default = false];

  // If specified, output timestamps are aligned with base_timestamp.
  // Otherwise, they are aligned with the first input timestamp.
@@ -12,6 +12,8 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.

+#include "mediapipe/calculators/core/packet_resampler_calculator.h"
+
 #include <memory>
 #include <string>
 #include <vector>
@@ -29,7 +31,6 @@
 namespace mediapipe {

 namespace {
-
 // A simple version of CalculatorRunner with built-in convenience
 // methods for setting inputs from a vector and checking outputs
 // against expected outputs (both timestamps and contents).
@@ -0,0 +1,304 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//
+// Declaration of PacketThinnerCalculator.
+
+#include <cmath>  // for ceil
+#include <memory>
+
+#include "mediapipe/calculators/core/packet_thinner_calculator.pb.h"
+#include "mediapipe/framework/calculator_context.h"
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/formats/video_stream_header.h"
+#include "mediapipe/framework/port/integral_types.h"
+#include "mediapipe/framework/port/logging.h"
+#include "mediapipe/framework/port/status.h"
+
+namespace mediapipe {
+
+namespace {
+const double kTimebaseUs = 1000000;  // Microseconds.
+const char* const kPeriodTag = "PERIOD";
+}  // namespace
+
+// This calculator is used to thin an input stream of Packets.
+// An example application would be to sample decoded frames of video
+// at a coarser temporal resolution. Unless otherwise stated, all
+// timestamps are in units of microseconds.
+//
+// Thinning can be accomplished in one of two ways:
+// 1) asynchronous thinning (known below as async):
+//    Algorithm does not rely on a master clock and is parameterized only
+//    by a single option -- the period.  Once a packet is emitted, the
+//    thinner will discard subsequent packets for the duration of the period
+//    [Analogous to a refractory period during which packet emission is
+//    suppressed.]
+//    Packets arriving before start_time are discarded, as are packets
+//    arriving at or after end_time.
+// 2) synchronous thinning (known below as sync):
+//    There are two variants of this algorithm, both parameterized by a
+//    start_time and a period.  As in (1), packets arriving before start_time
+//    or at/after end_time are discarded.  Otherwise, at most one packet is
+//    emitted during a period, centered at timestamps generated by the
+//    expression:
+//      start_time + i * period  [where i is a non-negative integer]
+//    During each period, the packet closest to the generated timestamp is
+//    emitted (latest in the case of ties).  In the first variant
+//    (sync_output_timestamps = true), the emitted packet is output at the
+//    generated timestamp.  In the second variant, the packet is output at
+//    its original timestamp.  Both variants emit exactly the same packets,
+//    but at different timestamps.
+//
+// Thinning period can be provided in the calculator options or via a
+// side packet with the tag "PERIOD".
+//
+// Example config:
+// node {
+//   calculator: "PacketThinnerCalculator"
+//   input_stream: "signal"
+//   output_stream: "output"
+//   options {
+//     [mediapipe.PacketThinnerCalculatorOptions.ext] {
+//       thinner_type: SYNC
+//       period: 10
+//       sync_output_timestamps: true
+//       update_frame_rate: false
+//     }
+//   }
+// }
+class PacketThinnerCalculator : public CalculatorBase {
+ public:
+  PacketThinnerCalculator() {}
+  ~PacketThinnerCalculator() override {}
+
+  static ::mediapipe::Status GetContract(CalculatorContract* cc) {
+    cc->Inputs().Index(0).SetAny();
+    cc->Outputs().Index(0).SetSameAs(&cc->Inputs().Index(0));
+    if (cc->InputSidePackets().HasTag(kPeriodTag)) {
+      cc->InputSidePackets().Tag(kPeriodTag).Set<int64>();
+    }
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Open(CalculatorContext* cc) override;
+  ::mediapipe::Status Close(CalculatorContext* cc) override;
+  ::mediapipe::Status Process(CalculatorContext* cc) override {
+    if (cc->InputTimestamp() < start_time_) {
+      return ::mediapipe::OkStatus();  // Drop packets before start_time_.
+    } else if (cc->InputTimestamp() >= end_time_) {
+      if (!cc->Outputs().Index(0).IsClosed()) {
+        cc->Outputs()
+            .Index(0)
+            .Close();  // No more Packets will be output after end_time_.
+      }
+      return ::mediapipe::OkStatus();
+    } else {
+      return thinner_type_ == PacketThinnerCalculatorOptions::ASYNC
+                 ? AsyncThinnerProcess(cc)
+                 : SyncThinnerProcess(cc);
+    }
+  }
+
+ private:
+  // Implementation of ASYNC and SYNC versions of thinner algorithm.
+  ::mediapipe::Status AsyncThinnerProcess(CalculatorContext* cc);
+  ::mediapipe::Status SyncThinnerProcess(CalculatorContext* cc);
+
+  // Cached option.
+  PacketThinnerCalculatorOptions::ThinnerType thinner_type_;
+
+  // Given a Timestamp, finds the closest sync Timestamp
+  // based on start_time_ and period_.  This can be earlier or
+  // later than given Timestamp, but is guaranteed to be within
+  // half a period_.
+  Timestamp NearestSyncTimestamp(Timestamp now) const;
+
+  // Cached option used by both async and sync thinners.
+  TimestampDiff period_;  // Interval during which only one packet is emitted.
+  Timestamp start_time_;  // Cached option - default Timestamp::Min()
+  Timestamp end_time_;    // Cached option - default Timestamp::Max()
+
+  // Only used by async thinner:
+  Timestamp next_valid_timestamp_;  // Suppress packets until this timestamp.
+
+  // Only used by sync thinner:
+  Packet saved_packet_;          // Best packet not yet emitted.
+  bool sync_output_timestamps_;  // Cached option.
+};
+REGISTER_CALCULATOR(PacketThinnerCalculator);
+
+namespace {
+TimestampDiff abs(TimestampDiff t) { return t < 0 ? -t : t; }
+}  // namespace
+
+::mediapipe::Status PacketThinnerCalculator::Open(CalculatorContext* cc) {
+  auto& options = cc->Options<PacketThinnerCalculatorOptions>();
+
+  thinner_type_ = options.thinner_type();
+  // This check enables us to assume only two thinner types exist in Process()
+  CHECK(thinner_type_ == PacketThinnerCalculatorOptions::ASYNC ||
+        thinner_type_ == PacketThinnerCalculatorOptions::SYNC)
+      << "Unsupported thinner type.";
+
+  if (thinner_type_ == PacketThinnerCalculatorOptions::ASYNC) {
+    // ASYNC thinner outputs packets with the same timestamp as their input so
+    // its safe to SetOffset(0). SYNC thinner manipulates timestamps of its
+    // output so we don't do this for that case.
+    cc->SetOffset(0);
+  }
+
+  if (cc->InputSidePackets().HasTag(kPeriodTag)) {
+    period_ =
+        TimestampDiff(cc->InputSidePackets().Tag(kPeriodTag).Get<int64>());
+  } else {
+    period_ = TimestampDiff(options.period());
+  }
+  CHECK_LT(TimestampDiff(0), period_) << "Specified period must be positive.";
+
+  if (options.has_start_time()) {
+    start_time_ = Timestamp(options.start_time());
+  } else if (thinner_type_ == PacketThinnerCalculatorOptions::ASYNC) {
+    start_time_ = Timestamp::Min();
+  } else {
+    start_time_ = Timestamp(0);
+  }
+
+  end_time_ =
+      options.has_end_time() ? Timestamp(options.end_time()) : Timestamp::Max();
+  CHECK_LT(start_time_, end_time_)
+      << "Invalid PacketThinner: start_time must be earlier than end_time";
+
+  sync_output_timestamps_ = options.sync_output_timestamps();
+
+  next_valid_timestamp_ = start_time_;
+  // Drop packets until this time.
+  cc->Outputs().Index(0).SetNextTimestampBound(start_time_);
+
+  if (!cc->Inputs().Index(0).Header().IsEmpty()) {
+    if (options.update_frame_rate()) {
+      const VideoHeader& video_header =
+          cc->Inputs().Index(0).Header().Get<VideoHeader>();
+      double new_frame_rate;
+      if (thinner_type_ == PacketThinnerCalculatorOptions::ASYNC) {
+        new_frame_rate =
+            video_header.frame_rate /
+            ceil(video_header.frame_rate * options.period() / kTimebaseUs);
+      } else {
+        const double sampling_rate = kTimebaseUs / options.period();
+        new_frame_rate = video_header.frame_rate < sampling_rate
+                             ? video_header.frame_rate
+                             : sampling_rate;
+      }
+      std::unique_ptr<VideoHeader> header(new VideoHeader);
+      header->format = video_header.format;
+      header->width = video_header.width;
+      header->height = video_header.height;
+      header->frame_rate = new_frame_rate;
+      cc->Outputs().Index(0).SetHeader(Adopt(header.release()));
+    } else {
+      cc->Outputs().Index(0).SetHeader(cc->Inputs().Index(0).Header());
+    }
+  }
+
+  return ::mediapipe::OkStatus();
+}
+
+::mediapipe::Status PacketThinnerCalculator::Close(CalculatorContext* cc) {
+  // Emit any saved packets before quitting.
+  if (!saved_packet_.IsEmpty()) {
+    // Only sync thinner should have saved packets.
+    CHECK_EQ(PacketThinnerCalculatorOptions::SYNC, thinner_type_);
+    if (sync_output_timestamps_) {
+      cc->Outputs().Index(0).AddPacket(
+          saved_packet_.At(NearestSyncTimestamp(saved_packet_.Timestamp())));
+    } else {
+      cc->Outputs().Index(0).AddPacket(saved_packet_);
+    }
+  }
+  return ::mediapipe::OkStatus();
+}
+
+::mediapipe::Status PacketThinnerCalculator::AsyncThinnerProcess(
+    CalculatorContext* cc) {
+  if (cc->InputTimestamp() >= next_valid_timestamp_) {
+    cc->Outputs().Index(0).AddPacket(
+        cc->Inputs().Index(0).Value());  // Emit current packet.
+    next_valid_timestamp_ = cc->InputTimestamp() + period_;
+    // Guaranteed not to emit packets seen during refractory period.
+    cc->Outputs().Index(0).SetNextTimestampBound(next_valid_timestamp_);
+  }
+  return ::mediapipe::OkStatus();
+}
+
+::mediapipe::Status PacketThinnerCalculator::SyncThinnerProcess(
+    CalculatorContext* cc) {
+  if (saved_packet_.IsEmpty()) {
+    // If no packet has been saved, store the current packet.
+    saved_packet_ = cc->Inputs().Index(0).Value();
+    cc->Outputs().Index(0).SetNextTimestampBound(
+        sync_output_timestamps_ ? NearestSyncTimestamp(cc->InputTimestamp())
+                                : cc->InputTimestamp());
+  } else {
+    // Saved packet exists -- update or emit.
+    const Timestamp saved = saved_packet_.Timestamp();
+    const Timestamp saved_sync = NearestSyncTimestamp(saved);
+    const Timestamp now = cc->InputTimestamp();
+    const Timestamp now_sync = NearestSyncTimestamp(now);
+    CHECK_LE(saved_sync, now_sync);
+    if (saved_sync == now_sync) {
+      // Saved Packet is in same interval as current packet.
+      // Replace saved packet with current if it is at least as
+      // central as the saved packet wrt temporal interval.
+      // [We break ties in favor of fresher packets]
+      if (abs(now - now_sync) <= abs(saved - saved_sync)) {
+        saved_packet_ = cc->Inputs().Index(0).Value();
+      }
+    } else {
+      // Saved packet is the best packet from earlier interval: emit!
+      if (sync_output_timestamps_) {
+        cc->Outputs().Index(0).AddPacket(saved_packet_.At(saved_sync));
+        cc->Outputs().Index(0).SetNextTimestampBound(now_sync);
+      } else {
+        cc->Outputs().Index(0).AddPacket(saved_packet_);
+        cc->Outputs().Index(0).SetNextTimestampBound(now);
+      }
+      // Current packet is the first one we've seen from new interval -- save!
+      saved_packet_ = cc->Inputs().Index(0).Value();
+    }
+  }
+  return ::mediapipe::OkStatus();
+}
+
+Timestamp PacketThinnerCalculator::NearestSyncTimestamp(Timestamp now) const {
+  CHECK_NE(start_time_, Timestamp::Unset())
+      << "Method only valid for sync thinner calculator.";
+
+  // Computation is done using int64 arithmetic.  No easy way to avoid
+  // since Timestamps don't support div and multiply.
+  const int64 now64 = now.Value();
+  const int64 start64 = start_time_.Value();
+  const int64 period64 = period_.Value();
+  CHECK_LE(0, period64);
+
+  // Round now64 to its closest interval (units of period64).
+  int64 sync64 =
+      (now64 - start64 + period64 / 2) / period64 * period64 + start64;
+  CHECK_LE(abs(now64 - sync64), period64 / 2)
+      << "start64: " << start64 << "; now64: " << now64
+      << "; sync64: " << sync64;
+
+  return Timestamp(sync64);
+}
+
+}  // namespace mediapipe
@@ -0,0 +1,66 @@
+// Copyright 2018 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+syntax = "proto2";
+
+package mediapipe;
+
+import "mediapipe/framework/calculator.proto";
+
+message PacketThinnerCalculatorOptions {
+  extend CalculatorOptions {
+    optional PacketThinnerCalculatorOptions ext = 288533508;
+  }
+
+  enum ThinnerType {
+    ASYNC = 1;  // Asynchronous thinner, described below [default].
+    SYNC = 2;   // Synchronous thinner, also described below.
+  }
+  optional ThinnerType thinner_type = 1 [default = ASYNC];
+
+  // The period (in microsecond) specifies the temporal interval during which
+  // only a single packet is emitted in the output stream.  Has subtly different
+  // semantics depending on the thinner type, as follows.
+  //
+  // Async thinner: this option is a refractory period -- once a packet is
+  // emitted, we guarantee that no packets will be emitted for period ticks.
+  //
+  // Sync thinner: the period specifies a temporal interval during which
+  // only one packet is emitted.  The emitted packet is guaranteed to be
+  // the one closest to the center of the temporal interval (no guarantee on
+  // how ties are broken).  More specifically,
+  //   intervals are centered at start_time + i * period
+  //   (for non-negative integers i).
+  // Thus, each interval extends period/2 ticks before and after its center.
+  // Additionally, in the sync thinner any packets earlier than start_time
+  // are discarded and the thinner calls Close() once timestamp equals or
+  // exceeds end_time.
+  optional int64 period = 2 [default = 1];
+
+  // Packets before start_time and at/after end_time are discarded.
+  // Additionally, for a sync thinner, start time specifies the center of
+  // time invervals as described above and therefore should be set explicitly.
+  optional int64 start_time = 3;  // If not specified, set to 0 for SYNC type,
+                                  // and set to Timestamp::Min() for ASYNC type.
+  optional int64 end_time = 4;    // Set to Timestamp::Max() if not specified.
+
+  // Whether the timestamps of packets emitted by sync thinner should
+  // correspond to the center of their corresponding temporal interval.
+  // If false, packets emitted using original timestamp (as in async thinner).
+  optional bool sync_output_timestamps = 5 [default = true];
+
+  // If true, update the frame rate in the header, if it's available, to an
+  // estimated frame rate due to the sampling.
+  optional bool update_frame_rate = 6 [default = false];
+}
@@ -0,0 +1,357 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <memory>
+#include <string>
+#include <vector>
+
+#include "absl/strings/str_cat.h"
+#include "mediapipe/calculators/core/packet_thinner_calculator.pb.h"
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/calculator_runner.h"
+#include "mediapipe/framework/formats/video_stream_header.h"
+#include "mediapipe/framework/port/gmock.h"
+#include "mediapipe/framework/port/gtest.h"
+#include "mediapipe/framework/port/integral_types.h"
+#include "mediapipe/framework/port/status_matchers.h"
+
+namespace mediapipe {
+namespace {
+
+// A simple version of CalculatorRunner with built-in convenience methods for
+// setting inputs from a vector and checking outputs against a vector of
+// expected outputs.
+class SimpleRunner : public CalculatorRunner {
+ public:
+  explicit SimpleRunner(const CalculatorOptions& options)
+      : CalculatorRunner("PacketThinnerCalculator", options) {
+    SetNumInputs(1);
+    SetNumOutputs(1);
+    SetNumInputSidePackets(0);
+  }
+
+  explicit SimpleRunner(const CalculatorGraphConfig::Node& node)
+      : CalculatorRunner(node) {}
+
+  void SetInput(const std::vector<int>& timestamp_list) {
+    MutableInputs()->Index(0).packets.clear();
+    for (const int ts : timestamp_list) {
+      MutableInputs()->Index(0).packets.push_back(
+          MakePacket<std::string>(absl::StrCat("Frame #", ts))
+              .At(Timestamp(ts)));
+    }
+  }
+
+  void SetFrameRate(const double frame_rate) {
+    auto video_header = absl::make_unique<VideoHeader>();
+    video_header->frame_rate = frame_rate;
+    MutableInputs()->Index(0).header = Adopt(video_header.release());
+  }
+
+  std::vector<int64> GetOutputTimestamps() const {
+    std::vector<int64> timestamps;
+    for (const Packet& packet : Outputs().Index(0).packets) {
+      timestamps.emplace_back(packet.Timestamp().Value());
+    }
+    return timestamps;
+  }
+
+  double GetFrameRate() const {
+    CHECK(!Outputs().Index(0).header.IsEmpty());
+    return Outputs().Index(0).header.Get<VideoHeader>().frame_rate;
+  }
+};
+
+// Check that thinner respects start_time and end_time options.
+// We only test with one thinner because the logic for start & end time
+// handling is shared across both types of thinner in Process().
+TEST(PacketThinnerCalculatorTest, StartAndEndTimeTest) {
+  CalculatorOptions options;
+  auto* extension =
+      options.MutableExtension(PacketThinnerCalculatorOptions::ext);
+  extension->set_thinner_type(PacketThinnerCalculatorOptions::ASYNC);
+  extension->set_period(5);
+  extension->set_start_time(4);
+  extension->set_end_time(12);
+  SimpleRunner runner(options);
+  runner.SetInput({2, 3, 5, 7, 11, 13, 17, 19, 23, 29});
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<int64> expected_timestamps = {5, 11};
+  EXPECT_EQ(expected_timestamps, runner.GetOutputTimestamps());
+}
+
+TEST(PacketThinnerCalculatorTest, AsyncUniformStreamThinningTest) {
+  CalculatorOptions options;
+  auto* extension =
+      options.MutableExtension(PacketThinnerCalculatorOptions::ext);
+  extension->set_thinner_type(PacketThinnerCalculatorOptions::ASYNC);
+  extension->set_period(5);
+  SimpleRunner runner(options);
+  runner.SetInput({2, 4, 6, 8, 10, 12, 14});
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<int64> expected_timestamps = {2, 8, 14};
+  EXPECT_EQ(expected_timestamps, runner.GetOutputTimestamps());
+}
+
+TEST(PacketThinnerCalculatorTest, ASyncUniformStreamThinningTestBySidePacket) {
+  // Note: sync runner but outputting *original* timestamps.
+  CalculatorGraphConfig::Node node;
+  node.set_calculator("PacketThinnerCalculator");
+  node.add_input_side_packet("PERIOD:period");
+  node.add_input_stream("input_stream");
+  node.add_output_stream("output_stream");
+  auto* extension = node.mutable_options()->MutableExtension(
+      PacketThinnerCalculatorOptions::ext);
+  extension->set_thinner_type(PacketThinnerCalculatorOptions::ASYNC);
+  extension->set_start_time(0);
+  extension->set_sync_output_timestamps(false);
+
+  SimpleRunner runner(node);
+  runner.SetInput({2, 4, 6, 8, 10, 12, 14});
+  runner.MutableSidePackets()->Tag("PERIOD") = MakePacket<int64>(5);
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<int64> expected_timestamps = {2, 8, 14};
+  EXPECT_EQ(expected_timestamps, runner.GetOutputTimestamps());
+}
+
+TEST(PacketThinnerCalculatorTest, SyncUniformStreamThinningTest1) {
+  // Note: sync runner but outputting *original* timestamps.
+  CalculatorOptions options;
+  auto* extension =
+      options.MutableExtension(PacketThinnerCalculatorOptions::ext);
+  extension->set_thinner_type(PacketThinnerCalculatorOptions::SYNC);
+  extension->set_start_time(0);
+  extension->set_period(5);
+  extension->set_sync_output_timestamps(false);
+  SimpleRunner runner(options);
+  runner.SetInput({2, 4, 6, 8, 10, 12, 14});
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<int64> expected_timestamps = {2, 6, 10, 14};
+  EXPECT_EQ(expected_timestamps, runner.GetOutputTimestamps());
+}
+
+TEST(PacketThinnerCalculatorTest, SyncUniformStreamThinningTestBySidePacket1) {
+  // Note: sync runner but outputting *original* timestamps.
+  CalculatorGraphConfig::Node node;
+  node.set_calculator("PacketThinnerCalculator");
+  node.add_input_side_packet("PERIOD:period");
+  node.add_input_stream("input_stream");
+  node.add_output_stream("output_stream");
+  auto* extension = node.mutable_options()->MutableExtension(
+      PacketThinnerCalculatorOptions::ext);
+  extension->set_thinner_type(PacketThinnerCalculatorOptions::SYNC);
+  extension->set_start_time(0);
+  extension->set_sync_output_timestamps(false);
+
+  SimpleRunner runner(node);
+  runner.SetInput({2, 4, 6, 8, 10, 12, 14});
+  runner.MutableSidePackets()->Tag("PERIOD") = MakePacket<int64>(5);
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<int64> expected_timestamps = {2, 6, 10, 14};
+  EXPECT_EQ(expected_timestamps, runner.GetOutputTimestamps());
+}
+
+TEST(PacketThinnerCalculatorTest, SyncUniformStreamThinningTest2) {
+  // Same test but now with synced timestamps.
+  CalculatorOptions options;
+  auto* extension =
+      options.MutableExtension(PacketThinnerCalculatorOptions::ext);
+  extension->set_thinner_type(PacketThinnerCalculatorOptions::SYNC);
+  extension->set_start_time(0);
+  extension->set_period(5);
+  extension->set_sync_output_timestamps(true);
+  SimpleRunner runner(options);
+  runner.SetInput({2, 4, 6, 8, 10, 12, 14});
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<int64> expected_timestamps = {0, 5, 10, 15};
+  EXPECT_EQ(expected_timestamps, runner.GetOutputTimestamps());
+}
+
+// Test: Given a stream with timestamps corresponding to first ten prime numbers
+// and period of 5, confirm whether timestamps of thinner stream matches
+// expectations.
+TEST(PacketThinnerCalculatorTest, PrimeStreamThinningTest1) {
+  // ASYNC thinner.
+  CalculatorOptions options;
+  auto* extension =
+      options.MutableExtension(PacketThinnerCalculatorOptions::ext);
+  extension->set_thinner_type(PacketThinnerCalculatorOptions::ASYNC);
+  extension->set_period(5);
+  SimpleRunner runner(options);
+  runner.SetInput({2, 3, 5, 7, 11, 13, 17, 19, 23, 29});
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<int64> expected_timestamps = {2, 7, 13, 19, 29};
+  EXPECT_EQ(expected_timestamps, runner.GetOutputTimestamps());
+}
+
+TEST(PacketThinnerCalculatorTest, PrimeStreamThinningTest2) {
+  // SYNC with original timestamps.
+  CalculatorOptions options;
+  auto* extension =
+      options.MutableExtension(PacketThinnerCalculatorOptions::ext);
+  extension->set_thinner_type(PacketThinnerCalculatorOptions::SYNC);
+  extension->set_start_time(0);
+  extension->set_period(5);
+  extension->set_sync_output_timestamps(false);
+  SimpleRunner runner(options);
+  runner.SetInput({2, 3, 5, 7, 11, 13, 17, 19, 23, 29});
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<int64> expected_timestamps = {2, 5, 11, 17, 19, 23, 29};
+  EXPECT_EQ(expected_timestamps, runner.GetOutputTimestamps());
+}
+
+// Confirm that Calculator correctly handles boundary cases.
+TEST(PacketThinnerCalculatorTest, BoundaryTimestampTest1) {
+  // Odd period, negative start_time
+  CalculatorOptions options;
+  auto* extension =
+      options.MutableExtension(PacketThinnerCalculatorOptions::ext);
+  extension->set_thinner_type(PacketThinnerCalculatorOptions::SYNC);
+  extension->set_start_time(-10);
+  extension->set_period(5);
+  extension->set_sync_output_timestamps(true);
+  SimpleRunner runner(options);
+  // Two timestamps falling on either side of a period boundary.
+  runner.SetInput({2, 3});
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<int64> expected_timestamps = {0, 5};
+  EXPECT_EQ(expected_timestamps, runner.GetOutputTimestamps());
+}
+
+TEST(PacketThinnerCalculatorTest, BoundaryTimestampTest2) {
+  // Even period, negative start_time, negative packet timestamps.
+  CalculatorOptions options;
+  auto* extension =
+      options.MutableExtension(PacketThinnerCalculatorOptions::ext);
+  extension->set_thinner_type(PacketThinnerCalculatorOptions::SYNC);
+  extension->set_start_time(-144);
+  extension->set_period(6);
+  extension->set_sync_output_timestamps(true);
+  SimpleRunner runner(options);
+  // Two timestamps falling on either side of a period boundary.
+  runner.SetInput({-4, -3, 8, 9});
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<int64> expected_timestamps = {-6, 0, 6, 12};
+  EXPECT_EQ(expected_timestamps, runner.GetOutputTimestamps());
+}
+
+TEST(PacketThinnerCalculatorTest, FrameRateTest1) {
+  CalculatorOptions options;
+  auto* extension =
+      options.MutableExtension(PacketThinnerCalculatorOptions::ext);
+  extension->set_thinner_type(PacketThinnerCalculatorOptions::ASYNC);
+  extension->set_period(5);
+  extension->set_update_frame_rate(true);
+  SimpleRunner runner(options);
+  runner.SetInput({2, 4, 6, 8, 10, 12, 14});
+  runner.SetFrameRate(1000000.0 / 2);
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<int64> expected_timestamps = {2, 8, 14};
+  EXPECT_EQ(expected_timestamps, runner.GetOutputTimestamps());
+  // The true sampling period is 6.
+  EXPECT_DOUBLE_EQ(1000000.0 / 6, runner.GetFrameRate());
+}
+
+TEST(PacketThinnerCalculatorTest, FrameRateTest2) {
+  CalculatorOptions options;
+  auto* extension =
+      options.MutableExtension(PacketThinnerCalculatorOptions::ext);
+  extension->set_thinner_type(PacketThinnerCalculatorOptions::ASYNC);
+  extension->set_period(5);
+  extension->set_update_frame_rate(true);
+  SimpleRunner runner(options);
+  runner.SetInput({8, 16, 24, 32, 40, 48, 56});
+  runner.SetFrameRate(1000000.0 / 8);
+  MP_ASSERT_OK(runner.Run());
+  const std::vector<int64> expected_timestamps = {8, 16, 24, 32, 40, 48, 56};
+  EXPECT_EQ(expected_timestamps, runner.GetOutputTimestamps());
+  // The true sampling period is still 8.
+  EXPECT_DOUBLE_EQ(1000000.0 / 8, runner.GetFrameRate());
+}
+
+TEST(PacketThinnerCalculatorTest, FrameRateTest3) {
+  // Note: sync runner but outputting *original* timestamps.
+  CalculatorOptions options;
+  auto* extension =
+      options.MutableExtension(PacketThinnerCalculatorOptions::ext);
+  extension->set_thinner_type(PacketThinnerCalculatorOptions::SYNC);
+  extension->set_start_time(0);
+  extension->set_period(5);
+  extension->set_sync_output_timestamps(false);
+  extension->set_update_frame_rate(true);
+  SimpleRunner runner(options);
+  runner.SetInput({2, 4, 6, 8, 10, 12, 14});
+  runner.SetFrameRate(1000000.0 / 2);
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<int64> expected_timestamps = {2, 6, 10, 14};
+  EXPECT_EQ(expected_timestamps, runner.GetOutputTimestamps());
+  // The true (long-run) sampling period is 5.
+  EXPECT_DOUBLE_EQ(1000000.0 / 5, runner.GetFrameRate());
+}
+
+TEST(PacketThinnerCalculatorTest, FrameRateTest4) {
+  // Same test but now with synced timestamps.
+  CalculatorOptions options;
+  auto* extension =
+      options.MutableExtension(PacketThinnerCalculatorOptions::ext);
+  extension->set_thinner_type(PacketThinnerCalculatorOptions::SYNC);
+  extension->set_start_time(0);
+  extension->set_period(5);
+  extension->set_sync_output_timestamps(true);
+  extension->set_update_frame_rate(true);
+  SimpleRunner runner(options);
+  runner.SetInput({2, 4, 6, 8, 10, 12, 14});
+  runner.SetFrameRate(1000000.0 / 2);
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<int64> expected_timestamps = {0, 5, 10, 15};
+  EXPECT_EQ(expected_timestamps, runner.GetOutputTimestamps());
+  // The true (long-run) sampling period is 5.
+  EXPECT_DOUBLE_EQ(1000000.0 / 5, runner.GetFrameRate());
+}
+
+TEST(PacketThinnerCalculatorTest, FrameRateTest5) {
+  CalculatorOptions options;
+  auto* extension =
+      options.MutableExtension(PacketThinnerCalculatorOptions::ext);
+  extension->set_thinner_type(PacketThinnerCalculatorOptions::SYNC);
+  extension->set_start_time(0);
+  extension->set_period(5);
+  extension->set_sync_output_timestamps(true);
+  extension->set_update_frame_rate(true);
+  SimpleRunner runner(options);
+  runner.SetInput({8, 16, 24, 32, 40, 48, 56});
+  runner.SetFrameRate(1000000.0 / 8);
+  MP_ASSERT_OK(runner.Run());
+
+  const std::vector<int64> expected_timestamps = {10, 15, 25, 30, 40, 50, 55};
+  EXPECT_EQ(expected_timestamps, runner.GetOutputTimestamps());
+  // The true (long-run) sampling period is 8.
+  EXPECT_DOUBLE_EQ(1000000.0 / 8, runner.GetFrameRate());
+}
+
+}  // namespace
+}  // namespace mediapipe
@@ -17,6 +17,7 @@
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/port/ret_check.h"
 #include "mediapipe/framework/port/status.h"
+#include "mediapipe/framework/timestamp.h"

 namespace mediapipe {

@@ -24,13 +25,17 @@ namespace mediapipe {
 // together with some previous output.
 //
 // For the first packet that arrives on the MAIN input, the timestamp bound is
-// advanced on the output. Downstream calculators will see this as an empty
+// advanced on the PREV_LOOP. Downstream calculators will see this as an empty
 // packet. This way they are not kept waiting for the previous output, which
 // for the first iteration does not exist.
 //
-// Thereafter, each packet received on MAIN is matched with a packet received
-// on LOOP; the LOOP packet's timestamp is changed to that of the MAIN packet,
-// and it is output on PREV_LOOP.
+// Thereafter,
+// - Each non-empty MAIN packet results in:
+//   a) a PREV_LOOP packet with contents of the LOOP packet received at the
+//      timestamp of the previous non-empty MAIN packet
+//   b) or in a PREV_LOOP timestamp bound update if the LOOP packet was empty.
+// - Each empty MAIN packet indicating timestamp bound update results in a
+//   PREV_LOOP timestamp bound update.
 //
 // Example config:
 // node {
@@ -55,63 +60,115 @@ class PreviousLoopbackCalculator : public CalculatorBase {
    // TODO: an optional PREV_TIMESTAMP output could be added to
    // carry the original timestamp of the packet on PREV_LOOP.
    cc->SetInputStreamHandler("ImmediateInputStreamHandler");
+    // Process() function is invoked in response to MAIN/LOOP stream timestamp
+    // bound updates.
+    cc->SetProcessTimestampBounds(true);
    return ::mediapipe::OkStatus();
  }

  ::mediapipe::Status Open(CalculatorContext* cc) final {
    main_id_ = cc->Inputs().GetId("MAIN", 0);
    loop_id_ = cc->Inputs().GetId("LOOP", 0);
-    loop_out_id_ = cc->Outputs().GetId("PREV_LOOP", 0);
+    prev_loop_id_ = cc->Outputs().GetId("PREV_LOOP", 0);
    cc->Outputs()
-        .Get(loop_out_id_)
+        .Get(prev_loop_id_)
        .SetHeader(cc->Inputs().Get(loop_id_).Header());
-
-    // Use an empty packet for the first round, since there is no previous
-    // output.
-    loopback_packets_.push_back({});
-
    return ::mediapipe::OkStatus();
  }

  ::mediapipe::Status Process(CalculatorContext* cc) final {
-    Packet& main_packet = cc->Inputs().Get(main_id_).Value();
-    if (!main_packet.IsEmpty()) {
-      main_ts_.push_back(main_packet.Timestamp());
-    }
-    Packet& loopback_packet = cc->Inputs().Get(loop_id_).Value();
-    if (!loopback_packet.IsEmpty()) {
-      loopback_packets_.push_back(loopback_packet);
-      while (!main_ts_.empty() &&
-             main_ts_.front() <= loopback_packets_.front().Timestamp()) {
-        main_ts_.pop_front();
-      }
-    }
+    // Non-empty packets and empty packets indicating timestamp bound updates
+    // are guaranteed to have timestamps greater than timestamps of previous
+    // packets within the same stream. Calculator tracks and operates on such
+    // packets.

-    while (!main_ts_.empty() && !loopback_packets_.empty()) {
-      Timestamp main_timestamp = main_ts_.front();
-      main_ts_.pop_front();
-      Packet previous_loopback = loopback_packets_.front().At(main_timestamp);
-      loopback_packets_.pop_front();
-
-      if (previous_loopback.IsEmpty()) {
-        // TODO: SetCompleteTimestampBound would be more useful.
-        cc->Outputs()
-            .Get(loop_out_id_)
-            .SetNextTimestampBound(main_timestamp + 1);
+    const Packet& main_packet = cc->Inputs().Get(main_id_).Value();
+    if (prev_main_ts_ < main_packet.Timestamp()) {
+      Timestamp loop_timestamp;
+      if (!main_packet.IsEmpty()) {
+        loop_timestamp = prev_non_empty_main_ts_;
+        prev_non_empty_main_ts_ = main_packet.Timestamp();
      } else {
-        cc->Outputs().Get(loop_out_id_).AddPacket(std::move(previous_loopback));
+        // Calculator advances PREV_LOOP timestamp bound in response to empty
+        // MAIN packet, hence not caring about corresponding loop packet.
+        loop_timestamp = Timestamp::Unset();
      }
+      main_packet_specs_.push_back({.timestamp = main_packet.Timestamp(),
+                                    .loop_timestamp = loop_timestamp});
+      prev_main_ts_ = main_packet.Timestamp();
+    }
+
+    const Packet& loop_packet = cc->Inputs().Get(loop_id_).Value();
+    if (prev_loop_ts_ < loop_packet.Timestamp()) {
+      loop_packets_.push_back(loop_packet);
+      prev_loop_ts_ = loop_packet.Timestamp();
+    }
+
+    auto& prev_loop = cc->Outputs().Get(prev_loop_id_);
+    while (!main_packet_specs_.empty() && !loop_packets_.empty()) {
+      // The earliest MAIN packet.
+      const MainPacketSpec& main_spec = main_packet_specs_.front();
+      // The earliest LOOP packet.
+      const Packet& loop_candidate = loop_packets_.front();
+      // Match LOOP and MAIN packets.
+      if (main_spec.loop_timestamp < loop_candidate.Timestamp()) {
+        // No LOOP packet can match the MAIN packet under review.
+        prev_loop.SetNextTimestampBound(main_spec.timestamp + 1);
+        main_packet_specs_.pop_front();
+      } else if (main_spec.loop_timestamp > loop_candidate.Timestamp()) {
+        // No MAIN packet can match the LOOP packet under review.
+        loop_packets_.pop_front();
+      } else {
+        // Exact match found.
+        if (loop_candidate.IsEmpty()) {
+          // However, LOOP packet is empty.
+          prev_loop.SetNextTimestampBound(main_spec.timestamp + 1);
+        } else {
+          prev_loop.AddPacket(loop_candidate.At(main_spec.timestamp));
+        }
+        loop_packets_.pop_front();
+        main_packet_specs_.pop_front();
+      }
+    }
+
+    if (main_packet_specs_.empty() && cc->Inputs().Get(main_id_).IsDone()) {
+      prev_loop.Close();
    }
    return ::mediapipe::OkStatus();
  }

 private:
+  struct MainPacketSpec {
+    Timestamp timestamp;
+    // Expected timestamp of the packet from LOOP stream that corresponds to the
+    // packet from MAIN stream descirbed by this spec.
+    Timestamp loop_timestamp;
+  };
+
  CollectionItemId main_id_;
  CollectionItemId loop_id_;
-  CollectionItemId loop_out_id_;
+  CollectionItemId prev_loop_id_;

-  std::deque<Timestamp> main_ts_;
-  std::deque<Packet> loopback_packets_;
+  // Contains specs for MAIN packets which only can be:
+  // - non-empty packets
+  // - empty packets indicating timestamp bound updates
+  //
+  // Sorted according to packet timestamps.
+  std::deque<MainPacketSpec> main_packet_specs_;
+  Timestamp prev_main_ts_ = Timestamp::Unstarted();
+  Timestamp prev_non_empty_main_ts_ = Timestamp::Unstarted();
+
+  // Contains LOOP packets which only can be:
+  // - the very first empty packet
+  // - non empty packets
+  // - empty packets indicating timestamp bound updates
+  //
+  // Sorted according to packet timestamps.
+  std::deque<Packet> loop_packets_;
+  // Using "Timestamp::Unset" instead of "Timestamp::Unstarted" in order to
+  // allow addition of the very first empty packet (which doesn't indicate
+  // timestamp bound change necessarily).
+  Timestamp prev_loop_ts_ = Timestamp::Unset();
 };
 REGISTER_CALCULATOR(PreviousLoopbackCalculator);

@@ -13,6 +13,7 @@
 // limitations under the License.

 #include <algorithm>
+#include <functional>
 #include <memory>
 #include <string>
 #include <vector>
@@ -25,12 +26,17 @@
 #include "mediapipe/framework/port/gtest.h"
 #include "mediapipe/framework/port/integral_types.h"
 #include "mediapipe/framework/port/parse_text_proto.h"
+#include "mediapipe/framework/port/status.h"
 #include "mediapipe/framework/port/status_matchers.h"
 #include "mediapipe/framework/timestamp.h"
 #include "mediapipe/framework/tool/sink.h"

 namespace mediapipe {

+using ::testing::ElementsAre;
+using ::testing::Eq;
+using ::testing::Pair;
+using ::testing::Value;
 namespace {

 // Returns the timestamp values for a vector of Packets.
@@ -43,6 +49,23 @@ std::vector<int64> TimestampValues(const std::vector<Packet>& packets) {
  return result;
 }

+MATCHER(EmptyPacket, negation ? "isn't empty" : "is empty") {
+  if (arg.IsEmpty()) {
+    return true;
+  }
+  return false;
+}
+
+MATCHER_P(IntPacket, value, "") {
+  return Value(arg.template Get<int>(), Eq(value));
+}
+
+MATCHER_P2(PairPacket, timestamp, pair, "") {
+  Timestamp actual_timestamp = arg.Timestamp();
+  const auto& actual_pair = arg.template Get<std::pair<Packet, Packet>>();
+  return Value(actual_timestamp, Eq(timestamp)) && Value(actual_pair, pair);
+}
+
 TEST(PreviousLoopbackCalculator, CorrectTimestamps) {
  std::vector<Packet> in_prev;
  CalculatorGraphConfig graph_config_ =
@@ -81,27 +104,662 @@ TEST(PreviousLoopbackCalculator, CorrectTimestamps) {
    MP_EXPECT_OK(graph_.AddPacketToInputStream(
        input_name, MakePacket<int>(n).At(Timestamp(n))));
  };
-  auto pair_values = [](const Packet& packet) {
-    auto pair = packet.Get<std::pair<Packet, Packet>>();
-    int first = pair.first.IsEmpty() ? -1 : pair.first.Get<int>();
-    int second = pair.second.IsEmpty() ? -1 : pair.second.Get<int>();
-    return std::make_pair(first, second);
+
+  send_packet("in", 1);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(TimestampValues(in_prev), ElementsAre(1));
+  EXPECT_THAT(in_prev.back(),
+              PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())));
+
+  send_packet("in", 2);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(TimestampValues(in_prev), ElementsAre(1, 2));
+  EXPECT_THAT(in_prev.back(),
+              PairPacket(Timestamp(2), Pair(IntPacket(2), IntPacket(1))));
+
+  send_packet("in", 5);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(TimestampValues(in_prev), ElementsAre(1, 2, 5));
+  EXPECT_THAT(in_prev.back(),
+              PairPacket(Timestamp(5), Pair(IntPacket(5), IntPacket(2))));
+
+  send_packet("in", 15);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(TimestampValues(in_prev), ElementsAre(1, 2, 5, 15));
+  EXPECT_THAT(in_prev.back(),
+              PairPacket(Timestamp(15), Pair(IntPacket(15), IntPacket(5))));
+
+  MP_EXPECT_OK(graph_.CloseAllInputStreams());
+  MP_EXPECT_OK(graph_.WaitUntilDone());
+}
+
+// A Calculator that outputs a summary packet in CalculatorBase::Close().
+class PacketOnCloseCalculator : public CalculatorBase {
+ public:
+  static ::mediapipe::Status GetContract(CalculatorContract* cc) {
+    cc->Inputs().Index(0).Set<int>();
+    cc->Outputs().Index(0).Set<int>();
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Open(CalculatorContext* cc) final {
+    cc->SetOffset(TimestampDiff(0));
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Process(CalculatorContext* cc) final {
+    sum_ += cc->Inputs().Index(0).Value().Get<int>();
+    cc->Outputs().Index(0).AddPacket(cc->Inputs().Index(0).Value());
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Close(CalculatorContext* cc) final {
+    cc->Outputs().Index(0).AddPacket(
+        MakePacket<int>(sum_).At(Timestamp::Max()));
+    return ::mediapipe::OkStatus();
+  }
+
+ private:
+  int sum_ = 0;
+};
+REGISTER_CALCULATOR(PacketOnCloseCalculator);
+
+// Demonstrates that all ouput and input streams in PreviousLoopbackCalculator
+// will close as expected when all graph input streams are closed.
+TEST(PreviousLoopbackCalculator, ClosesCorrectly) {
+  std::vector<Packet> outputs;
+  CalculatorGraphConfig graph_config_ =
+      ParseTextProtoOrDie<CalculatorGraphConfig>(R"(
+        input_stream: 'in'
+        node {
+          calculator: 'PreviousLoopbackCalculator'
+          input_stream: 'MAIN:in'
+          input_stream: 'LOOP:out'
+          input_stream_info: { tag_index: 'LOOP' back_edge: true }
+          output_stream: 'PREV_LOOP:previous'
+        }
+        # This calculator synchronizes its inputs as normal, so it is used
+        # to check that both "in" and "previous" are ready.
+        node {
+          calculator: 'PassThroughCalculator'
+          input_stream: 'in'
+          input_stream: 'previous'
+          output_stream: 'out'
+          output_stream: 'previous2'
+        }
+        node {
+          calculator: 'PacketOnCloseCalculator'
+          input_stream: 'out'
+          output_stream: 'close_out'
+        }
+      )");
+  tool::AddVectorSink("close_out", &graph_config_, &outputs);
+
+  CalculatorGraph graph_;
+  MP_ASSERT_OK(graph_.Initialize(graph_config_, {}));
+  MP_ASSERT_OK(graph_.StartRun({}));
+
+  auto send_packet = [&graph_](const std::string& input_name, int n) {
+    MP_EXPECT_OK(graph_.AddPacketToInputStream(
+        input_name, MakePacket<int>(n).At(Timestamp(n))));
  };

  send_packet("in", 1);
  MP_EXPECT_OK(graph_.WaitUntilIdle());
-  EXPECT_EQ(TimestampValues(in_prev), (std::vector<int64>{1}));
-  EXPECT_EQ(pair_values(in_prev.back()), std::make_pair(1, -1));
+  EXPECT_THAT(TimestampValues(outputs), ElementsAre(1));
+
+  send_packet("in", 2);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(TimestampValues(outputs), ElementsAre(1, 2));

  send_packet("in", 5);
  MP_EXPECT_OK(graph_.WaitUntilIdle());
-  EXPECT_EQ(TimestampValues(in_prev), (std::vector<int64>{1, 5}));
-  EXPECT_EQ(pair_values(in_prev.back()), std::make_pair(5, 1));
+  EXPECT_THAT(TimestampValues(outputs), ElementsAre(1, 2, 5));

  send_packet("in", 15);
  MP_EXPECT_OK(graph_.WaitUntilIdle());
-  EXPECT_EQ(TimestampValues(in_prev), (std::vector<int64>{1, 5, 15}));
-  EXPECT_EQ(pair_values(in_prev.back()), std::make_pair(15, 5));
+  EXPECT_THAT(TimestampValues(outputs), ElementsAre(1, 2, 5, 15));
+
+  MP_EXPECT_OK(graph_.CloseAllInputStreams());
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(TimestampValues(outputs),
+              ElementsAre(1, 2, 5, 15, Timestamp::Max().Value()));
+
+  MP_EXPECT_OK(graph_.WaitUntilDone());
+}
+
+// Demonstrates that downstream calculators won't be blocked by
+// always-empty-LOOP-stream.
+TEST(PreviousLoopbackCalculator, EmptyLoopForever) {
+  std::vector<Packet> outputs;
+  CalculatorGraphConfig graph_config_ =
+      ParseTextProtoOrDie<CalculatorGraphConfig>(R"(
+        input_stream: 'in'
+        node {
+          calculator: 'PreviousLoopbackCalculator'
+          input_stream: 'MAIN:in'
+          input_stream: 'LOOP:previous'
+          input_stream_info: { tag_index: 'LOOP' back_edge: true }
+          output_stream: 'PREV_LOOP:previous'
+        }
+        # This calculator synchronizes its inputs as normal, so it is used
+        # to check that both "in" and "previous" are ready.
+        node {
+          calculator: 'PassThroughCalculator'
+          input_stream: 'in'
+          input_stream: 'previous'
+          output_stream: 'out'
+          output_stream: 'previous2'
+        }
+        node {
+          calculator: 'PacketOnCloseCalculator'
+          input_stream: 'out'
+          output_stream: 'close_out'
+        }
+      )");
+  tool::AddVectorSink("close_out", &graph_config_, &outputs);
+
+  CalculatorGraph graph_;
+  MP_ASSERT_OK(graph_.Initialize(graph_config_, {}));
+  MP_ASSERT_OK(graph_.StartRun({}));
+
+  auto send_packet = [&graph_](const std::string& input_name, int n) {
+    MP_EXPECT_OK(graph_.AddPacketToInputStream(
+        input_name, MakePacket<int>(n).At(Timestamp(n))));
+  };
+
+  for (int main_ts = 0; main_ts < 50; ++main_ts) {
+    send_packet("in", main_ts);
+    MP_EXPECT_OK(graph_.WaitUntilIdle());
+    std::vector<int64> ts_values = TimestampValues(outputs);
+    EXPECT_EQ(ts_values.size(), main_ts + 1);
+    for (int j = 0; j < main_ts + 1; ++j) {
+      EXPECT_EQ(ts_values[j], j);
+    }
+  }
+
+  MP_EXPECT_OK(graph_.CloseAllInputStreams());
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  MP_EXPECT_OK(graph_.WaitUntilDone());
+}
+
+class PreviousLoopbackCalculatorProcessingTimestampsTest
+    : public testing::Test {
+ protected:
+  void SetUp() override {
+    CalculatorGraphConfig graph_config =
+        ParseTextProtoOrDie<CalculatorGraphConfig>(R"(
+          input_stream: 'input'
+          input_stream: 'force_main_empty'
+          input_stream: 'force_loop_empty'
+          # Used to indicate "main" timestamp bound updates.
+          node {
+            calculator: 'GateCalculator'
+            input_stream: 'input'
+            input_stream: 'DISALLOW:force_main_empty'
+            output_stream: 'main'
+          }
+          node {
+            calculator: 'PreviousLoopbackCalculator'
+            input_stream: 'MAIN:main'
+            input_stream: 'LOOP:loop'
+            input_stream_info: { tag_index: 'LOOP' back_edge: true }
+            output_stream: 'PREV_LOOP:prev_loop'
+          }
+          node {
+            calculator: 'PassThroughCalculator'
+            input_stream: 'input'
+            input_stream: 'prev_loop'
+            output_stream: 'passed_through_input'
+            output_stream: 'passed_through_prev_loop'
+          }
+          # Used to indicate "loop" timestamp bound updates.
+          node {
+            calculator: 'GateCalculator'
+            input_stream: 'input'
+            input_stream: 'DISALLOW:force_loop_empty'
+            output_stream: 'loop'
+          }
+          node {
+            calculator: 'MakePairCalculator'
+            input_stream: 'passed_through_input'
+            input_stream: 'passed_through_prev_loop'
+            output_stream: 'passed_through_input_and_prev_loop'
+          }
+        )");
+    tool::AddVectorSink("passed_through_input_and_prev_loop", &graph_config,
+                        &output_packets_);
+    MP_ASSERT_OK(graph_.Initialize(graph_config, {}));
+    MP_ASSERT_OK(graph_.StartRun({}));
+  }
+
+  void SendPackets(int timestamp, int input, bool force_main_empty,
+                   bool force_loop_empty) {
+    MP_ASSERT_OK(graph_.AddPacketToInputStream(
+        "input", MakePacket<int>(input).At(Timestamp(timestamp))));
+    MP_ASSERT_OK(graph_.AddPacketToInputStream(
+        "force_main_empty",
+        MakePacket<bool>(force_main_empty).At(Timestamp(timestamp))));
+    MP_ASSERT_OK(graph_.AddPacketToInputStream(
+        "force_loop_empty",
+        MakePacket<bool>(force_loop_empty).At(Timestamp(timestamp))));
+  }
+
+  CalculatorGraph graph_;
+  std::vector<Packet> output_packets_;
+};
+
+TEST_F(PreviousLoopbackCalculatorProcessingTimestampsTest,
+       MultiplePacketsEmptyMainNonEmptyLoop) {
+  SendPackets(/*timestamp=*/1, /*input=*/1, /*force_main_empty=*/true,
+              /*force_loop_empty=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/2, /*input=*/2, /*force_main_empty=*/true,
+              /*force_loop_empty=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+                  PairPacket(Timestamp(2), Pair(IntPacket(2), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/3, /*input=*/3, /*force_main_empty=*/true,
+              /*force_loop_empty=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+                  PairPacket(Timestamp(2), Pair(IntPacket(2), EmptyPacket())),
+                  PairPacket(Timestamp(3), Pair(IntPacket(3), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/5, /*input=*/5, /*force_main_empty=*/true,
+              /*force_loop_empty=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+                  PairPacket(Timestamp(2), Pair(IntPacket(2), EmptyPacket())),
+                  PairPacket(Timestamp(3), Pair(IntPacket(3), EmptyPacket())),
+                  PairPacket(Timestamp(5), Pair(IntPacket(5), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/15, /*input=*/15,
+              /*force_main_empty=*/true,
+              /*force_loop_empty=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(
+          PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+          PairPacket(Timestamp(2), Pair(IntPacket(2), EmptyPacket())),
+          PairPacket(Timestamp(3), Pair(IntPacket(3), EmptyPacket())),
+          PairPacket(Timestamp(5), Pair(IntPacket(5), EmptyPacket())),
+          PairPacket(Timestamp(15), Pair(IntPacket(15), EmptyPacket()))));
+
+  MP_EXPECT_OK(graph_.CloseAllInputStreams());
+  MP_EXPECT_OK(graph_.WaitUntilDone());
+}
+
+TEST_F(PreviousLoopbackCalculatorProcessingTimestampsTest,
+       MultiplePacketsNonEmptyMainEmptyLoop) {
+  SendPackets(/*timestamp=*/1, /*input=*/1,
+              /*force_main_empty=*/false,
+              /*force_loop_empty=*/true);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/2, /*input=*/2,
+              /*force_main_empty=*/false,
+              /*force_loop_empty=*/true);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+                  PairPacket(Timestamp(2), Pair(IntPacket(2), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/3, /*input=*/3,
+              /*force_main_empty=*/false,
+              /*force_loop_empty=*/true);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+                  PairPacket(Timestamp(2), Pair(IntPacket(2), EmptyPacket())),
+                  PairPacket(Timestamp(3), Pair(IntPacket(3), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/5, /*input=*/5,
+              /*force_main_empty=*/false,
+              /*force_loop_empty=*/true);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+                  PairPacket(Timestamp(2), Pair(IntPacket(2), EmptyPacket())),
+                  PairPacket(Timestamp(3), Pair(IntPacket(3), EmptyPacket())),
+                  PairPacket(Timestamp(5), Pair(IntPacket(5), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/15, /*input=*/15,
+              /*force_main_empty=*/false,
+              /*force_loop_empty=*/true);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(
+          PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+          PairPacket(Timestamp(2), Pair(IntPacket(2), EmptyPacket())),
+          PairPacket(Timestamp(3), Pair(IntPacket(3), EmptyPacket())),
+          PairPacket(Timestamp(5), Pair(IntPacket(5), EmptyPacket())),
+          PairPacket(Timestamp(15), Pair(IntPacket(15), EmptyPacket()))));
+
+  MP_EXPECT_OK(graph_.CloseAllInputStreams());
+  MP_EXPECT_OK(graph_.WaitUntilDone());
+}
+
+TEST_F(PreviousLoopbackCalculatorProcessingTimestampsTest,
+       MultiplePacketsAlteringMainNonEmptyLoop) {
+  SendPackets(/*timestamp=*/1, /*input=*/1,
+              /*force_main_empty=*/false,
+              /*force_loop_empty=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/2, /*input=*/2, /*force_main_empty=*/true,
+              /*force_loop_empty=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+                  PairPacket(Timestamp(2), Pair(IntPacket(2), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/3, /*input=*/3,
+              /*force_main_empty=*/false,
+              /*force_loop_empty=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+                  PairPacket(Timestamp(2), Pair(IntPacket(2), EmptyPacket())),
+                  PairPacket(Timestamp(3), Pair(IntPacket(3), IntPacket(1)))));
+
+  SendPackets(/*timestamp=*/5, /*input=*/5,
+              /*force_main_empty=*/false,
+              /*force_loop_empty=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+                  PairPacket(Timestamp(2), Pair(IntPacket(2), EmptyPacket())),
+                  PairPacket(Timestamp(3), Pair(IntPacket(3), IntPacket(1))),
+                  PairPacket(Timestamp(5), Pair(IntPacket(5), IntPacket(3)))));
+
+  SendPackets(/*timestamp=*/15, /*input=*/15,
+              /*force_main_empty=*/true,
+              /*force_loop_empty=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(
+          PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+          PairPacket(Timestamp(2), Pair(IntPacket(2), EmptyPacket())),
+          PairPacket(Timestamp(3), Pair(IntPacket(3), IntPacket(1))),
+          PairPacket(Timestamp(5), Pair(IntPacket(5), IntPacket(3))),
+          PairPacket(Timestamp(15), Pair(IntPacket(15), EmptyPacket()))));
+
+  MP_EXPECT_OK(graph_.CloseAllInputStreams());
+  MP_EXPECT_OK(graph_.WaitUntilDone());
+}
+
+TEST_F(PreviousLoopbackCalculatorProcessingTimestampsTest,
+       MultiplePacketsNonEmptyMainAlteringLoop) {
+  SendPackets(/*timestamp=*/1, /*input=*/1,
+              /*force_main_empty=*/false,
+              /*force_loop_empty=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/2, /*input=*/2,
+              /*force_main_empty=*/false,
+              /*force_loop_empty=*/true);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+                  PairPacket(Timestamp(2), Pair(IntPacket(2), IntPacket(1)))));
+
+  SendPackets(/*timestamp=*/3, /*input=*/3,
+              /*force_main_empty=*/false,
+              /*force_loop_empty=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+                  PairPacket(Timestamp(2), Pair(IntPacket(2), IntPacket(1))),
+                  PairPacket(Timestamp(3), Pair(IntPacket(3), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/5, /*input=*/5,
+              /*force_main_empty=*/false,
+              /*force_loop_empty=*/true);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+                  PairPacket(Timestamp(2), Pair(IntPacket(2), IntPacket(1))),
+                  PairPacket(Timestamp(3), Pair(IntPacket(3), EmptyPacket())),
+                  PairPacket(Timestamp(5), Pair(IntPacket(5), IntPacket(3)))));
+
+  SendPackets(/*timestamp=*/15, /*input=*/15,
+              /*force_main_empty=*/false,
+              /*force_loop_empty=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(
+          PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+          PairPacket(Timestamp(2), Pair(IntPacket(2), IntPacket(1))),
+          PairPacket(Timestamp(3), Pair(IntPacket(3), EmptyPacket())),
+          PairPacket(Timestamp(5), Pair(IntPacket(5), IntPacket(3))),
+          PairPacket(Timestamp(15), Pair(IntPacket(15), EmptyPacket()))));
+
+  MP_EXPECT_OK(graph_.CloseAllInputStreams());
+  MP_EXPECT_OK(graph_.WaitUntilDone());
+}
+
+TEST_F(PreviousLoopbackCalculatorProcessingTimestampsTest,
+       MultiplePacketsCheckIfLastCorrectAlteringMainAlteringLoop) {
+  int num_packets = 1000;
+  for (int i = 0; i < num_packets; ++i) {
+    bool force_main_empty = i % 3 == 0 ? true : false;
+    bool force_loop_empty = i % 2 == 0 ? true : false;
+    SendPackets(/*timestamp=*/i + 1, /*input=*/i + 1, force_main_empty,
+                force_loop_empty);
+  }
+  SendPackets(/*timestamp=*/num_packets + 1,
+              /*input=*/num_packets + 1, /*force_main_empty=*/false,
+              /*force_loop_empty=*/false);
+  SendPackets(/*timestamp=*/num_packets + 2,
+              /*input=*/num_packets + 2, /*force_main_empty=*/false,
+              /*force_loop_empty=*/false);
+
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  ASSERT_FALSE(output_packets_.empty());
+  EXPECT_THAT(
+      output_packets_.back(),
+      PairPacket(Timestamp(num_packets + 2),
+                 Pair(IntPacket(num_packets + 2), IntPacket(num_packets + 1))));
+
+  MP_EXPECT_OK(graph_.CloseAllInputStreams());
+  MP_EXPECT_OK(graph_.WaitUntilDone());
+}
+
+// Similar to GateCalculator, but it doesn't propagate timestamp bound updates.
+class DroppingGateCalculator : public CalculatorBase {
+ public:
+  static ::mediapipe::Status GetContract(CalculatorContract* cc) {
+    cc->Inputs().Index(0).SetAny();
+    cc->Inputs().Tag("DISALLOW").Set<bool>();
+    cc->Outputs().Index(0).SetSameAs(&cc->Inputs().Index(0));
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Process(CalculatorContext* cc) final {
+    if (!cc->Inputs().Index(0).IsEmpty() &&
+        !cc->Inputs().Tag("DISALLOW").Get<bool>()) {
+      cc->Outputs().Index(0).AddPacket(cc->Inputs().Index(0).Value());
+    }
+    return ::mediapipe::OkStatus();
+  }
+};
+REGISTER_CALCULATOR(DroppingGateCalculator);
+
+// Tests PreviousLoopbackCalculator in cases when there are no "LOOP" timestamp
+// bound updates and non-empty packets for a while and the aforementioned start
+// to arrive at some point. So, "PREV_LOOP" is delayed for a couple of inputs.
+class PreviousLoopbackCalculatorDelayBehaviorTest : public testing::Test {
+ protected:
+  void SetUp() override {
+    CalculatorGraphConfig graph_config =
+        ParseTextProtoOrDie<CalculatorGraphConfig>(R"(
+          input_stream: 'input'
+          # Drops "loop" when set to "true", delaying output of prev_loop, hence
+          # delaying output of the graph.
+          input_stream: 'delay_next_output'
+          node {
+            calculator: 'PreviousLoopbackCalculator'
+            input_stream: 'MAIN:input'
+            input_stream: 'LOOP:loop'
+            input_stream_info: { tag_index: 'LOOP' back_edge: true }
+            output_stream: 'PREV_LOOP:prev_loop'
+          }
+          node {
+            calculator: 'PassThroughCalculator'
+            input_stream: 'input'
+            input_stream: 'prev_loop'
+            output_stream: 'passed_through_input'
+            output_stream: 'passed_through_prev_loop'
+          }
+          node {
+            calculator: 'DroppingGateCalculator'
+            input_stream: 'input'
+            input_stream: 'DISALLOW:delay_next_output'
+            output_stream: 'loop'
+          }
+          node {
+            calculator: 'MakePairCalculator'
+            input_stream: 'passed_through_input'
+            input_stream: 'passed_through_prev_loop'
+            output_stream: 'passed_through_input_and_prev_loop'
+          }
+        )");
+    tool::AddVectorSink("passed_through_input_and_prev_loop", &graph_config,
+                        &output_packets_);
+    MP_ASSERT_OK(graph_.Initialize(graph_config, {}));
+    MP_ASSERT_OK(graph_.StartRun({}));
+  }
+
+  void SendPackets(int timestamp, int input, bool delay_next_output) {
+    MP_ASSERT_OK(graph_.AddPacketToInputStream(
+        "input", MakePacket<int>(input).At(Timestamp(timestamp))));
+    MP_ASSERT_OK(graph_.AddPacketToInputStream(
+        "delay_next_output",
+        MakePacket<bool>(delay_next_output).At(Timestamp(timestamp))));
+  }
+
+  CalculatorGraph graph_;
+  std::vector<Packet> output_packets_;
+};
+
+TEST_F(PreviousLoopbackCalculatorDelayBehaviorTest, MultipleDelayedOutputs) {
+  SendPackets(/*timestamp=*/1, /*input=*/1, /*delay_next_output=*/true);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/2, /*input=*/2, /*delay_next_output=*/true);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/3, /*input=*/3, /*delay_next_output=*/true);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/5, /*input=*/5, /*delay_next_output=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+                  PairPacket(Timestamp(2), Pair(IntPacket(2), EmptyPacket())),
+                  PairPacket(Timestamp(3), Pair(IntPacket(3), EmptyPacket())),
+                  PairPacket(Timestamp(5), Pair(IntPacket(5), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/15, /*input=*/15, /*delay_next_output=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(
+          PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+          PairPacket(Timestamp(2), Pair(IntPacket(2), EmptyPacket())),
+          PairPacket(Timestamp(3), Pair(IntPacket(3), EmptyPacket())),
+          PairPacket(Timestamp(5), Pair(IntPacket(5), EmptyPacket())),
+          PairPacket(Timestamp(15), Pair(IntPacket(15), IntPacket(5)))));
+
+  MP_EXPECT_OK(graph_.CloseAllInputStreams());
+  MP_EXPECT_OK(graph_.WaitUntilDone());
+}
+
+TEST_F(PreviousLoopbackCalculatorDelayBehaviorTest,
+       NonDelayedOutputFollowedByMultipleDelayedOutputs) {
+  SendPackets(/*timestamp=*/1, /*input=*/1, /*delay_next_output=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/2, /*input=*/2, /*delay_next_output=*/true);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+                  PairPacket(Timestamp(2), Pair(IntPacket(2), IntPacket(1)))));
+
+  SendPackets(/*timestamp=*/3, /*input=*/3, /*delay_next_output=*/true);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+                  PairPacket(Timestamp(2), Pair(IntPacket(2), IntPacket(1)))));
+
+  SendPackets(/*timestamp=*/5, /*input=*/5, /*delay_next_output=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+                  PairPacket(Timestamp(2), Pair(IntPacket(2), IntPacket(1))),
+                  PairPacket(Timestamp(3), Pair(IntPacket(3), EmptyPacket())),
+                  PairPacket(Timestamp(5), Pair(IntPacket(5), EmptyPacket()))));
+
+  SendPackets(/*timestamp=*/15, /*input=*/15, /*delay_next_output=*/false);
+  MP_EXPECT_OK(graph_.WaitUntilIdle());
+  EXPECT_THAT(
+      output_packets_,
+      ElementsAre(
+          PairPacket(Timestamp(1), Pair(IntPacket(1), EmptyPacket())),
+          PairPacket(Timestamp(2), Pair(IntPacket(2), IntPacket(1))),
+          PairPacket(Timestamp(3), Pair(IntPacket(3), EmptyPacket())),
+          PairPacket(Timestamp(5), Pair(IntPacket(5), EmptyPacket())),
+          PairPacket(Timestamp(15), Pair(IntPacket(15), IntPacket(5)))));

  MP_EXPECT_OK(graph_.CloseAllInputStreams());
  MP_EXPECT_OK(graph_.WaitUntilDone());
@@ -0,0 +1,161 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <map>
+#include <memory>
+#include <set>
+#include <string>
+
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/port/logging.h"
+#include "mediapipe/framework/port/ret_check.h"
+#include "mediapipe/framework/port/status.h"
+
+namespace mediapipe {
+
+using mediapipe::PacketTypeSet;
+using mediapipe::Timestamp;
+
+namespace {
+
+constexpr char kTagAtPreStream[] = "AT_PRESTREAM";
+constexpr char kTagAtPostStream[] = "AT_POSTSTREAM";
+constexpr char kTagAtZero[] = "AT_ZERO";
+constexpr char kTagAtTick[] = "AT_TICK";
+constexpr char kTagTick[] = "TICK";
+
+static std::map<std::string, Timestamp>* kTimestampMap = []() {
+  auto* res = new std::map<std::string, Timestamp>();
+  res->emplace(kTagAtPreStream, Timestamp::PreStream());
+  res->emplace(kTagAtPostStream, Timestamp::PostStream());
+  res->emplace(kTagAtZero, Timestamp(0));
+  res->emplace(kTagAtTick, Timestamp::Unset());
+  return res;
+}();
+
+template <typename CC>
+std::string GetOutputTag(const CC& cc) {
+  // Single output tag only is required by contract.
+  return *cc.Outputs().GetTags().begin();
+}
+
+}  // namespace
+
+// Outputs side packet(s) in corresponding output stream(s) with a particular
+// timestamp, depending on the tag used to define output stream(s). (One tag can
+// be used only.)
+//
+// Valid tags are AT_PRESTREAM, AT_POSTSTREAM, AT_ZERO and AT_TICK and
+// corresponding timestamps are Timestamp::PreStream(), Timestamp::PostStream(),
+// Timestamp(0) and timestamp of a packet received in TICK input.
+//
+// Examples:
+// node {
+//   calculator: "SidePacketToStreamCalculator"
+//   input_side_packet: "side_packet"
+//   output_stream: "AT_PRESTREAM:packet"
+// }
+//
+// node {
+//   calculator: "SidePacketToStreamCalculator"
+//   input_stream: "TICK:tick"
+//   input_side_packet: "side_packet"
+//   output_stream: "AT_TICK:packet"
+// }
+class SidePacketToStreamCalculator : public CalculatorBase {
+ public:
+  SidePacketToStreamCalculator() = default;
+  ~SidePacketToStreamCalculator() override = default;
+
+  static ::mediapipe::Status GetContract(CalculatorContract* cc);
+  ::mediapipe::Status Open(CalculatorContext* cc) override;
+  ::mediapipe::Status Process(CalculatorContext* cc) override;
+  ::mediapipe::Status Close(CalculatorContext* cc) override;
+
+ private:
+  bool is_tick_processing_ = false;
+  std::string output_tag_;
+};
+REGISTER_CALCULATOR(SidePacketToStreamCalculator);
+
+::mediapipe::Status SidePacketToStreamCalculator::GetContract(
+    CalculatorContract* cc) {
+  const auto& tags = cc->Outputs().GetTags();
+  RET_CHECK(tags.size() == 1 && kTimestampMap->count(*tags.begin()) == 1)
+      << "Only one of AT_PRESTREAM, AT_POSTSTREAM, AT_ZERO and AT_TICK tags is "
+         "allowed and required to specify output stream(s).";
+  RET_CHECK(
+      (cc->Outputs().HasTag(kTagAtTick) && cc->Inputs().HasTag(kTagTick)) ||
+      (!cc->Outputs().HasTag(kTagAtTick) && !cc->Inputs().HasTag(kTagTick)))
+      << "Either both of TICK and AT_TICK should be used or none of them.";
+  const std::string output_tag = GetOutputTag(*cc);
+  const int num_entries = cc->Outputs().NumEntries(output_tag);
+  RET_CHECK_EQ(num_entries, cc->InputSidePackets().NumEntries())
+      << "Same number of input side packets and output streams is required.";
+  for (int i = 0; i < num_entries; ++i) {
+    cc->InputSidePackets().Index(i).SetAny();
+    cc->Outputs()
+        .Get(output_tag, i)
+        .SetSameAs(cc->InputSidePackets().Index(i).GetSameAs());
+  }
+
+  if (cc->Inputs().HasTag(kTagTick)) {
+    cc->Inputs().Tag(kTagTick).SetAny();
+  }
+
+  return ::mediapipe::OkStatus();
+}
+
+::mediapipe::Status SidePacketToStreamCalculator::Open(CalculatorContext* cc) {
+  output_tag_ = GetOutputTag(*cc);
+  if (cc->Inputs().HasTag(kTagTick)) {
+    is_tick_processing_ = true;
+    // Set offset, so output timestamp bounds are updated in response to TICK
+    // timestamp bound update.
+    cc->SetOffset(TimestampDiff(0));
+  }
+  return ::mediapipe::OkStatus();
+}
+
+::mediapipe::Status SidePacketToStreamCalculator::Process(
+    CalculatorContext* cc) {
+  if (is_tick_processing_) {
+    // TICK input is guaranteed to be non-empty, as it's the only input stream
+    // for this calculator.
+    const auto& timestamp = cc->Inputs().Tag(kTagTick).Value().Timestamp();
+    for (int i = 0; i < cc->Outputs().NumEntries(output_tag_); ++i) {
+      cc->Outputs()
+          .Get(output_tag_, i)
+          .AddPacket(cc->InputSidePackets().Index(i).At(timestamp));
+    }
+
+    return ::mediapipe::OkStatus();
+  }
+
+  return ::mediapipe::tool::StatusStop();
+}
+
+::mediapipe::Status SidePacketToStreamCalculator::Close(CalculatorContext* cc) {
+  if (!cc->Outputs().HasTag(kTagAtTick)) {
+    const auto& timestamp = kTimestampMap->at(output_tag_);
+    for (int i = 0; i < cc->Outputs().NumEntries(output_tag_); ++i) {
+      cc->Outputs()
+          .Get(output_tag_, i)
+          .AddPacket(cc->InputSidePackets().Index(i).At(timestamp));
+    }
+  }
+  return ::mediapipe::OkStatus();
+}
+
+}  // namespace mediapipe
@@ -0,0 +1,275 @@
+// Copyright 2020 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <string>
+#include <vector>
+
+#include "absl/memory/memory.h"
+#include "absl/strings/match.h"
+#include "absl/strings/str_replace.h"
+#include "absl/strings/string_view.h"
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/port/gtest.h"
+#include "mediapipe/framework/port/integral_types.h"
+#include "mediapipe/framework/port/parse_text_proto.h"
+#include "mediapipe/framework/port/status.h"
+#include "mediapipe/framework/port/status_matchers.h"
+#include "mediapipe/framework/tool/options_util.h"
+
+namespace mediapipe {
+namespace {
+
+TEST(SidePacketToStreamCalculator, WrongConfig_MissingTick) {
+  CalculatorGraphConfig graph_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig>(
+          R"(
+            input_stream: "tick"
+            input_side_packet: "side_packet"
+            output_stream: "packet"
+            node {
+              calculator: "SidePacketToStreamCalculator"
+              input_side_packet: "side_packet"
+              output_stream: "AT_TICK:packet"
+            }
+          )");
+  CalculatorGraph graph;
+  auto status = graph.Initialize(graph_config);
+  EXPECT_FALSE(status.ok());
+  EXPECT_PRED2(
+      absl::StrContains, status.message(),
+      "Either both of TICK and AT_TICK should be used or none of them.");
+}
+
+TEST(SidePacketToStreamCalculator, WrongConfig_NonExistentTag) {
+  CalculatorGraphConfig graph_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig>(
+          R"(
+            input_stream: "tick"
+            input_side_packet: "side_packet"
+            output_stream: "packet"
+            node {
+              calculator: "SidePacketToStreamCalculator"
+              input_side_packet: "side_packet"
+              output_stream: "DOES_NOT_EXIST:packet"
+            }
+          )");
+  CalculatorGraph graph;
+  auto status = graph.Initialize(graph_config);
+  EXPECT_FALSE(status.ok());
+  EXPECT_PRED2(absl::StrContains, status.message(),
+               "Only one of AT_PRESTREAM, AT_POSTSTREAM, AT_ZERO and AT_TICK "
+               "tags is allowed and required to specify output stream(s).");
+}
+
+TEST(SidePacketToStreamCalculator, WrongConfig_MixedTags) {
+  CalculatorGraphConfig graph_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig>(
+          R"(
+            input_stream: "tick"
+            input_side_packet: "side_packet0"
+            input_side_packet: "side_packet1"
+            node {
+              calculator: "SidePacketToStreamCalculator"
+              input_side_packet: "side_packet0"
+              input_side_packet: "side_packet1"
+              output_stream: "AT_TICK:packet0"
+              output_stream: "AT_PRE_STREAM:packet1"
+            }
+          )");
+  CalculatorGraph graph;
+  auto status = graph.Initialize(graph_config);
+  EXPECT_FALSE(status.ok());
+  EXPECT_PRED2(absl::StrContains, status.message(),
+               "Only one of AT_PRESTREAM, AT_POSTSTREAM, AT_ZERO and AT_TICK "
+               "tags is allowed and required to specify output stream(s).");
+}
+
+TEST(SidePacketToStreamCalculator, WrongConfig_NotEnoughSidePackets) {
+  CalculatorGraphConfig graph_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig>(
+          R"(
+            input_side_packet: "side_packet0"
+            input_side_packet: "side_packet1"
+            node {
+              calculator: "SidePacketToStreamCalculator"
+              input_side_packet: "side_packet0"
+              output_stream: "AT_PRESTREAM:0:packet0"
+              output_stream: "AT_PRESTREAM:1:packet1"
+            }
+          )");
+  CalculatorGraph graph;
+  auto status = graph.Initialize(graph_config);
+  EXPECT_FALSE(status.ok());
+  EXPECT_PRED2(
+      absl::StrContains, status.message(),
+      "Same number of input side packets and output streams is required.");
+}
+
+TEST(SidePacketToStreamCalculator, WrongConfig_NotEnoughOutputStreams) {
+  CalculatorGraphConfig graph_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig>(
+          R"(
+            input_side_packet: "side_packet0"
+            input_side_packet: "side_packet1"
+            node {
+              calculator: "SidePacketToStreamCalculator"
+              input_side_packet: "side_packet0"
+              input_side_packet: "side_packet1"
+              output_stream: "AT_PRESTREAM:packet0"
+            }
+          )");
+  CalculatorGraph graph;
+  auto status = graph.Initialize(graph_config);
+  EXPECT_FALSE(status.ok());
+  EXPECT_PRED2(
+      absl::StrContains, status.message(),
+      "Same number of input side packets and output streams is required.");
+}
+
+void DoTestNonAtTickOutputTag(absl::string_view tag,
+                              Timestamp expected_timestamp) {
+  CalculatorGraphConfig graph_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig>(absl::StrReplaceAll(
+          R"(
+            input_side_packet: "side_packet"
+            output_stream: "packet"
+            node {
+              calculator: "SidePacketToStreamCalculator"
+              input_side_packet: "side_packet"
+              output_stream: "$tag:packet"
+            }
+          )",
+          {{"$tag", tag}}));
+  CalculatorGraph graph;
+  MP_ASSERT_OK(graph.Initialize(graph_config));
+  const int expected_value = 10;
+  std::vector<Packet> output_packets;
+  MP_ASSERT_OK(graph.ObserveOutputStream(
+      "packet", [&output_packets](const Packet& packet) {
+        output_packets.push_back(packet);
+        return ::mediapipe::OkStatus();
+      }));
+  MP_ASSERT_OK(
+      graph.StartRun({{"side_packet", MakePacket<int>(expected_value)}}));
+  MP_ASSERT_OK(graph.WaitForObservedOutput());
+
+  ASSERT_FALSE(output_packets.empty());
+  EXPECT_EQ(expected_timestamp, output_packets.back().Timestamp());
+  EXPECT_EQ(expected_value, output_packets.back().Get<int>());
+}
+
+TEST(SidePacketToStreamCalculator, NoAtTickOutputTags) {
+  DoTestNonAtTickOutputTag("AT_PRESTREAM", Timestamp::PreStream());
+  DoTestNonAtTickOutputTag("AT_POSTSTREAM", Timestamp::PostStream());
+  DoTestNonAtTickOutputTag("AT_ZERO", Timestamp(0));
+}
+
+TEST(SidePacketToStreamCalculator, AtTick) {
+  CalculatorGraphConfig graph_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig>(
+          R"(
+            input_stream: "tick"
+            input_side_packet: "side_packet"
+            output_stream: "packet"
+            node {
+              calculator: "SidePacketToStreamCalculator"
+              input_stream: "TICK:tick"
+              input_side_packet: "side_packet"
+              output_stream: "AT_TICK:packet"
+            }
+          )");
+  std::vector<Packet> output_packets;
+  tool::AddVectorSink("packet", &graph_config, &output_packets);
+  CalculatorGraph graph;
+
+  MP_ASSERT_OK(graph.Initialize(graph_config));
+  const int expected_value = 20;
+  MP_ASSERT_OK(
+      graph.StartRun({{"side_packet", MakePacket<int>(expected_value)}}));
+
+  auto tick_and_verify = [&graph, &output_packets,
+                          expected_value](int at_timestamp) {
+    MP_ASSERT_OK(graph.AddPacketToInputStream(
+        "tick",
+        MakePacket<int>(/*doesn't matter*/ 1).At(Timestamp(at_timestamp))));
+    MP_ASSERT_OK(graph.WaitUntilIdle());
+
+    ASSERT_FALSE(output_packets.empty());
+    EXPECT_EQ(Timestamp(at_timestamp), output_packets.back().Timestamp());
+    EXPECT_EQ(expected_value, output_packets.back().Get<int>());
+  };
+
+  tick_and_verify(/*at_timestamp=*/0);
+  tick_and_verify(/*at_timestamp=*/1);
+  tick_and_verify(/*at_timestamp=*/128);
+  tick_and_verify(/*at_timestamp=*/1024);
+  tick_and_verify(/*at_timestamp=*/1025);
+}
+
+TEST(SidePacketToStreamCalculator, AtTick_MultipleSidePackets) {
+  CalculatorGraphConfig graph_config =
+      ParseTextProtoOrDie<CalculatorGraphConfig>(
+          R"(
+            input_stream: "tick"
+            input_side_packet: "side_packet0"
+            input_side_packet: "side_packet1"
+            output_stream: "packet0"
+            output_stream: "packet1"
+            node {
+              calculator: "SidePacketToStreamCalculator"
+              input_stream: "TICK:tick"
+              input_side_packet: "side_packet0"
+              input_side_packet: "side_packet1"
+              output_stream: "AT_TICK:0:packet0"
+              output_stream: "AT_TICK:1:packet1"
+            }
+          )");
+  std::vector<Packet> output_packets0;
+  tool::AddVectorSink("packet0", &graph_config, &output_packets0);
+  std::vector<Packet> output_packets1;
+  tool::AddVectorSink("packet1", &graph_config, &output_packets1);
+  CalculatorGraph graph;
+
+  MP_ASSERT_OK(graph.Initialize(graph_config));
+  const int expected_value0 = 20;
+  const int expected_value1 = 128;
+  MP_ASSERT_OK(
+      graph.StartRun({{"side_packet0", MakePacket<int>(expected_value0)},
+                      {"side_packet1", MakePacket<int>(expected_value1)}}));
+
+  auto tick_and_verify = [&graph, &output_packets0, &output_packets1,
+                          expected_value0, expected_value1](int at_timestamp) {
+    MP_ASSERT_OK(graph.AddPacketToInputStream(
+        "tick",
+        MakePacket<int>(/*doesn't matter*/ 1).At(Timestamp(at_timestamp))));
+    MP_ASSERT_OK(graph.WaitUntilIdle());
+
+    ASSERT_FALSE(output_packets0.empty());
+    ASSERT_FALSE(output_packets1.empty());
+
+    EXPECT_EQ(Timestamp(at_timestamp), output_packets0.back().Timestamp());
+    EXPECT_EQ(expected_value0, output_packets0.back().Get<int>());
+    EXPECT_EQ(Timestamp(at_timestamp), output_packets1.back().Timestamp());
+    EXPECT_EQ(expected_value1, output_packets1.back().Get<int>());
+  };
+
+  tick_and_verify(/*at_timestamp=*/0);
+  tick_and_verify(/*at_timestamp=*/1);
+  tick_and_verify(/*at_timestamp=*/128);
+  tick_and_verify(/*at_timestamp=*/1024);
+  tick_and_verify(/*at_timestamp=*/1025);
+}
+
+}  // namespace
+}  // namespace mediapipe
@@ -16,9 +16,16 @@

 #include <vector>

+#include "mediapipe/framework/formats/detection.pb.h"
 #include "mediapipe/framework/formats/landmark.pb.h"
+#include "mediapipe/framework/formats/matrix.h"
+#include "mediapipe/framework/formats/rect.pb.h"
 #include "tensorflow/lite/interpreter.h"

+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
+#include "tensorflow/lite/delegates/gpu/gl/gl_buffer.h"
+#endif  //  !MEDIAPIPE_DISABLE_GPU
+
 namespace mediapipe {

 // Example config:
@@ -35,10 +42,33 @@ namespace mediapipe {
 //     }
 //   }
 // }
-typedef SplitVectorCalculator<TfLiteTensor> SplitTfLiteTensorVectorCalculator;
+typedef SplitVectorCalculator<TfLiteTensor, false>
+    SplitTfLiteTensorVectorCalculator;
 REGISTER_CALCULATOR(SplitTfLiteTensorVectorCalculator);

-typedef SplitVectorCalculator<::mediapipe::NormalizedLandmark>
+typedef SplitVectorCalculator<::mediapipe::NormalizedLandmark, false>
    SplitLandmarkVectorCalculator;
 REGISTER_CALCULATOR(SplitLandmarkVectorCalculator);
+
+typedef SplitVectorCalculator<::mediapipe::NormalizedLandmarkList, false>
+    SplitNormalizedLandmarkListVectorCalculator;
+REGISTER_CALCULATOR(SplitNormalizedLandmarkListVectorCalculator);
+
+typedef SplitVectorCalculator<::mediapipe::NormalizedRect, false>
+    SplitNormalizedRectVectorCalculator;
+REGISTER_CALCULATOR(SplitNormalizedRectVectorCalculator);
+
+typedef SplitVectorCalculator<Matrix, false> SplitMatrixVectorCalculator;
+REGISTER_CALCULATOR(SplitMatrixVectorCalculator);
+
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
+typedef SplitVectorCalculator<::tflite::gpu::gl::GlBuffer, true>
+    MovableSplitGlBufferVectorCalculator;
+REGISTER_CALCULATOR(MovableSplitGlBufferVectorCalculator);
+#endif
+
+typedef SplitVectorCalculator<::mediapipe::Detection, false>
+    SplitDetectionVectorCalculator;
+REGISTER_CALCULATOR(SplitDetectionVectorCalculator);
+
 }  // namespace mediapipe
@@ -15,12 +15,14 @@
 #ifndef MEDIAPIPE_CALCULATORS_CORE_SPLIT_VECTOR_CALCULATOR_H_
 #define MEDIAPIPE_CALCULATORS_CORE_SPLIT_VECTOR_CALCULATOR_H_

+#include <type_traits>
 #include <vector>

 #include "mediapipe/calculators/core/split_vector_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/port/canonical_errors.h"
 #include "mediapipe/framework/port/ret_check.h"
+#include "mediapipe/framework/port/status.h"
 #include "mediapipe/util/resource_util.h"
 #include "tensorflow/lite/error_reporter.h"
 #include "tensorflow/lite/interpreter.h"
@@ -29,15 +31,31 @@

 namespace mediapipe {

+template <typename T>
+using IsCopyable = std::enable_if_t<std::is_copy_constructible<T>::value, bool>;
+
+template <typename T>
+using IsNotCopyable =
+    std::enable_if_t<!std::is_copy_constructible<T>::value, bool>;
+
+template <typename T>
+using IsMovable = std::enable_if_t<std::is_move_constructible<T>::value, bool>;
+
+template <typename T>
+using IsNotMovable =
+    std::enable_if_t<!std::is_move_constructible<T>::value, bool>;
+
 // Splits an input packet with std::vector<T> into multiple std::vector<T>
 // output packets using the [begin, end) ranges specified in
 // SplitVectorCalculatorOptions. If the option "element_only" is set to true,
 // all ranges should be of size 1 and all outputs will be elements of type T. If
 // "element_only" is false, ranges can be non-zero in size and all outputs will
-// be of type std::vector<T>.
+// be of type std::vector<T>. If the option "combine_outputs" is set to true,
+// only one output stream can be specified and all ranges of elements will be
+// combined into one vector.
 // To use this class for a particular type T, register a calculator using
 // SplitVectorCalculator<T>.
-template <typename T>
+template <typename T, bool move_elements>
 class SplitVectorCalculator : public CalculatorBase {
 public:
  static ::mediapipe::Status GetContract(CalculatorContract* cc) {
@@ -49,28 +67,40 @@ class SplitVectorCalculator : public CalculatorBase {
    const auto& options =
        cc->Options<::mediapipe::SplitVectorCalculatorOptions>();

-    if (cc->Outputs().NumEntries() != options.ranges_size()) {
-      return ::mediapipe::InvalidArgumentError(
-          "The number of output streams should match the number of ranges "
-          "specified in the CalculatorOptions.");
+    if (!std::is_copy_constructible<T>::value || move_elements) {
+      // Ranges of elements shouldn't overlap when the vector contains
+      // non-copyable elements.
+      RET_CHECK_OK(checkRangesDontOverlap(options));
    }

-    // Set the output types for each output stream.
-    for (int i = 0; i < cc->Outputs().NumEntries(); ++i) {
-      if (options.ranges(i).begin() < 0 || options.ranges(i).end() < 0 ||
-          options.ranges(i).begin() >= options.ranges(i).end()) {
+    if (options.combine_outputs()) {
+      RET_CHECK_EQ(cc->Outputs().NumEntries(), 1);
+      cc->Outputs().Index(0).Set<std::vector<T>>();
+      RET_CHECK_OK(checkRangesDontOverlap(options));
+    } else {
+      if (cc->Outputs().NumEntries() != options.ranges_size()) {
        return ::mediapipe::InvalidArgumentError(
-            "Indices should be non-negative and begin index should be less "
-            "than the end index.");
+            "The number of output streams should match the number of ranges "
+            "specified in the CalculatorOptions.");
      }
-      if (options.element_only()) {
-        if (options.ranges(i).end() - options.ranges(i).begin() != 1) {
+
+      // Set the output types for each output stream.
+      for (int i = 0; i < cc->Outputs().NumEntries(); ++i) {
+        if (options.ranges(i).begin() < 0 || options.ranges(i).end() < 0 ||
+            options.ranges(i).begin() >= options.ranges(i).end()) {
          return ::mediapipe::InvalidArgumentError(
-              "Since element_only is true, all ranges should be of size 1.");
+              "Indices should be non-negative and begin index should be less "
+              "than the end index.");
+        }
+        if (options.element_only()) {
+          if (options.ranges(i).end() - options.ranges(i).begin() != 1) {
+            return ::mediapipe::InvalidArgumentError(
+                "Since element_only is true, all ranges should be of size 1.");
+          }
+          cc->Outputs().Index(i).Set<T>();
+        } else {
+          cc->Outputs().Index(i).Set<std::vector<T>>();
        }
-        cc->Outputs().Index(i).Set<T>();
-      } else {
-        cc->Outputs().Index(i).Set<std::vector<T>>();
      }
    }

@@ -83,41 +113,140 @@ class SplitVectorCalculator : public CalculatorBase {
    const auto& options =
        cc->Options<::mediapipe::SplitVectorCalculatorOptions>();

+    element_only_ = options.element_only();
+    combine_outputs_ = options.combine_outputs();
+
    for (const auto& range : options.ranges()) {
      ranges_.push_back({range.begin(), range.end()});
      max_range_end_ = std::max(max_range_end_, range.end());
+      total_elements_ += range.end() - range.begin();
    }

-    element_only_ = options.element_only();
-
    return ::mediapipe::OkStatus();
  }

  ::mediapipe::Status Process(CalculatorContext* cc) override {
-    const auto& input = cc->Inputs().Index(0).Get<std::vector<T>>();
-    RET_CHECK_GE(input.size(), max_range_end_);
+    if (cc->Inputs().Index(0).IsEmpty()) return ::mediapipe::OkStatus();

-    if (element_only_) {
-      for (int i = 0; i < ranges_.size(); ++i) {
-        cc->Outputs().Index(i).AddPacket(
-            MakePacket<T>(input[ranges_[i].first]).At(cc->InputTimestamp()));
-      }
+    if (move_elements) {
+      return ProcessMovableElements<T>(cc);
    } else {
+      return ProcessCopyableElements<T>(cc);
+    }
+  }
+
+  template <typename U, IsCopyable<U> = true>
+  ::mediapipe::Status ProcessCopyableElements(CalculatorContext* cc) {
+    // static_assert(std::is_copy_constructible<U>::value,
+    //              "Cannot copy non-copyable elements");
+    const auto& input = cc->Inputs().Index(0).Get<std::vector<U>>();
+    RET_CHECK_GE(input.size(), max_range_end_);
+    if (combine_outputs_) {
+      auto output = absl::make_unique<std::vector<U>>();
+      output->reserve(total_elements_);
      for (int i = 0; i < ranges_.size(); ++i) {
-        auto output = absl::make_unique<std::vector<T>>(
+        auto elements = absl::make_unique<std::vector<U>>(
            input.begin() + ranges_[i].first,
            input.begin() + ranges_[i].second);
-        cc->Outputs().Index(i).Add(output.release(), cc->InputTimestamp());
+        output->insert(output->end(), elements->begin(), elements->end());
+      }
+      cc->Outputs().Index(0).Add(output.release(), cc->InputTimestamp());
+    } else {
+      if (element_only_) {
+        for (int i = 0; i < ranges_.size(); ++i) {
+          cc->Outputs().Index(i).AddPacket(
+              MakePacket<U>(input[ranges_[i].first]).At(cc->InputTimestamp()));
+        }
+      } else {
+        for (int i = 0; i < ranges_.size(); ++i) {
+          auto output = absl::make_unique<std::vector<T>>(
+              input.begin() + ranges_[i].first,
+              input.begin() + ranges_[i].second);
+          cc->Outputs().Index(i).Add(output.release(), cc->InputTimestamp());
+        }
      }
    }

    return ::mediapipe::OkStatus();
  }

+  template <typename U, IsNotCopyable<U> = true>
+  ::mediapipe::Status ProcessCopyableElements(CalculatorContext* cc) {
+    return ::mediapipe::InternalError("Cannot copy non-copyable elements.");
+  }
+
+  template <typename U, IsMovable<U> = true>
+  ::mediapipe::Status ProcessMovableElements(CalculatorContext* cc) {
+    ::mediapipe::StatusOr<std::unique_ptr<std::vector<U>>> input_status =
+        cc->Inputs().Index(0).Value().Consume<std::vector<U>>();
+    if (!input_status.ok()) return input_status.status();
+    std::unique_ptr<std::vector<U>> input_vector =
+        std::move(input_status).ValueOrDie();
+    RET_CHECK_GE(input_vector->size(), max_range_end_);
+
+    if (combine_outputs_) {
+      auto output = absl::make_unique<std::vector<U>>();
+      output->reserve(total_elements_);
+      for (int i = 0; i < ranges_.size(); ++i) {
+        output->insert(
+            output->end(),
+            std::make_move_iterator(input_vector->begin() + ranges_[i].first),
+            std::make_move_iterator(input_vector->begin() + ranges_[i].second));
+      }
+      cc->Outputs().Index(0).Add(output.release(), cc->InputTimestamp());
+    } else {
+      if (element_only_) {
+        for (int i = 0; i < ranges_.size(); ++i) {
+          cc->Outputs().Index(i).AddPacket(
+              MakePacket<U>(std::move(input_vector->at(ranges_[i].first)))
+                  .At(cc->InputTimestamp()));
+        }
+      } else {
+        for (int i = 0; i < ranges_.size(); ++i) {
+          auto output = absl::make_unique<std::vector<T>>();
+          output->insert(
+              output->end(),
+              std::make_move_iterator(input_vector->begin() + ranges_[i].first),
+              std::make_move_iterator(input_vector->begin() +
+                                      ranges_[i].second));
+          cc->Outputs().Index(i).Add(output.release(), cc->InputTimestamp());
+        }
+      }
+    }
+
+    return ::mediapipe::OkStatus();
+  }
+
+  template <typename U, IsNotMovable<U> = true>
+  ::mediapipe::Status ProcessMovableElements(CalculatorContext* cc) {
+    return ::mediapipe::InternalError("Cannot move non-movable elements.");
+  }
+
 private:
+  static ::mediapipe::Status checkRangesDontOverlap(
+      const ::mediapipe::SplitVectorCalculatorOptions& options) {
+    for (int i = 0; i < options.ranges_size() - 1; ++i) {
+      for (int j = i + 1; j < options.ranges_size(); ++j) {
+        const auto& range_0 = options.ranges(i);
+        const auto& range_1 = options.ranges(j);
+        if ((range_0.begin() >= range_1.begin() &&
+             range_0.begin() < range_1.end()) ||
+            (range_1.begin() >= range_0.begin() &&
+             range_1.begin() < range_0.end())) {
+          return ::mediapipe::InvalidArgumentError(
+              "Ranges must be non-overlapping when using combine_outputs "
+              "option.");
+        }
+      }
+    }
+    return ::mediapipe::OkStatus();
+  }
+
  std::vector<std::pair<int32, int32>> ranges_;
  int32 max_range_end_ = -1;
+  int32 total_elements_ = 0;
  bool element_only_ = false;
+  bool combine_outputs_ = false;
 };

 }  // namespace mediapipe
@@ -37,4 +37,7 @@ message SplitVectorCalculatorOptions {
  // just element of type T. By default, if a range specifies only one element,
  // it is outputted as an std::vector<T>.
  optional bool element_only = 2 [default = false];
+
+  // Combines output elements to one vector.
+  optional bool combine_outputs = 3 [default = false];
 }
@@ -105,6 +105,34 @@ class SplitTfLiteTensorVectorCalculatorTest : public ::testing::Test {
    }
  }

+  void ValidateCombinedVectorOutput(std::vector<Packet>& output_packets,
+                                    int expected_elements,
+                                    std::vector<int>& input_begin_indices,
+                                    std::vector<int>& input_end_indices) {
+    ASSERT_EQ(1, output_packets.size());
+    ASSERT_EQ(input_begin_indices.size(), input_end_indices.size());
+    const std::vector<TfLiteTensor>& output_vec =
+        output_packets[0].Get<std::vector<TfLiteTensor>>();
+    ASSERT_EQ(expected_elements, output_vec.size());
+    const int num_ranges = input_begin_indices.size();
+
+    int element_id = 0;
+    for (int range_id = 0; range_id < num_ranges; ++range_id) {
+      for (int i = input_begin_indices[range_id];
+           i < input_end_indices[range_id]; ++i) {
+        const int expected_value = i;
+        const TfLiteTensor* result = &output_vec[element_id];
+        float* result_buffer = result->data.f;
+        ASSERT_NE(result_buffer, nullptr);
+        ASSERT_EQ(result_buffer, input_buffers_[i]);
+        for (int j = 0; j < width * height * channels; ++j) {
+          ASSERT_EQ(expected_value, result_buffer[j]);
+        }
+        element_id++;
+      }
+    }
+  }
+
  void ValidateElementOutput(std::vector<Packet>& output_packets,
                             int input_begin_index) {
    ASSERT_EQ(1, output_packets.size());
@@ -234,6 +262,65 @@ TEST_F(SplitTfLiteTensorVectorCalculatorTest, InvalidOutputStreamCountTest) {
  ASSERT_FALSE(graph.Initialize(graph_config).ok());
 }

+TEST_F(SplitTfLiteTensorVectorCalculatorTest,
+       InvalidCombineOutputsMultipleOutputsTest) {
+  ASSERT_NE(interpreter_, nullptr);
+
+  // Prepare a graph to use the SplitTfLiteTensorVectorCalculator.
+  CalculatorGraphConfig graph_config =
+      ::mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(
+          R"(
+            input_stream: "tensor_in"
+            node {
+              calculator: "SplitTfLiteTensorVectorCalculator"
+              input_stream: "tensor_in"
+              output_stream: "range_0"
+              output_stream: "range_1"
+              options {
+                [mediapipe.SplitVectorCalculatorOptions.ext] {
+                  ranges: { begin: 0 end: 1 }
+                  ranges: { begin: 2 end: 3 }
+                  combine_outputs: true
+                }
+              }
+            }
+          )");
+
+  // Run the graph.
+  CalculatorGraph graph;
+  // The graph should fail running because the number of output streams does not
+  // match the number of range elements in the options.
+  ASSERT_FALSE(graph.Initialize(graph_config).ok());
+}
+
+TEST_F(SplitTfLiteTensorVectorCalculatorTest, InvalidOverlappingRangesTest) {
+  ASSERT_NE(interpreter_, nullptr);
+
+  // Prepare a graph to use the SplitTfLiteTensorVectorCalculator.
+  CalculatorGraphConfig graph_config =
+      ::mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(
+          R"(
+            input_stream: "tensor_in"
+            node {
+              calculator: "SplitTfLiteTensorVectorCalculator"
+              input_stream: "tensor_in"
+              output_stream: "range_0"
+              options {
+                [mediapipe.SplitVectorCalculatorOptions.ext] {
+                  ranges: { begin: 0 end: 3 }
+                  ranges: { begin: 1 end: 4 }
+                  combine_outputs: true
+                }
+              }
+            }
+          )");
+
+  // Run the graph.
+  CalculatorGraph graph;
+  // The graph should fail running because there are overlapping ranges.
+  ASSERT_FALSE(graph.Initialize(graph_config).ok());
+}
+
 TEST_F(SplitTfLiteTensorVectorCalculatorTest, SmokeTestElementOnly) {
  ASSERT_NE(interpreter_, nullptr);

@@ -289,6 +376,53 @@ TEST_F(SplitTfLiteTensorVectorCalculatorTest, SmokeTestElementOnly) {
  MP_ASSERT_OK(graph.WaitUntilDone());
 }

+TEST_F(SplitTfLiteTensorVectorCalculatorTest, SmokeTestCombiningOutputs) {
+  ASSERT_NE(interpreter_, nullptr);
+
+  PrepareTfLiteTensorVector(/*vector_size=*/5);
+  ASSERT_NE(input_vec_, nullptr);
+
+  // Prepare a graph to use the SplitTfLiteTensorVectorCalculator.
+  CalculatorGraphConfig graph_config =
+      ::mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(
+          R"(
+            input_stream: "tensor_in"
+            node {
+              calculator: "SplitTfLiteTensorVectorCalculator"
+              input_stream: "tensor_in"
+              output_stream: "range_0"
+              options {
+                [mediapipe.SplitVectorCalculatorOptions.ext] {
+                  ranges: { begin: 0 end: 1 }
+                  ranges: { begin: 2 end: 3 }
+                  ranges: { begin: 4 end: 5 }
+                  combine_outputs: true
+                }
+              }
+            }
+          )");
+  std::vector<Packet> range_0_packets;
+  tool::AddVectorSink("range_0", &graph_config, &range_0_packets);
+
+  // Run the graph.
+  CalculatorGraph graph;
+  MP_ASSERT_OK(graph.Initialize(graph_config));
+  MP_ASSERT_OK(graph.StartRun({}));
+  MP_ASSERT_OK(graph.AddPacketToInputStream(
+      "tensor_in", Adopt(input_vec_.release()).At(Timestamp(0))));
+  // Wait until the calculator finishes processing.
+  MP_ASSERT_OK(graph.WaitUntilIdle());
+
+  std::vector<int> input_begin_indices = {0, 2, 4};
+  std::vector<int> input_end_indices = {1, 3, 5};
+  ValidateCombinedVectorOutput(range_0_packets, /*expected_elements=*/3,
+                               input_begin_indices, input_end_indices);
+
+  // Fully close the graph at the end.
+  MP_ASSERT_OK(graph.CloseInputStream("tensor_in"));
+  MP_ASSERT_OK(graph.WaitUntilDone());
+}
+
 TEST_F(SplitTfLiteTensorVectorCalculatorTest,
       ElementOnlyDisablesVectorOutputs) {
  // Prepare a graph to use the SplitTfLiteTensorVectorCalculator.
@@ -318,4 +452,243 @@ TEST_F(SplitTfLiteTensorVectorCalculatorTest,
  ASSERT_FALSE(graph.Initialize(graph_config).ok());
 }

+typedef SplitVectorCalculator<std::unique_ptr<int>, true>
+    MovableSplitUniqueIntPtrCalculator;
+REGISTER_CALCULATOR(MovableSplitUniqueIntPtrCalculator);
+
+class MovableSplitUniqueIntPtrCalculatorTest : public ::testing::Test {
+ protected:
+  void ValidateVectorOutput(std::vector<Packet>& output_packets,
+                            int expected_elements, int input_begin_index) {
+    ASSERT_EQ(1, output_packets.size());
+    const std::vector<std::unique_ptr<int>>& output_vec =
+        output_packets[0].Get<std::vector<std::unique_ptr<int>>>();
+    ASSERT_EQ(expected_elements, output_vec.size());
+
+    for (int i = 0; i < expected_elements; ++i) {
+      const int expected_value = input_begin_index + i;
+      const std::unique_ptr<int>& result = output_vec[i];
+      ASSERT_NE(result, nullptr);
+      ASSERT_EQ(expected_value, *result);
+    }
+  }
+
+  void ValidateElementOutput(std::vector<Packet>& output_packets,
+                             int expected_value) {
+    ASSERT_EQ(1, output_packets.size());
+    const std::unique_ptr<int>& result =
+        output_packets[0].Get<std::unique_ptr<int>>();
+    ASSERT_NE(result, nullptr);
+    ASSERT_EQ(expected_value, *result);
+  }
+
+  void ValidateCombinedVectorOutput(std::vector<Packet>& output_packets,
+                                    int expected_elements,
+                                    std::vector<int>& input_begin_indices,
+                                    std::vector<int>& input_end_indices) {
+    ASSERT_EQ(1, output_packets.size());
+    ASSERT_EQ(input_begin_indices.size(), input_end_indices.size());
+    const std::vector<std::unique_ptr<int>>& output_vector =
+        output_packets[0].Get<std::vector<std::unique_ptr<int>>>();
+    ASSERT_EQ(expected_elements, output_vector.size());
+    const int num_ranges = input_begin_indices.size();
+
+    int element_id = 0;
+    for (int range_id = 0; range_id < num_ranges; ++range_id) {
+      for (int i = input_begin_indices[range_id];
+           i < input_end_indices[range_id]; ++i) {
+        const int expected_value = i;
+        const std::unique_ptr<int>& result = output_vector[element_id];
+        ASSERT_NE(result, nullptr);
+        ASSERT_EQ(expected_value, *result);
+        ++element_id;
+      }
+    }
+  }
+};
+
+TEST_F(MovableSplitUniqueIntPtrCalculatorTest, InvalidOverlappingRangesTest) {
+  // Prepare a graph to use the TestMovableSplitUniqueIntPtrVectorCalculator.
+  CalculatorGraphConfig graph_config =
+      ::mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(
+          R"(
+            input_stream: "input_vector"
+            node {
+              calculator: "MovableSplitUniqueIntPtrCalculator"
+              input_stream: "input_vector"
+              output_stream: "range_0"
+              options {
+                [mediapipe.SplitVectorCalculatorOptions.ext] {
+                  ranges: { begin: 0 end: 3 }
+                  ranges: { begin: 1 end: 4 }
+                }
+              }
+            }
+          )");
+
+  // Run the graph.
+  CalculatorGraph graph;
+  // The graph should fail running because there are overlapping ranges.
+  ASSERT_FALSE(graph.Initialize(graph_config).ok());
+}
+
+TEST_F(MovableSplitUniqueIntPtrCalculatorTest, SmokeTest) {
+  // Prepare a graph to use the TestMovableSplitUniqueIntPtrVectorCalculator.
+  CalculatorGraphConfig graph_config =
+      ::mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(
+          R"(
+            input_stream: "input_vector"
+            node {
+              calculator: "MovableSplitUniqueIntPtrCalculator"
+              input_stream: "input_vector"
+              output_stream: "range_0"
+              output_stream: "range_1"
+              output_stream: "range_2"
+              options {
+                [mediapipe.SplitVectorCalculatorOptions.ext] {
+                  ranges: { begin: 0 end: 1 }
+                  ranges: { begin: 1 end: 4 }
+                  ranges: { begin: 4 end: 5 }
+                }
+              }
+            }
+          )");
+
+  std::vector<Packet> range_0_packets;
+  tool::AddVectorSink("range_0", &graph_config, &range_0_packets);
+  std::vector<Packet> range_1_packets;
+  tool::AddVectorSink("range_1", &graph_config, &range_1_packets);
+  std::vector<Packet> range_2_packets;
+  tool::AddVectorSink("range_2", &graph_config, &range_2_packets);
+
+  // Run the graph.
+  CalculatorGraph graph;
+  MP_ASSERT_OK(graph.Initialize(graph_config));
+  MP_ASSERT_OK(graph.StartRun({}));
+
+  // input_vector : {0, 1, 2, 3, 4, 5}
+  std::unique_ptr<std::vector<std::unique_ptr<int>>> input_vector =
+      absl::make_unique<std::vector<std::unique_ptr<int>>>(6);
+  for (int i = 0; i < 6; ++i) {
+    input_vector->at(i) = absl::make_unique<int>(i);
+  }
+
+  MP_ASSERT_OK(graph.AddPacketToInputStream(
+      "input_vector", Adopt(input_vector.release()).At(Timestamp(1))));
+
+  MP_ASSERT_OK(graph.WaitUntilIdle());
+  MP_ASSERT_OK(graph.CloseAllPacketSources());
+  MP_ASSERT_OK(graph.WaitUntilDone());
+
+  ValidateVectorOutput(range_0_packets, /*expected_elements=*/1,
+                       /*input_begin_index=*/0);
+  ValidateVectorOutput(range_1_packets, /*expected_elements=*/3,
+                       /*input_begin_index=*/1);
+  ValidateVectorOutput(range_2_packets, /*expected_elements=*/1,
+                       /*input_begin_index=*/4);
+}
+
+TEST_F(MovableSplitUniqueIntPtrCalculatorTest, SmokeTestElementOnly) {
+  // Prepare a graph to use the TestMovableSplitUniqueIntPtrVectorCalculator.
+  CalculatorGraphConfig graph_config =
+      ::mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(
+          R"(
+            input_stream: "input_vector"
+            node {
+              calculator: "MovableSplitUniqueIntPtrCalculator"
+              input_stream: "input_vector"
+              output_stream: "range_0"
+              output_stream: "range_1"
+              output_stream: "range_2"
+              options {
+                [mediapipe.SplitVectorCalculatorOptions.ext] {
+                  ranges: { begin: 0 end: 1 }
+                  ranges: { begin: 2 end: 3 }
+                  ranges: { begin: 4 end: 5 }
+                  element_only: true
+                }
+              }
+            }
+          )");
+
+  std::vector<Packet> range_0_packets;
+  tool::AddVectorSink("range_0", &graph_config, &range_0_packets);
+  std::vector<Packet> range_1_packets;
+  tool::AddVectorSink("range_1", &graph_config, &range_1_packets);
+  std::vector<Packet> range_2_packets;
+  tool::AddVectorSink("range_2", &graph_config, &range_2_packets);
+
+  // Run the graph.
+  CalculatorGraph graph;
+  MP_ASSERT_OK(graph.Initialize(graph_config));
+  MP_ASSERT_OK(graph.StartRun({}));
+
+  // input_vector : {0, 1, 2, 3, 4, 5}
+  std::unique_ptr<std::vector<std::unique_ptr<int>>> input_vector =
+      absl::make_unique<std::vector<std::unique_ptr<int>>>(6);
+  for (int i = 0; i < 6; ++i) {
+    input_vector->at(i) = absl::make_unique<int>(i);
+  }
+
+  MP_ASSERT_OK(graph.AddPacketToInputStream(
+      "input_vector", Adopt(input_vector.release()).At(Timestamp(1))));
+
+  MP_ASSERT_OK(graph.WaitUntilIdle());
+  MP_ASSERT_OK(graph.CloseAllPacketSources());
+  MP_ASSERT_OK(graph.WaitUntilDone());
+
+  ValidateElementOutput(range_0_packets, /*expected_value=*/0);
+  ValidateElementOutput(range_1_packets, /*expected_value=*/2);
+  ValidateElementOutput(range_2_packets, /*expected_value=*/4);
+}
+
+TEST_F(MovableSplitUniqueIntPtrCalculatorTest, SmokeTestCombiningOutputs) {
+  // Prepare a graph to use the TestMovableSplitUniqueIntPtrVectorCalculator.
+  CalculatorGraphConfig graph_config =
+      ::mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(
+          R"(
+            input_stream: "input_vector"
+            node {
+              calculator: "MovableSplitUniqueIntPtrCalculator"
+              input_stream: "input_vector"
+              output_stream: "range_0"
+              options {
+                [mediapipe.SplitVectorCalculatorOptions.ext] {
+                  ranges: { begin: 0 end: 1 }
+                  ranges: { begin: 2 end: 3 }
+                  ranges: { begin: 4 end: 5 }
+                  combine_outputs: true
+                }
+              }
+            }
+          )");
+
+  std::vector<Packet> range_0_packets;
+  tool::AddVectorSink("range_0", &graph_config, &range_0_packets);
+
+  // Run the graph.
+  CalculatorGraph graph;
+  MP_ASSERT_OK(graph.Initialize(graph_config));
+  MP_ASSERT_OK(graph.StartRun({}));
+
+  // input_vector : {0, 1, 2, 3, 4, 5}
+  std::unique_ptr<std::vector<std::unique_ptr<int>>> input_vector =
+      absl::make_unique<std::vector<std::unique_ptr<int>>>(6);
+  for (int i = 0; i < 6; ++i) {
+    input_vector->at(i) = absl::make_unique<int>(i);
+  }
+
+  MP_ASSERT_OK(graph.AddPacketToInputStream(
+      "input_vector", Adopt(input_vector.release()).At(Timestamp(1))));
+
+  MP_ASSERT_OK(graph.WaitUntilIdle());
+  MP_ASSERT_OK(graph.CloseAllPacketSources());
+  MP_ASSERT_OK(graph.WaitUntilDone());
+
+  std::vector<int> input_begin_indices = {0, 2, 4};
+  std::vector<int> input_end_indices = {1, 3, 5};
+  ValidateCombinedVectorOutput(range_0_packets, /*expected_elements=*/3,
+                               input_begin_indices, input_end_indices);
+}
+
 }  // namespace mediapipe
@@ -0,0 +1,48 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/port/status.h"
+#include "mediapipe/framework/timestamp.h"
+
+namespace mediapipe {
+
+// A calculator that takes a packet of an input stream and converts it to an
+// output side packet. This calculator only works under the assumption that the
+// input stream only has a single packet passing through.
+//
+// Example config:
+// node {
+//   calculator: "StreamToSidePacketCalculator"
+//   input_stream: "stream"
+//   output_side_packet: "side_packet"
+// }
+class StreamToSidePacketCalculator : public mediapipe::CalculatorBase {
+ public:
+  static mediapipe::Status GetContract(mediapipe::CalculatorContract* cc) {
+    cc->Inputs().Index(0).SetAny();
+    cc->OutputSidePackets().Index(0).SetAny();
+    return mediapipe::OkStatus();
+  }
+
+  mediapipe::Status Process(mediapipe::CalculatorContext* cc) override {
+    mediapipe::Packet& packet = cc->Inputs().Index(0).Value();
+    cc->OutputSidePackets().Index(0).Set(
+        packet.At(mediapipe::Timestamp::Unset()));
+    return mediapipe::OkStatus();
+  }
+};
+REGISTER_CALCULATOR(StreamToSidePacketCalculator);
+
+}  // namespace mediapipe
@@ -0,0 +1,67 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <memory>
+#include <string>
+
+#include "absl/memory/memory.h"
+#include "mediapipe/framework/calculator_runner.h"
+#include "mediapipe/framework/packet.h"
+#include "mediapipe/framework/port/gmock.h"
+#include "mediapipe/framework/port/gtest.h"
+#include "mediapipe/framework/port/status.h"
+#include "mediapipe/framework/port/status_matchers.h"
+#include "mediapipe/framework/timestamp.h"
+
+namespace mediapipe {
+
+using ::testing::Test;
+
+class StreamToSidePacketCalculatorTest : public Test {
+ protected:
+  StreamToSidePacketCalculatorTest() {
+    const char kConfig[] = R"(
+      calculator: "StreamToSidePacketCalculator"
+      input_stream: "stream"
+      output_side_packet: "side_packet"
+    )";
+    runner_ = absl::make_unique<CalculatorRunner>(kConfig);
+  }
+
+  std::unique_ptr<CalculatorRunner> runner_;
+};
+
+TEST_F(StreamToSidePacketCalculatorTest,
+       StreamToSidePacketCalculatorWithEmptyStreamFails) {
+  EXPECT_EQ(runner_->Run().code(), mediapipe::StatusCode::kUnavailable);
+}
+
+TEST_F(StreamToSidePacketCalculatorTest,
+       StreamToSidePacketCalculatorWithSinglePacketCreatesSidePacket) {
+  runner_->MutableInputs()->Index(0).packets.push_back(
+      Adopt(new std::string("test")).At(Timestamp(1)));
+  MP_ASSERT_OK(runner_->Run());
+  EXPECT_EQ(runner_->OutputSidePackets().Index(0).Get<std::string>(), "test");
+}
+
+TEST_F(StreamToSidePacketCalculatorTest,
+       StreamToSidePacketCalculatorWithMultiplePacketsFails) {
+  runner_->MutableInputs()->Index(0).packets.push_back(
+      Adopt(new std::string("test1")).At(Timestamp(1)));
+  runner_->MutableInputs()->Index(0).packets.push_back(
+      Adopt(new std::string("test2")).At(Timestamp(2)));
+  EXPECT_EQ(runner_->Run().code(), mediapipe::StatusCode::kAlreadyExists);
+}
+
+}  // namespace mediapipe
@@ -0,0 +1,79 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <sys/types.h>
+
+#include <memory>
+#include <string>
+
+#include "absl/strings/numbers.h"
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/port/integral_types.h"
+#include "mediapipe/framework/port/status.h"
+
+namespace mediapipe {
+
+// Calculator that converts a std::string into an integer type, or fails if the
+// conversion is not possible.
+//
+// Example config:
+// node {
+//   calculator: "StringToIntCalculator"
+//   input_side_packet: "string"
+//   output_side_packet: "index"
+// }
+template <typename IntType>
+class StringToIntCalculatorTemplate : public CalculatorBase {
+ public:
+  static ::mediapipe::Status GetContract(CalculatorContract* cc) {
+    cc->InputSidePackets().Index(0).Set<std::string>();
+    cc->OutputSidePackets().Index(0).Set<IntType>();
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Open(CalculatorContext* cc) override {
+    IntType number;
+    if (!absl::SimpleAtoi(cc->InputSidePackets().Index(0).Get<std::string>(),
+                          &number)) {
+      return ::mediapipe::InvalidArgumentError(
+          "The std::string could not be parsed as an integer.");
+    }
+    cc->OutputSidePackets().Index(0).Set(MakePacket<IntType>(number));
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Process(CalculatorContext* cc) override {
+    return ::mediapipe::OkStatus();
+  }
+};
+
+using StringToIntCalculator = StringToIntCalculatorTemplate<int>;
+REGISTER_CALCULATOR(StringToIntCalculator);
+
+using StringToUintCalculator = StringToIntCalculatorTemplate<uint>;
+REGISTER_CALCULATOR(StringToUintCalculator);
+
+using StringToInt32Calculator = StringToIntCalculatorTemplate<int32>;
+REGISTER_CALCULATOR(StringToInt32Calculator);
+
+using StringToUint32Calculator = StringToIntCalculatorTemplate<uint32>;
+REGISTER_CALCULATOR(StringToUint32Calculator);
+
+using StringToInt64Calculator = StringToIntCalculatorTemplate<int64>;
+REGISTER_CALCULATOR(StringToInt64Calculator);
+
+using StringToUint64Calculator = StringToIntCalculatorTemplate<uint64>;
+REGISTER_CALCULATOR(StringToUint64Calculator);
+
+}  // namespace mediapipe
@@ -12,14 +12,14 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.

+load("//mediapipe/framework/port:build_config.bzl", "mediapipe_cc_proto_library")
+
 licenses(["notice"])  # Apache 2.0

 package(default_visibility = ["//visibility:private"])

 exports_files(["LICENSE"])

-load("//mediapipe/framework/port:build_config.bzl", "mediapipe_cc_proto_library")
-
 proto_library(
    name = "opencv_image_encoder_calculator_proto",
    srcs = ["opencv_image_encoder_calculator.proto"],
@@ -80,10 +80,20 @@ mediapipe_cc_proto_library(
    name = "opencv_image_encoder_calculator_cc_proto",
    srcs = ["opencv_image_encoder_calculator.proto"],
    cc_deps = ["//mediapipe/framework:calculator_cc_proto"],
-    visibility = ["//visibility:public"],
+    visibility = [
+        "//visibility:public",
+    ],
    deps = [":opencv_image_encoder_calculator_proto"],
 )

+mediapipe_cc_proto_library(
+    name = "opencv_encoded_image_to_image_frame_calculator_cc_proto",
+    srcs = ["opencv_encoded_image_to_image_frame_calculator.proto"],
+    cc_deps = ["//mediapipe/framework:calculator_cc_proto"],
+    visibility = ["//visibility:public"],
+    deps = [":opencv_encoded_image_to_image_frame_calculator_proto"],
+)
+
 mediapipe_cc_proto_library(
    name = "mask_overlay_calculator_cc_proto",
    srcs = ["mask_overlay_calculator.proto"],
@@ -170,6 +180,7 @@ cc_library(
    srcs = ["opencv_encoded_image_to_image_frame_calculator.cc"],
    visibility = ["//visibility:public"],
    deps = [
+        ":opencv_encoded_image_to_image_frame_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/formats:image_frame_opencv",
        "//mediapipe/framework/port:opencv_imgcodecs",
@@ -330,6 +341,7 @@ cc_library(
 cc_library(
    name = "image_cropping_calculator",
    srcs = ["image_cropping_calculator.cc"],
+    hdrs = ["image_cropping_calculator.h"],
    copts = select({
        "//mediapipe:apple": [
            "-x objective-c++",
@@ -343,9 +355,7 @@ cc_library(
        ],
        "//conditions:default": [],
    }),
-    visibility = [
-        "//visibility:public",
-    ],
+    visibility = ["//visibility:public"],
    deps = [
        ":image_cropping_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
@@ -356,19 +366,35 @@ cc_library(
        "//mediapipe/framework/port:opencv_imgproc",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
-        "//mediapipe/gpu:gpu_buffer",
    ] + select({
        "//mediapipe/gpu:disable_gpu": [],
        "//conditions:default": [
            "//mediapipe/gpu:gl_calculator_helper",
            "//mediapipe/gpu:gl_simple_shaders",
            "//mediapipe/gpu:gl_quad_renderer",
+            "//mediapipe/gpu:gpu_buffer",
            "//mediapipe/gpu:shader_util",
        ],
    }),
    alwayslink = 1,
 )

+cc_test(
+    name = "image_cropping_calculator_test",
+    srcs = ["image_cropping_calculator_test.cc"],
+    deps = [
+        ":image_cropping_calculator",
+        ":image_cropping_calculator_cc_proto",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/formats:rect_cc_proto",
+        "//mediapipe/framework/port:gtest_main",
+        "//mediapipe/framework/port:parse_text_proto",
+        "//mediapipe/framework/port:status",
+        "//mediapipe/framework/tool:tag_map",
+        "//mediapipe/framework/tool:tag_map_helper",
+    ],
+)
+
 cc_library(
    name = "luminance_calculator",
    srcs = ["luminance_calculator.cc"],
@@ -405,9 +431,12 @@ cc_library(
        ":recolor_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/formats:image_frame",
+        "//mediapipe/framework/formats:image_frame_opencv",
        "//mediapipe/framework/port:status",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/util:color_cc_proto",
+        "//mediapipe/framework/port:opencv_core",
+        "//mediapipe/framework/port:opencv_imgproc",
    ] + select({
        "//mediapipe/gpu:disable_gpu": [],
        "//conditions:default": [
@@ -537,6 +566,27 @@ proto_library(
    deps = ["//mediapipe/framework:calculator_proto"],
 )

+proto_library(
+    name = "opencv_encoded_image_to_image_frame_calculator_proto",
+    srcs = ["opencv_encoded_image_to_image_frame_calculator.proto"],
+    visibility = ["//visibility:public"],
+    deps = ["//mediapipe/framework:calculator_proto"],
+)
+
+proto_library(
+    name = "feature_detector_calculator_proto",
+    srcs = ["feature_detector_calculator.proto"],
+    deps = ["//mediapipe/framework:calculator_proto"],
+)
+
+mediapipe_cc_proto_library(
+    name = "feature_detector_calculator_cc_proto",
+    srcs = ["feature_detector_calculator.proto"],
+    cc_deps = ["//mediapipe/framework:calculator_cc_proto"],
+    visibility = ["//visibility:public"],
+    deps = [":feature_detector_calculator_proto"],
+)
+
 cc_library(
    name = "mask_overlay_calculator",
    srcs = ["mask_overlay_calculator.cc"],
@@ -552,3 +602,30 @@ cc_library(
    ],
    alwayslink = 1,
 )
+
+cc_library(
+    name = "feature_detector_calculator",
+    srcs = ["feature_detector_calculator.cc"],
+    visibility = ["//mediapipe:__subpackages__"],
+    deps = [
+        ":feature_detector_calculator_cc_proto",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/formats:image_frame",
+        "//mediapipe/framework/formats:image_frame_opencv",
+        "//mediapipe/framework/formats:landmark_cc_proto",
+        "//mediapipe/framework/formats:video_stream_header",
+        "//mediapipe/framework/port:integral_types",
+        "//mediapipe/framework/port:logging",
+        "//mediapipe/framework/port:opencv_core",
+        "//mediapipe/framework/port:opencv_features2d",
+        "//mediapipe/framework/port:opencv_imgproc",
+        "//mediapipe/framework/port:ret_check",
+        "//mediapipe/framework/port:status",
+        "//mediapipe/framework/port:threadpool",
+        "//mediapipe/framework/tool:options_util",
+        "@com_google_absl//absl/memory",
+        "@com_google_absl//absl/synchronization",
+        "@org_tensorflow//tensorflow/lite:framework",
+    ],
+    alwayslink = 1,
+)
@@ -75,6 +75,11 @@ class ColorConvertCalculator : public CalculatorBase {
  static ::mediapipe::Status GetContract(CalculatorContract* cc);
  ::mediapipe::Status Process(CalculatorContext* cc) override;

+  ::mediapipe::Status Open(CalculatorContext* cc) override {
+    cc->SetOffset(TimestampDiff(0));
+    return ::mediapipe::OkStatus();
+  }
+
 private:
  // Wrangles the appropriate inputs and outputs to perform the color
  // conversion. The ImageFrame on input_tag is converted using the
@@ -0,0 +1,210 @@
+// Copyright 2020 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <memory>
+#include <vector>
+
+#include "absl/memory/memory.h"
+#include "absl/synchronization/blocking_counter.h"
+#include "mediapipe/calculators/image/feature_detector_calculator.pb.h"
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/formats/image_frame.h"
+#include "mediapipe/framework/formats/image_frame_opencv.h"
+#include "mediapipe/framework/formats/landmark.pb.h"
+#include "mediapipe/framework/formats/video_stream_header.h"
+#include "mediapipe/framework/port/integral_types.h"
+#include "mediapipe/framework/port/logging.h"
+#include "mediapipe/framework/port/opencv_core_inc.h"
+#include "mediapipe/framework/port/opencv_features2d_inc.h"
+#include "mediapipe/framework/port/opencv_imgproc_inc.h"
+#include "mediapipe/framework/port/ret_check.h"
+#include "mediapipe/framework/port/status.h"
+#include "mediapipe/framework/port/threadpool.h"
+#include "mediapipe/framework/tool/options_util.h"
+#include "tensorflow/lite/interpreter.h"
+
+namespace mediapipe {
+
+const char kOptionsTag[] = "OPTIONS";
+const int kPatchSize = 32;
+const int kNumThreads = 16;
+
+// A calculator to apply local feature detection.
+// Input stream:
+//   IMAGE: Input image frame of type ImageFrame from video stream.
+// Output streams:
+//   FEATURES: The detected keypoints from input image as vector<cv::KeyPoint>.
+//   PATCHES:  Optional output the extracted patches as vector<cv::Mat>
+class FeatureDetectorCalculator : public CalculatorBase {
+ public:
+  ~FeatureDetectorCalculator() override = default;
+
+  static ::mediapipe::Status GetContract(CalculatorContract* cc);
+
+  ::mediapipe::Status Open(CalculatorContext* cc) override;
+  ::mediapipe::Status Process(CalculatorContext* cc) override;
+
+ private:
+  FeatureDetectorCalculatorOptions options_;
+  cv::Ptr<cv::Feature2D> feature_detector_;
+  std::unique_ptr<::mediapipe::ThreadPool> pool_;
+
+  // Create image pyramid based on input image.
+  void ComputeImagePyramid(const cv::Mat& input_image,
+                           std::vector<cv::Mat>* image_pyramid);
+
+  // Extract the patch for single feature with image pyramid.
+  cv::Mat ExtractPatch(const cv::KeyPoint& feature,
+                       const std::vector<cv::Mat>& image_pyramid);
+};
+
+REGISTER_CALCULATOR(FeatureDetectorCalculator);
+
+::mediapipe::Status FeatureDetectorCalculator::GetContract(
+    CalculatorContract* cc) {
+  if (cc->Inputs().HasTag("IMAGE")) {
+    cc->Inputs().Tag("IMAGE").Set<ImageFrame>();
+  }
+  if (cc->Outputs().HasTag("FEATURES")) {
+    cc->Outputs().Tag("FEATURES").Set<std::vector<cv::KeyPoint>>();
+  }
+  if (cc->Outputs().HasTag("LANDMARKS")) {
+    cc->Outputs().Tag("LANDMARKS").Set<NormalizedLandmarkList>();
+  }
+  if (cc->Outputs().HasTag("PATCHES")) {
+    cc->Outputs().Tag("PATCHES").Set<std::vector<TfLiteTensor>>();
+  }
+  return ::mediapipe::OkStatus();
+}
+
+::mediapipe::Status FeatureDetectorCalculator::Open(CalculatorContext* cc) {
+  options_ =
+      tool::RetrieveOptions(cc->Options(), cc->InputSidePackets(), kOptionsTag)
+          .GetExtension(FeatureDetectorCalculatorOptions::ext);
+  feature_detector_ = cv::ORB::create(
+      options_.max_features(), options_.scale_factor(),
+      options_.pyramid_level(), kPatchSize - 1, 0, 2, cv::ORB::FAST_SCORE);
+  pool_ = absl::make_unique<::mediapipe::ThreadPool>("ThreadPool", kNumThreads);
+  pool_->StartWorkers();
+  return ::mediapipe::OkStatus();
+}
+
+::mediapipe::Status FeatureDetectorCalculator::Process(CalculatorContext* cc) {
+  const Timestamp& timestamp = cc->InputTimestamp();
+  if (timestamp == Timestamp::PreStream()) {
+    // Indicator packet.
+    return ::mediapipe::OkStatus();
+  }
+  InputStream* input_frame = &(cc->Inputs().Tag("IMAGE"));
+  cv::Mat input_view = formats::MatView(&input_frame->Get<ImageFrame>());
+  cv::Mat grayscale_view;
+  cv::cvtColor(input_view, grayscale_view, cv::COLOR_RGB2GRAY);
+
+  std::vector<cv::KeyPoint> keypoints;
+  feature_detector_->detect(grayscale_view, keypoints);
+  if (keypoints.size() > options_.max_features()) {
+    keypoints.resize(options_.max_features());
+  }
+
+  if (cc->Outputs().HasTag("FEATURES")) {
+    auto features_ptr = absl::make_unique<std::vector<cv::KeyPoint>>(keypoints);
+    cc->Outputs().Tag("FEATURES").Add(features_ptr.release(), timestamp);
+  }
+
+  if (cc->Outputs().HasTag("LANDMARKS")) {
+    auto landmarks_ptr = absl::make_unique<NormalizedLandmarkList>();
+    for (int j = 0; j < keypoints.size(); ++j) {
+      auto feature_landmark = landmarks_ptr->add_landmark();
+      feature_landmark->set_x(keypoints[j].pt.x / grayscale_view.cols);
+      feature_landmark->set_y(keypoints[j].pt.y / grayscale_view.rows);
+    }
+    cc->Outputs().Tag("LANDMARKS").Add(landmarks_ptr.release(), timestamp);
+  }
+
+  if (cc->Outputs().HasTag("PATCHES")) {
+    std::vector<cv::Mat> image_pyramid;
+    ComputeImagePyramid(grayscale_view, &image_pyramid);
+    std::vector<cv::Mat> patch_mat;
+    patch_mat.resize(keypoints.size());
+    absl::BlockingCounter counter(keypoints.size());
+    for (int i = 0; i < keypoints.size(); i++) {
+      pool_->Schedule(
+          [this, &image_pyramid, &keypoints, &patch_mat, i, &counter] {
+            patch_mat[i] = ExtractPatch(keypoints[i], image_pyramid);
+            counter.DecrementCount();
+          });
+    }
+    counter.Wait();
+    const int batch_size = options_.max_features();
+    auto patches = absl::make_unique<std::vector<TfLiteTensor>>();
+    TfLiteTensor tensor;
+    tensor.type = kTfLiteFloat32;
+    tensor.dims = TfLiteIntArrayCreate(4);
+    tensor.dims->data[0] = batch_size;
+    tensor.dims->data[1] = kPatchSize;
+    tensor.dims->data[2] = kPatchSize;
+    tensor.dims->data[3] = 1;
+    int num_bytes = batch_size * kPatchSize * kPatchSize * sizeof(float);
+    tensor.data.data = malloc(num_bytes);
+    tensor.bytes = num_bytes;
+    tensor.allocation_type = kTfLiteArenaRw;
+    float* tensor_buffer = tensor.data.f;
+    for (int i = 0; i < keypoints.size(); i++) {
+      for (int j = 0; j < patch_mat[i].rows; ++j) {
+        for (int k = 0; k < patch_mat[i].cols; ++k) {
+          *tensor_buffer++ = patch_mat[i].at<uchar>(j, k) / 128.0f - 1.0f;
+        }
+      }
+    }
+    for (int i = keypoints.size() * kPatchSize * kPatchSize; i < num_bytes / 4;
+         i++) {
+      *tensor_buffer++ = 0;
+    }
+
+    patches->emplace_back(tensor);
+    cc->Outputs().Tag("PATCHES").Add(patches.release(), timestamp);
+  }
+
+  return ::mediapipe::OkStatus();
+}
+
+void FeatureDetectorCalculator::ComputeImagePyramid(
+    const cv::Mat& input_image, std::vector<cv::Mat>* image_pyramid) {
+  cv::Mat tmp_image = input_image;
+  cv::Mat src_image = input_image;
+  for (int i = 0; i < options_.pyramid_level(); ++i) {
+    image_pyramid->push_back(src_image);
+    cv::resize(src_image, tmp_image, cv::Size(), 1.0f / options_.scale_factor(),
+               1.0f / options_.scale_factor());
+    src_image = tmp_image;
+  }
+}
+
+cv::Mat FeatureDetectorCalculator::ExtractPatch(
+    const cv::KeyPoint& feature, const std::vector<cv::Mat>& image_pyramid) {
+  cv::Mat img = image_pyramid[feature.octave];
+  float scale_factor = 1 / pow(options_.scale_factor(), feature.octave);
+  cv::Point2f center =
+      cv::Point2f(feature.pt.x * scale_factor, feature.pt.y * scale_factor);
+  cv::Mat rot = cv::getRotationMatrix2D(center, feature.angle, 1.0);
+  rot.at<double>(0, 2) += kPatchSize / 2 - center.x;
+  rot.at<double>(1, 2) += kPatchSize / 2 - center.y;
+  cv::Mat cropped_img;
+  // perform the affine transformation
+  cv::warpAffine(img, cropped_img, rot, cv::Size(kPatchSize, kPatchSize),
+                 cv::INTER_LINEAR);
+  return cropped_img;
+}
+
+}  // namespace mediapipe
@@ -0,0 +1,24 @@
+// Options for FeatureDetectorCalculator
+syntax = "proto2";
+
+package mediapipe;
+
+import "mediapipe/framework/calculator.proto";
+
+message FeatureDetectorCalculatorOptions {
+  extend CalculatorOptions {
+    optional FeatureDetectorCalculatorOptions ext = 278741680;
+  }
+
+  // Set to true if output patches, otherwise only output cv::KeyPoint
+  optional bool output_patch = 1;
+
+  // The max number of detected features.
+  optional int32 max_features = 2 [default = 200];
+
+  // The number of pyramid levels.
+  optional int32 pyramid_level = 3 [default = 4];
+
+  // Pyramid decimation ratio.
+  optional float scale_factor = 4 [default = 1.2];
+}
@@ -12,10 +12,10 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.

+#include "mediapipe/calculators/image/image_cropping_calculator.h"
+
 #include <cmath>

-#include "mediapipe/calculators/image/image_cropping_calculator.pb.h"
-#include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/formats/image_frame.h"
 #include "mediapipe/framework/formats/image_frame_opencv.h"
 #include "mediapipe/framework/formats/rect.pb.h"
@@ -25,7 +25,6 @@
 #include "mediapipe/framework/port/status.h"

 #if !defined(MEDIAPIPE_DISABLE_GPU)
-#include "mediapipe/gpu/gl_calculator_helper.h"
 #include "mediapipe/gpu/gl_simple_shaders.h"
 #include "mediapipe/gpu/gpu_buffer.h"
 #include "mediapipe/gpu/shader_util.h"
@@ -52,62 +51,6 @@ constexpr char kWidthTag[] = "WIDTH";

 }  // namespace

-// Crops the input texture to the given rectangle region. The rectangle can
-// be at arbitrary location on the image with rotation. If there's rotation, the
-// output texture will have the size of the input rectangle. The rotation should
-// be in radian, see rect.proto for detail.
-//
-// Input:
-//   One of the following two tags:
-//   IMAGE - ImageFrame representing the input image.
-//   IMAGE_GPU - GpuBuffer representing the input image.
-//   One of the following two tags (optional if WIDTH/HEIGHT is specified):
-//   RECT - A Rect proto specifying the width/height and location of the
-//          cropping rectangle.
-//   NORM_RECT - A NormalizedRect proto specifying the width/height and location
-//               of the cropping rectangle in normalized coordinates.
-//   Alternative tags to RECT (optional if RECT/NORM_RECT is specified):
-//   WIDTH - The desired width of the output cropped image,
-//           based on image center
-//   HEIGHT - The desired height of the output cropped image,
-//            based on image center
-//
-// Output:
-//   One of the following two tags:
-//   IMAGE - Cropped ImageFrame
-//   IMAGE_GPU - Cropped GpuBuffer.
-//
-// Note: input_stream values take precedence over options defined in the graph.
-//
-class ImageCroppingCalculator : public CalculatorBase {
- public:
-  ImageCroppingCalculator() = default;
-  ~ImageCroppingCalculator() override = default;
-
-  static ::mediapipe::Status GetContract(CalculatorContract* cc);
-  ::mediapipe::Status Open(CalculatorContext* cc) override;
-  ::mediapipe::Status Process(CalculatorContext* cc) override;
-  ::mediapipe::Status Close(CalculatorContext* cc) override;
-
- private:
-  ::mediapipe::Status RenderCpu(CalculatorContext* cc);
-  ::mediapipe::Status RenderGpu(CalculatorContext* cc);
-  ::mediapipe::Status InitGpu(CalculatorContext* cc);
-  void GlRender();
-  void GetOutputDimensions(CalculatorContext* cc, int src_width, int src_height,
-                           int* dst_width, int* dst_height);
-
-  mediapipe::ImageCroppingCalculatorOptions options_;
-
-  bool use_gpu_ = false;
-  // Output texture corners (4) after transoformation in normalized coordinates.
-  float transformed_points_[8];
-#if !defined(MEDIAPIPE_DISABLE_GPU)
-  bool gpu_initialized_ = false;
-  mediapipe::GlCalculatorHelper gpu_helper_;
-  GLuint program_ = 0;
-#endif  //  !MEDIAPIPE_DISABLE_GPU
-};
 REGISTER_CALCULATOR(ImageCroppingCalculator);

 ::mediapipe::Status ImageCroppingCalculator::GetContract(
@@ -132,7 +75,28 @@ REGISTER_CALCULATOR(ImageCroppingCalculator);
  }
 #endif  //  !MEDIAPIPE_DISABLE_GPU

-  RET_CHECK(cc->Inputs().HasTag(kRectTag) ^ cc->Inputs().HasTag(kNormRectTag));
+  int flags = 0;
+  if (cc->Inputs().HasTag(kRectTag)) {
+    ++flags;
+  }
+  if (cc->Inputs().HasTag(kWidthTag) && cc->Inputs().HasTag(kHeightTag)) {
+    ++flags;
+  }
+  if (cc->Inputs().HasTag(kNormRectTag)) {
+    ++flags;
+  }
+  if (cc->Options<mediapipe::ImageCroppingCalculatorOptions>()
+          .has_norm_width() &&
+      cc->Options<mediapipe::ImageCroppingCalculatorOptions>()
+          .has_norm_height()) {
+    ++flags;
+  }
+  if (cc->Options<mediapipe::ImageCroppingCalculatorOptions>().has_width() &&
+      cc->Options<mediapipe::ImageCroppingCalculatorOptions>().has_height()) {
+    ++flags;
+  }
+  RET_CHECK(flags == 1) << "Illegal combination of input streams/options.";
+
  if (cc->Inputs().HasTag(kRectTag)) {
    cc->Inputs().Tag(kRectTag).Set<Rect>();
  }
@@ -172,6 +136,13 @@ REGISTER_CALCULATOR(ImageCroppingCalculator);
 #endif  //  !MEDIAPIPE_DISABLE_GPU
  }

+  // Validate border mode.
+  if (use_gpu_) {
+    MP_RETURN_IF_ERROR(ValidateBorderModeForGPU(cc));
+  } else {
+    MP_RETURN_IF_ERROR(ValidateBorderModeForCPU(cc));
+  }
+
  return ::mediapipe::OkStatus();
 }

@@ -215,6 +186,32 @@ REGISTER_CALCULATOR(ImageCroppingCalculator);
  return ::mediapipe::OkStatus();
 }

+::mediapipe::Status ImageCroppingCalculator::ValidateBorderModeForCPU(
+    CalculatorContext* cc) {
+  int border_mode;
+  return GetBorderModeForOpenCV(cc, &border_mode);
+}
+
+::mediapipe::Status ImageCroppingCalculator::ValidateBorderModeForGPU(
+    CalculatorContext* cc) {
+  mediapipe::ImageCroppingCalculatorOptions options =
+      cc->Options<mediapipe::ImageCroppingCalculatorOptions>();
+
+  switch (options.border_mode()) {
+    case mediapipe::ImageCroppingCalculatorOptions::BORDER_ZERO:
+      LOG(WARNING) << "BORDER_ZERO mode is not supported by GPU "
+                   << "implementation and will fall back into BORDER_REPLICATE";
+      break;
+    case mediapipe::ImageCroppingCalculatorOptions::BORDER_REPLICATE:
+      break;
+    default:
+      RET_CHECK_FAIL() << "Unsupported border mode for GPU: "
+                       << options.border_mode();
+  }
+
+  return ::mediapipe::OkStatus();
+}
+
 ::mediapipe::Status ImageCroppingCalculator::RenderCpu(CalculatorContext* cc) {
  if (cc->Inputs().Tag(kImageTag).IsEmpty()) {
    return ::mediapipe::OkStatus();
@@ -222,41 +219,14 @@ REGISTER_CALCULATOR(ImageCroppingCalculator);
  const auto& input_img = cc->Inputs().Tag(kImageTag).Get<ImageFrame>();
  cv::Mat input_mat = formats::MatView(&input_img);

-  float rect_center_x = input_img.Width() / 2.0f;
-  float rect_center_y = input_img.Height() / 2.0f;
-  float rotation = 0.0f;
-  int target_width = input_img.Width();
-  int target_height = input_img.Height();
-  if (cc->Inputs().HasTag(kRectTag)) {
-    const auto& rect = cc->Inputs().Tag(kRectTag).Get<Rect>();
-    if (rect.width() > 0 && rect.height() > 0 && rect.x_center() >= 0 &&
-        rect.y_center() >= 0) {
-      rect_center_x = rect.x_center();
-      rect_center_y = rect.y_center();
-      target_width = rect.width();
-      target_height = rect.height();
-      rotation = rect.rotation();
-    }
-  } else if (cc->Inputs().HasTag(kNormRectTag)) {
-    const auto& rect = cc->Inputs().Tag(kNormRectTag).Get<NormalizedRect>();
-    if (rect.width() > 0.0 && rect.height() > 0.0 && rect.x_center() >= 0.0 &&
-        rect.y_center() >= 0.0) {
-      rect_center_x = std::round(rect.x_center() * input_img.Width());
-      rect_center_y = std::round(rect.y_center() * input_img.Height());
-      target_width = std::round(rect.width() * input_img.Width());
-      target_height = std::round(rect.height() * input_img.Height());
-      rotation = rect.rotation();
-    }
-  } else {
-    if (cc->Inputs().HasTag(kWidthTag) && cc->Inputs().HasTag(kHeightTag)) {
-      target_width = cc->Inputs().Tag(kWidthTag).Get<int>();
-      target_height = cc->Inputs().Tag(kHeightTag).Get<int>();
-    } else if (options_.has_width() && options_.has_height()) {
-      target_width = options_.width();
-      target_height = options_.height();
-    }
-    rotation = options_.rotation();
-  }
+  RectSpec specs = GetCropSpecs(cc, input_img.Width(), input_img.Height());
+  int target_width = specs.width, target_height = specs.height,
+      rect_center_x = specs.center_x, rect_center_y = specs.center_y;
+  float rotation = specs.rotation;
+
+  // Get border mode and value for OpenCV.
+  int border_mode;
+  MP_RETURN_IF_ERROR(GetBorderModeForOpenCV(cc, &border_mode));

  const cv::RotatedRect min_rect(cv::Point2f(rect_center_x, rect_center_y),
                                 cv::Size2f(target_width, target_height),
@@ -277,7 +247,9 @@ REGISTER_CALCULATOR(ImageCroppingCalculator);
      cv::getPerspectiveTransform(src_points, dst_points);
  cv::Mat cropped_image;
  cv::warpPerspective(input_mat, cropped_image, projection_matrix,
-                      cv::Size(min_rect.size.width, min_rect.size.height));
+                      cv::Size(min_rect.size.width, min_rect.size.height),
+                      /* flags = */ 0,
+                      /* borderMode = */ border_mode);

  std::unique_ptr<ImageFrame> output_frame(new ImageFrame(
      input_img.Format(), cropped_image.cols, cropped_image.rows));
@@ -433,46 +405,10 @@ void ImageCroppingCalculator::GetOutputDimensions(CalculatorContext* cc,
                                                  int src_width, int src_height,
                                                  int* dst_width,
                                                  int* dst_height) {
-  // Get the size of the cropping box.
-  int crop_width = src_width;
-  int crop_height = src_height;
-  // Get the center of cropping box. Default is the at the center.
-  int x_center = src_width / 2;
-  int y_center = src_height / 2;
-  // Get the rotation of the cropping box.
-  float rotation = 0.0f;
-  if (cc->Inputs().HasTag(kRectTag)) {
-    const auto& rect = cc->Inputs().Tag(kRectTag).Get<Rect>();
-    // Only use the rect if it is valid.
-    if (rect.width() > 0 && rect.height() > 0 && rect.x_center() >= 0 &&
-        rect.y_center() >= 0) {
-      x_center = rect.x_center();
-      y_center = rect.y_center();
-      crop_width = rect.width();
-      crop_height = rect.height();
-      rotation = rect.rotation();
-    }
-  } else if (cc->Inputs().HasTag(kNormRectTag)) {
-    const auto& rect = cc->Inputs().Tag(kNormRectTag).Get<NormalizedRect>();
-    // Only use the rect if it is valid.
-    if (rect.width() > 0.0 && rect.height() > 0.0 && rect.x_center() >= 0.0 &&
-        rect.y_center() >= 0.0) {
-      x_center = std::round(rect.x_center() * src_width);
-      y_center = std::round(rect.y_center() * src_height);
-      crop_width = std::round(rect.width() * src_width);
-      crop_height = std::round(rect.height() * src_height);
-      rotation = rect.rotation();
-    }
-  } else {
-    if (cc->Inputs().HasTag(kWidthTag) && cc->Inputs().HasTag(kHeightTag)) {
-      crop_width = cc->Inputs().Tag(kWidthTag).Get<int>();
-      crop_height = cc->Inputs().Tag(kHeightTag).Get<int>();
-    } else if (options_.has_width() && options_.has_height()) {
-      crop_width = options_.width();
-      crop_height = options_.height();
-    }
-    rotation = options_.rotation();
-  }
+  RectSpec specs = GetCropSpecs(cc, src_width, src_height);
+  int crop_width = specs.width, crop_height = specs.height,
+      x_center = specs.center_x, y_center = specs.center_y;
+  float rotation = specs.rotation;

  const float half_width = crop_width / 2.0f;
  const float half_height = crop_height / 2.0f;
@@ -501,8 +437,110 @@ void ImageCroppingCalculator::GetOutputDimensions(CalculatorContext* cc,
    row_max = std::max(row_max, transformed_points_[i * 2 + 1]);
  }

-  *dst_width = std::round((col_max - col_min) * src_width);
-  *dst_height = std::round((row_max - row_min) * src_height);
+  int width = static_cast<int>(std::round((col_max - col_min) * src_width));
+  int height = static_cast<int>(std::round((row_max - row_min) * src_height));
+  // Minimum output dimension 1x1 prevents creation of textures with 0x0.
+  *dst_width = std::max(1, width);
+  *dst_height = std::max(1, height);
+}
+
+RectSpec ImageCroppingCalculator::GetCropSpecs(const CalculatorContext* cc,
+                                               int src_width, int src_height) {
+  // Get the size of the cropping box.
+  int crop_width = src_width;
+  int crop_height = src_height;
+  // Get the center of cropping box. Default is the at the center.
+  int x_center = src_width / 2;
+  int y_center = src_height / 2;
+  // Get the rotation of the cropping box.
+  float rotation = 0.0f;
+  // Get the normalized width and height if specified by the inputs or options.
+  float normalized_width = 0.0f;
+  float normalized_height = 0.0f;
+
+  mediapipe::ImageCroppingCalculatorOptions options =
+      cc->Options<mediapipe::ImageCroppingCalculatorOptions>();
+
+  // width/height, norm_width/norm_height from input streams take precednece.
+  if (cc->Inputs().HasTag(kRectTag)) {
+    const auto& rect = cc->Inputs().Tag(kRectTag).Get<Rect>();
+    // Only use the rect if it is valid.
+    if (rect.width() > 0 && rect.height() > 0 && rect.x_center() >= 0 &&
+        rect.y_center() >= 0) {
+      x_center = rect.x_center();
+      y_center = rect.y_center();
+      crop_width = rect.width();
+      crop_height = rect.height();
+      rotation = rect.rotation();
+    }
+  } else if (cc->Inputs().HasTag(kNormRectTag)) {
+    const auto& norm_rect =
+        cc->Inputs().Tag(kNormRectTag).Get<NormalizedRect>();
+    if (norm_rect.width() > 0.0 && norm_rect.height() > 0.0) {
+      normalized_width = norm_rect.width();
+      normalized_height = norm_rect.height();
+      x_center = std::round(norm_rect.x_center() * src_width);
+      y_center = std::round(norm_rect.y_center() * src_height);
+      rotation = norm_rect.rotation();
+    }
+  } else if (cc->Inputs().HasTag(kWidthTag) &&
+             cc->Inputs().HasTag(kHeightTag)) {
+    crop_width = cc->Inputs().Tag(kWidthTag).Get<int>();
+    crop_height = cc->Inputs().Tag(kHeightTag).Get<int>();
+  } else if (options.has_width() && options.has_height()) {
+    crop_width = options.width();
+    crop_height = options.height();
+  } else if (options.has_norm_width() && options.has_norm_height()) {
+    normalized_width = options.norm_width();
+    normalized_height = options.norm_height();
+  }
+
+  // Get the crop width and height from the normalized width and height.
+  if (normalized_width > 0 && normalized_height > 0) {
+    crop_width = std::round(normalized_width * src_width);
+    crop_height = std::round(normalized_height * src_height);
+  }
+
+  // Rotation and center values from input streams take precedence, so only
+  // look at those values in the options if kRectTag and kNormRectTag are not
+  // present from the inputs.
+  if (!cc->Inputs().HasTag(kRectTag) && !cc->Inputs().HasTag(kNormRectTag)) {
+    if (options.has_norm_center_x() && options.has_norm_center_y()) {
+      x_center = std::round(options.norm_center_x() * src_width);
+      y_center = std::round(options.norm_center_y() * src_height);
+    }
+    if (options.has_rotation()) {
+      rotation = options.rotation();
+    }
+  }
+
+  return {
+      .width = crop_width,
+      .height = crop_height,
+      .center_x = x_center,
+      .center_y = y_center,
+      .rotation = rotation,
+  };
+}
+
+::mediapipe::Status ImageCroppingCalculator::GetBorderModeForOpenCV(
+    CalculatorContext* cc, int* border_mode) {
+  mediapipe::ImageCroppingCalculatorOptions options =
+      cc->Options<mediapipe::ImageCroppingCalculatorOptions>();
+
+  switch (options.border_mode()) {
+    case mediapipe::ImageCroppingCalculatorOptions::BORDER_ZERO:
+      *border_mode = cv::BORDER_CONSTANT;
+      break;
+    case mediapipe::ImageCroppingCalculatorOptions::BORDER_REPLICATE:
+      *border_mode = cv::BORDER_REPLICATE;
+      break;
+    default:
+      RET_CHECK_FAIL() << "Unsupported border mode for CPU: "
+                       << options.border_mode();
+  }
+
+  return ::mediapipe::OkStatus();
 }

 }  // namespace mediapipe
@@ -0,0 +1,91 @@
+#ifndef MEDIAPIPE_CALCULATORS_IMAGE_IMAGE_CROPPING_CALCULATOR_H_
+#define MEDIAPIPE_CALCULATORS_IMAGE_IMAGE_CROPPING_CALCULATOR_H_
+
+#include "mediapipe/calculators/image/image_cropping_calculator.pb.h"
+#include "mediapipe/framework/calculator_framework.h"
+
+#if !defined(MEDIAPIPE_DISABLE_GPU)
+#include "mediapipe/gpu/gl_calculator_helper.h"
+#endif  //  !MEDIAPIPE_DISABLE_GPU
+
+// Crops the input texture to the given rectangle region. The rectangle can
+// be at arbitrary location on the image with rotation. If there's rotation, the
+// output texture will have the size of the input rectangle. The rotation should
+// be in radian, see rect.proto for detail.
+//
+// Input:
+//   One of the following two tags:
+//   IMAGE - ImageFrame representing the input image.
+//   IMAGE_GPU - GpuBuffer representing the input image.
+//   One of the following two tags (optional if WIDTH/HEIGHT is specified):
+//   RECT - A Rect proto specifying the width/height and location of the
+//          cropping rectangle.
+//   NORM_RECT - A NormalizedRect proto specifying the width/height and location
+//               of the cropping rectangle in normalized coordinates.
+//   Alternative tags to RECT (optional if RECT/NORM_RECT is specified):
+//   WIDTH - The desired width of the output cropped image,
+//           based on image center
+//   HEIGHT - The desired height of the output cropped image,
+//            based on image center
+//
+// Output:
+//   One of the following two tags:
+//   IMAGE - Cropped ImageFrame
+//   IMAGE_GPU - Cropped GpuBuffer.
+//
+// Note: input_stream values take precedence over options defined in the graph.
+//
+namespace mediapipe {
+
+struct RectSpec {
+  int width;
+  int height;
+  int center_x;
+  int center_y;
+  float rotation;
+
+  bool operator==(const RectSpec& rect) const {
+    return (width == rect.width && height == rect.height &&
+            center_x == rect.center_x && center_y == rect.center_y &&
+            rotation == rect.rotation);
+  }
+};
+
+class ImageCroppingCalculator : public CalculatorBase {
+ public:
+  ImageCroppingCalculator() = default;
+  ~ImageCroppingCalculator() override = default;
+
+  static ::mediapipe::Status GetContract(CalculatorContract* cc);
+  ::mediapipe::Status Open(CalculatorContext* cc) override;
+  ::mediapipe::Status Process(CalculatorContext* cc) override;
+  ::mediapipe::Status Close(CalculatorContext* cc) override;
+  static RectSpec GetCropSpecs(const CalculatorContext* cc, int src_width,
+                               int src_height);
+
+ private:
+  ::mediapipe::Status ValidateBorderModeForCPU(CalculatorContext* cc);
+  ::mediapipe::Status ValidateBorderModeForGPU(CalculatorContext* cc);
+  ::mediapipe::Status RenderCpu(CalculatorContext* cc);
+  ::mediapipe::Status RenderGpu(CalculatorContext* cc);
+  ::mediapipe::Status InitGpu(CalculatorContext* cc);
+  void GlRender();
+  void GetOutputDimensions(CalculatorContext* cc, int src_width, int src_height,
+                           int* dst_width, int* dst_height);
+  ::mediapipe::Status GetBorderModeForOpenCV(CalculatorContext* cc,
+                                             int* border_mode);
+
+  mediapipe::ImageCroppingCalculatorOptions options_;
+
+  bool use_gpu_ = false;
+  // Output texture corners (4) after transoformation in normalized coordinates.
+  float transformed_points_[8];
+#if !defined(MEDIAPIPE_DISABLE_GPU)
+  bool gpu_initialized_ = false;
+  mediapipe::GlCalculatorHelper gpu_helper_;
+  GLuint program_ = 0;
+#endif  //  !MEDIAPIPE_DISABLE_GPU
+};
+
+}  // namespace mediapipe
+#endif  // MEDIAPIPE_CALCULATORS_IMAGE_IMAGE_CROPPING_CALCULATOR_H_
@@ -30,4 +30,25 @@ message ImageCroppingCalculatorOptions {

  // Rotation angle is counter-clockwise in radian.
  optional float rotation = 3 [default = 0.0];
+
+  // Normalized width and height of the output rect. Value is within [0, 1].
+  optional float norm_width = 4;
+  optional float norm_height = 5;
+
+  // Normalized location of the center of the output
+  // rectangle in image coordinates. Value is within [0, 1].
+  // The (0, 0) point is at the (top, left) corner.
+  optional float norm_center_x = 6 [default = 0];
+  optional float norm_center_y = 7 [default = 0];
+
+  enum BorderMode {
+    // First unspecified value is required by the guideline. See details here:
+    // https://developers.google.com/protocol-buffers/docs/style#enums
+    BORDER_UNSPECIFIED = 0;
+    BORDER_ZERO = 1;
+    BORDER_REPLICATE = 2;
+  }
+
+  // Specifies behaviour for crops that go beyond image borders.
+  optional BorderMode border_mode = 8 [default = BORDER_ZERO];
 }
@@ -0,0 +1,216 @@
+// Copyright 2020 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "mediapipe/calculators/image/image_cropping_calculator.h"
+
+#include <cmath>
+#include <memory>
+
+#include "mediapipe/calculators/image/image_cropping_calculator.pb.h"
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/formats/rect.pb.h"
+#include "mediapipe/framework/port/gtest.h"
+#include "mediapipe/framework/port/parse_text_proto.h"
+#include "mediapipe/framework/port/status_matchers.h"
+#include "mediapipe/framework/tool/tag_map.h"
+#include "mediapipe/framework/tool/tag_map_helper.h"
+
+namespace mediapipe {
+
+namespace {
+
+constexpr int input_width = 100;
+constexpr int input_height = 100;
+
+constexpr char kRectTag[] = "RECT";
+constexpr char kHeightTag[] = "HEIGHT";
+constexpr char kWidthTag[] = "WIDTH";
+
+// Test normal case, where norm_width and norm_height in options are set.
+TEST(ImageCroppingCalculatorTest, GetCroppingDimensionsNormal) {
+  auto calculator_node =
+      ParseTextProtoOrDie<mediapipe::CalculatorGraphConfig::Node>(
+          R"(
+            calculator: "ImageCroppingCalculator"
+            input_stream: "IMAGE_GPU:input_frames"
+            output_stream: "IMAGE_GPU:cropped_output_frames"
+            options: {
+              [mediapipe.ImageCroppingCalculatorOptions.ext] {
+                norm_width: 0.6
+                norm_height: 0.6
+                norm_center_x: 0.5
+                norm_center_y: 0.5
+                rotation: 0.3
+              }
+            }
+          )");
+
+  auto calculator_state = absl::make_unique<CalculatorState>(
+      "Node", 0, "Calculator", calculator_node, nullptr);
+  auto cc = absl::make_unique<CalculatorContext>(
+      calculator_state.get(), tool::CreateTagMap({}).ValueOrDie(),
+      tool::CreateTagMap({}).ValueOrDie());
+
+  RectSpec expectRect = {
+      .width = 60,
+      .height = 60,
+      .center_x = 50,
+      .center_y = 50,
+      .rotation = 0.3,
+  };
+  EXPECT_EQ(ImageCroppingCalculator::GetCropSpecs(cc.get(), input_width,
+                                                  input_height),
+            expectRect);
+}  // TEST
+
+// Test when (width height) + (norm_width norm_height) are set in options.
+// width and height should take precedence.
+TEST(ImageCroppingCalculatorTest, RedundantSpecInOptions) {
+  auto calculator_node =
+      ParseTextProtoOrDie<mediapipe::CalculatorGraphConfig::Node>(
+          R"(
+            calculator: "ImageCroppingCalculator"
+            input_stream: "IMAGE_GPU:input_frames"
+            output_stream: "IMAGE_GPU:cropped_output_frames"
+            options: {
+              [mediapipe.ImageCroppingCalculatorOptions.ext] {
+                width: 50
+                height: 50
+                norm_width: 0.6
+                norm_height: 0.6
+                norm_center_x: 0.5
+                norm_center_y: 0.5
+                rotation: 0.3
+              }
+            }
+          )");
+
+  auto calculator_state = absl::make_unique<CalculatorState>(
+      "Node", 0, "Calculator", calculator_node, nullptr);
+  auto cc = absl::make_unique<CalculatorContext>(
+      calculator_state.get(), tool::CreateTagMap({}).ValueOrDie(),
+      tool::CreateTagMap({}).ValueOrDie());
+  RectSpec expectRect = {
+      .width = 50,
+      .height = 50,
+      .center_x = 50,
+      .center_y = 50,
+      .rotation = 0.3,
+  };
+  EXPECT_EQ(ImageCroppingCalculator::GetCropSpecs(cc.get(), input_width,
+                                                  input_height),
+            expectRect);
+}  // TEST
+
+// Test when WIDTH HEIGHT are set from input stream,
+// and options has norm_width/height set.
+// WIDTH HEIGHT from input stream should take precedence.
+TEST(ImageCroppingCalculatorTest, RedundantSpectWithInputStream) {
+  auto calculator_node =
+      ParseTextProtoOrDie<mediapipe::CalculatorGraphConfig::Node>(
+          R"(
+            calculator: "ImageCroppingCalculator"
+            input_stream: "IMAGE_GPU:input_frames"
+            input_stream: "WIDTH:crop_width"
+            input_stream: "HEIGHT:crop_height"
+            output_stream: "IMAGE_GPU:cropped_output_frames"
+            options: {
+              [mediapipe.ImageCroppingCalculatorOptions.ext] {
+                width: 50
+                height: 50
+                norm_width: 0.6
+                norm_height: 0.6
+                norm_center_x: 0.5
+                norm_center_y: 0.5
+                rotation: 0.3
+              }
+            }
+          )");
+
+  auto calculator_state = absl::make_unique<CalculatorState>(
+      "Node", 0, "Calculator", calculator_node, nullptr);
+  auto inputTags = tool::CreateTagMap({
+                                          "HEIGHT:0:crop_height",
+                                          "WIDTH:0:crop_width",
+                                      })
+                       .ValueOrDie();
+  auto cc = absl::make_unique<CalculatorContext>(
+      calculator_state.get(), inputTags, tool::CreateTagMap({}).ValueOrDie());
+  auto& inputs = cc->Inputs();
+  inputs.Tag(kHeightTag).Value() = MakePacket<int>(1);
+  inputs.Tag(kWidthTag).Value() = MakePacket<int>(1);
+  RectSpec expectRect = {
+      .width = 1,
+      .height = 1,
+      .center_x = 50,
+      .center_y = 50,
+      .rotation = 0.3,
+  };
+  EXPECT_EQ(ImageCroppingCalculator::GetCropSpecs(cc.get(), input_width,
+                                                  input_height),
+            expectRect);
+}  // TEST
+
+// Test when RECT is set from input stream,
+// and options has norm_width/height set.
+// RECT from input stream should take precedence.
+TEST(ImageCroppingCalculatorTest, RedundantSpecWithInputStream) {
+  auto calculator_node =
+      ParseTextProtoOrDie<mediapipe::CalculatorGraphConfig::Node>(
+          R"(
+            calculator: "ImageCroppingCalculator"
+            input_stream: "IMAGE_GPU:input_frames"
+            input_stream: "RECT:rect"
+            output_stream: "IMAGE_GPU:cropped_output_frames"
+            options: {
+              [mediapipe.ImageCroppingCalculatorOptions.ext] {
+                width: 50
+                height: 50
+                norm_width: 0.6
+                norm_height: 0.6
+                norm_center_x: 0.5
+                norm_center_y: 0.5
+                rotation: 0.3
+              }
+            }
+          )");
+
+  auto calculator_state = absl::make_unique<CalculatorState>(
+      "Node", 0, "Calculator", calculator_node, nullptr);
+  auto inputTags = tool::CreateTagMap({
+                                          "RECT:0:rect",
+                                      })
+                       .ValueOrDie();
+  auto cc = absl::make_unique<CalculatorContext>(
+      calculator_state.get(), inputTags, tool::CreateTagMap({}).ValueOrDie());
+  auto& inputs = cc->Inputs();
+  mediapipe::Rect rect = ParseTextProtoOrDie<mediapipe::Rect>(
+      R"(
+        width: 1 height: 1 x_center: 40 y_center: 40 rotation: 0.5
+      )");
+  inputs.Tag(kRectTag).Value() = MakePacket<mediapipe::Rect>(rect);
+  RectSpec expectRect = {
+      .width = 1,
+      .height = 1,
+      .center_x = 40,
+      .center_y = 40,
+      .rotation = 0.5,
+  };
+  EXPECT_EQ(ImageCroppingCalculator::GetCropSpecs(cc.get(), input_width,
+                                                  input_height),
+            expectRect);
+}  // TEST
+
+}  // namespace
+}  // namespace mediapipe
@@ -104,6 +104,14 @@ mediapipe::ScaleMode_Mode ParseScaleMode(
 //   to be a multiple of 90 degrees. If provided, it overrides the
 //   ROTATION_DEGREES input side packet.
 //
+//   FLIP_HORIZONTALLY (optional): Whether to flip image horizontally or not. If
+//   provided, it overrides the FLIP_HORIZONTALLY input side packet and/or
+//   corresponding field in the calculator options.
+//
+//   FLIP_VERTICALLY (optional): Whether to flip image vertically or not. If
+//   provided, it overrides the FLIP_VERTICALLY input side packet and/or
+//   corresponding field in the calculator options.
+//
 // Output:
 //   One of the following two tags:
 //   IMAGE - ImageFrame representing the output image.
@@ -129,6 +137,12 @@ mediapipe::ScaleMode_Mode ParseScaleMode(
 //   degrees. It has to be a multiple of 90 degrees. It overrides the
 //   corresponding field in the calculator options.
 //
+//   FLIP_HORIZONTALLY (optional): Whether to flip image horizontally or not.
+//   It overrides the corresponding field in the calculator options.
+//
+//   FLIP_VERTICALLY (optional): Whether to flip image vertically or not.
+//   It overrides the corresponding field in the calculator options.
+//
 // Calculator options (see image_transformation_calculator.proto):
 //   output_width, output_height - (optional) Desired scaled image size.
 //   rotation_mode - (optional) Rotation in multiples of 90 degrees.
@@ -138,8 +152,7 @@ mediapipe::ScaleMode_Mode ParseScaleMode(
 // Note: To enable horizontal or vertical flipping, specify them in the
 // calculator options. Flipping is applied after rotation.
 //
-// Note: Only scale mode STRETCH is currently supported on CPU,
-// and flipping is not yet supported either.
+// Note: Only scale mode STRETCH is currently supported on CPU.
 //
 class ImageTransformationCalculator : public CalculatorBase {
 public:
@@ -168,6 +181,8 @@ class ImageTransformationCalculator : public CalculatorBase {
  int output_height_ = 0;
  mediapipe::RotationMode_Mode rotation_;
  mediapipe::ScaleMode_Mode scale_mode_;
+  bool flip_horizontally_ = false;
+  bool flip_vertically_ = false;

  bool use_gpu_ = false;
 #if !defined(MEDIAPIPE_DISABLE_GPU)
@@ -204,6 +219,12 @@ REGISTER_CALCULATOR(ImageTransformationCalculator);
  if (cc->Inputs().HasTag("ROTATION_DEGREES")) {
    cc->Inputs().Tag("ROTATION_DEGREES").Set<int>();
  }
+  if (cc->Inputs().HasTag("FLIP_HORIZONTALLY")) {
+    cc->Inputs().Tag("FLIP_HORIZONTALLY").Set<bool>();
+  }
+  if (cc->Inputs().HasTag("FLIP_VERTICALLY")) {
+    cc->Inputs().Tag("FLIP_VERTICALLY").Set<bool>();
+  }

  if (cc->InputSidePackets().HasTag("OUTPUT_DIMENSIONS")) {
    cc->InputSidePackets().Tag("OUTPUT_DIMENSIONS").Set<DimensionsPacketType>();
@@ -211,6 +232,12 @@ REGISTER_CALCULATOR(ImageTransformationCalculator);
  if (cc->InputSidePackets().HasTag("ROTATION_DEGREES")) {
    cc->InputSidePackets().Tag("ROTATION_DEGREES").Set<int>();
  }
+  if (cc->InputSidePackets().HasTag("FLIP_HORIZONTALLY")) {
+    cc->InputSidePackets().Tag("FLIP_HORIZONTALLY").Set<bool>();
+  }
+  if (cc->InputSidePackets().HasTag("FLIP_VERTICALLY")) {
+    cc->InputSidePackets().Tag("FLIP_VERTICALLY").Set<bool>();
+  }

  if (cc->Outputs().HasTag("LETTERBOX_PADDING")) {
    cc->Outputs().Tag("LETTERBOX_PADDING").Set<std::array<float, 4>>();
@@ -246,6 +273,7 @@ REGISTER_CALCULATOR(ImageTransformationCalculator);
    output_width_ = options_.output_width();
    output_height_ = options_.output_height();
  }
+
  if (cc->InputSidePackets().HasTag("ROTATION_DEGREES")) {
    rotation_ = DegreesToRotationMode(
        cc->InputSidePackets().Tag("ROTATION_DEGREES").Get<int>());
@@ -253,6 +281,20 @@ REGISTER_CALCULATOR(ImageTransformationCalculator);
    rotation_ = options_.rotation_mode();
  }

+  if (cc->InputSidePackets().HasTag("FLIP_HORIZONTALLY")) {
+    flip_horizontally_ =
+        cc->InputSidePackets().Tag("FLIP_HORIZONTALLY").Get<bool>();
+  } else {
+    flip_horizontally_ = options_.flip_horizontally();
+  }
+
+  if (cc->InputSidePackets().HasTag("FLIP_VERTICALLY")) {
+    flip_vertically_ =
+        cc->InputSidePackets().Tag("FLIP_VERTICALLY").Get<bool>();
+  } else {
+    flip_vertically_ = options_.flip_vertically();
+  }
+
  scale_mode_ = ParseScaleMode(options_.scale_mode(), DEFAULT_SCALE_MODE);

  if (use_gpu_) {
@@ -269,12 +311,37 @@ REGISTER_CALCULATOR(ImageTransformationCalculator);

 ::mediapipe::Status ImageTransformationCalculator::Process(
    CalculatorContext* cc) {
+  // Override values if specified so.
+  if (cc->Inputs().HasTag("ROTATION_DEGREES") &&
+      !cc->Inputs().Tag("ROTATION_DEGREES").IsEmpty()) {
+    rotation_ =
+        DegreesToRotationMode(cc->Inputs().Tag("ROTATION_DEGREES").Get<int>());
+  }
+  if (cc->Inputs().HasTag("FLIP_HORIZONTALLY") &&
+      !cc->Inputs().Tag("FLIP_HORIZONTALLY").IsEmpty()) {
+    flip_horizontally_ = cc->Inputs().Tag("FLIP_HORIZONTALLY").Get<bool>();
+  }
+  if (cc->Inputs().HasTag("FLIP_VERTICALLY") &&
+      !cc->Inputs().Tag("FLIP_VERTICALLY").IsEmpty()) {
+    flip_vertically_ = cc->Inputs().Tag("FLIP_VERTICALLY").Get<bool>();
+  }
+
  if (use_gpu_) {
 #if !defined(MEDIAPIPE_DISABLE_GPU)
+    if (cc->Inputs().Tag("IMAGE_GPU").IsEmpty()) {
+      // Image is missing, hence no way to produce output image. (Timestamp
+      // bound will be updated automatically.)
+      return ::mediapipe::OkStatus();
+    }
    return helper_.RunInGlContext(
        [this, cc]() -> ::mediapipe::Status { return RenderGpu(cc); });
 #endif  //  !MEDIAPIPE_DISABLE_GPU
  } else {
+    if (cc->Inputs().Tag("IMAGE").IsEmpty()) {
+      // Image is missing, hence no way to produce output image. (Timestamp
+      // bound will be updated automatically.)
+      return ::mediapipe::OkStatus();
+    }
    return RenderCpu(cc);
  }
  return ::mediapipe::OkStatus();
@@ -316,6 +383,11 @@ REGISTER_CALCULATOR(ImageTransformationCalculator);
  cv::Mat input_mat = formats::MatView(&input_img);
  cv::Mat scaled_mat;

+  if (!output_height_ || !output_width_) {
+    output_height_ = input_height;
+    output_width_ = input_width;
+  }
+
  if (scale_mode_ == mediapipe::ScaleMode_Mode_STRETCH) {
    cv::resize(input_mat, scaled_mat, cv::Size(output_width_, output_height_));
  } else {
@@ -356,21 +428,25 @@ REGISTER_CALCULATOR(ImageTransformationCalculator);
        .Add(padding.release(), cc->InputTimestamp());
  }

-  if (cc->InputSidePackets().HasTag("ROTATION_DEGREES")) {
-    rotation_ = DegreesToRotationMode(
-        cc->InputSidePackets().Tag("ROTATION_DEGREES").Get<int>());
-  }
-
  cv::Mat rotated_mat;
  const int angle = RotationModeToDegrees(rotation_);
  cv::Point2f src_center(scaled_mat.cols / 2.0, scaled_mat.rows / 2.0);
  cv::Mat rotation_mat = cv::getRotationMatrix2D(src_center, angle, 1.0);
  cv::warpAffine(scaled_mat, rotated_mat, rotation_mat, scaled_mat.size());

+  cv::Mat flipped_mat;
+  if (flip_horizontally_ || flip_vertically_) {
+    const int flip_code =
+        flip_horizontally_ && flip_vertically_ ? -1 : flip_horizontally_;
+    cv::flip(rotated_mat, flipped_mat, flip_code);
+  } else {
+    flipped_mat = rotated_mat;
+  }
+
  std::unique_ptr<ImageFrame> output_frame(
      new ImageFrame(input_img.Format(), output_width, output_height));
  cv::Mat output_mat = formats::MatView(output_frame.get());
-  rotated_mat.copyTo(output_mat);
+  flipped_mat.copyTo(output_mat);
  cc->Outputs().Tag("IMAGE").Add(output_frame.release(), cc->InputTimestamp());

  return ::mediapipe::OkStatus();
@@ -400,7 +476,7 @@ REGISTER_CALCULATOR(ImageTransformationCalculator);
  QuadRenderer* renderer = nullptr;
  GlTexture src1;

-#if defined(__APPLE__) && !TARGET_OS_OSX
+#if defined(MEDIAPIPE_IOS)
  if (input.format() == GpuBufferFormat::kBiPlanar420YpCbCr8VideoRange ||
      input.format() == GpuBufferFormat::kBiPlanar420YpCbCr8FullRange) {
    if (!yuv_renderer_) {
@@ -435,14 +511,8 @@ REGISTER_CALCULATOR(ImageTransformationCalculator);
  }
  RET_CHECK(renderer) << "Unsupported input texture type";

-  if (cc->InputSidePackets().HasTag("ROTATION_DEGREES")) {
-    rotation_ = DegreesToRotationMode(
-        cc->InputSidePackets().Tag("ROTATION_DEGREES").Get<int>());
-  }
-
-  static mediapipe::FrameScaleMode scale_mode =
-      mediapipe::FrameScaleModeFromProto(scale_mode_,
-                                         mediapipe::FrameScaleMode::kStretch);
+  mediapipe::FrameScaleMode scale_mode = mediapipe::FrameScaleModeFromProto(
+      scale_mode_, mediapipe::FrameScaleMode::kStretch);
  mediapipe::FrameRotation rotation =
      mediapipe::FrameRotationFromDegrees(RotationModeToDegrees(rotation_));

@@ -455,7 +525,7 @@ REGISTER_CALCULATOR(ImageTransformationCalculator);

  MP_RETURN_IF_ERROR(renderer->GlRender(
      src1.width(), src1.height(), dst.width(), dst.height(), scale_mode,
-      rotation, options_.flip_horizontally(), options_.flip_vertically(),
+      rotation, flip_horizontally_, flip_vertically_,
      /*flip_texture=*/false));

  glActiveTexture(GL_TEXTURE1);
@@ -12,6 +12,7 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.

+#include "mediapipe/calculators/image/opencv_encoded_image_to_image_frame_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/formats/image_frame_opencv.h"
 #include "mediapipe/framework/port/opencv_imgcodecs_inc.h"
@@ -34,7 +35,11 @@ namespace mediapipe {
 class OpenCvEncodedImageToImageFrameCalculator : public CalculatorBase {
 public:
  static ::mediapipe::Status GetContract(CalculatorContract* cc);
+  ::mediapipe::Status Open(CalculatorContext* cc) override;
  ::mediapipe::Status Process(CalculatorContext* cc) override;
+
+ private:
+  mediapipe::OpenCvEncodedImageToImageFrameCalculatorOptions options_;
 };

 ::mediapipe::Status OpenCvEncodedImageToImageFrameCalculator::GetContract(
@@ -44,13 +49,29 @@ class OpenCvEncodedImageToImageFrameCalculator : public CalculatorBase {
  return ::mediapipe::OkStatus();
 }

+::mediapipe::Status OpenCvEncodedImageToImageFrameCalculator::Open(
+    CalculatorContext* cc) {
+  options_ =
+      cc->Options<mediapipe::OpenCvEncodedImageToImageFrameCalculatorOptions>();
+  return ::mediapipe::OkStatus();
+}
+
 ::mediapipe::Status OpenCvEncodedImageToImageFrameCalculator::Process(
    CalculatorContext* cc) {
  const std::string& contents = cc->Inputs().Index(0).Get<std::string>();
  const std::vector<char> contents_vector(contents.begin(), contents.end());
-  cv::Mat decoded_mat =
-      cv::imdecode(contents_vector, -1 /* return the loaded image as-is */);
-
+  cv::Mat decoded_mat;
+  if (options_.apply_orientation_from_exif_data()) {
+    // We want to respect the orientation from the EXIF data, which
+    // IMREAD_UNCHANGED ignores, but otherwise we want to be as permissive as
+    // possible with our reading flags. Therefore, we use IMREAD_ANYCOLOR and
+    // IMREAD_ANYDEPTH.
+    decoded_mat = cv::imdecode(contents_vector,
+                               cv::IMREAD_ANYCOLOR | cv::IMREAD_ANYDEPTH);
+  } else {
+    // Return the loaded image as-is
+    decoded_mat = cv::imdecode(contents_vector, cv::IMREAD_UNCHANGED);
+  }
  ImageFormat::Format image_format = ImageFormat::UNKNOWN;
  cv::Mat output_mat;
  switch (decoded_mat.channels()) {
@@ -70,7 +91,8 @@ class OpenCvEncodedImageToImageFrameCalculator : public CalculatorBase {
             << "Unsupported number of channels: " << decoded_mat.channels();
  }
  std::unique_ptr<ImageFrame> output_frame = absl::make_unique<ImageFrame>(
-      image_format, decoded_mat.size().width, decoded_mat.size().height);
+      image_format, decoded_mat.size().width, decoded_mat.size().height,
+      ImageFrame::kGlDefaultAlignmentBoundary);
  output_mat.copyTo(formats::MatView(output_frame.get()));
  cc->Outputs().Index(0).Add(output_frame.release(), cc->InputTimestamp());
  return ::mediapipe::OkStatus();
@@ -0,0 +1,30 @@
+// Copyright 2020 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+syntax = "proto2";
+
+package mediapipe;
+
+import "mediapipe/framework/calculator.proto";
+
+message OpenCvEncodedImageToImageFrameCalculatorOptions {
+  extend CalculatorOptions {
+    optional OpenCvEncodedImageToImageFrameCalculatorOptions ext = 303447308;
+  }
+
+  // If set, we will attempt to automatically apply the orientation specified by
+  // the image's EXIF data when loading the image. Otherwise, the image data
+  // will be loaded as-is.
+  optional bool apply_orientation_from_exif_data = 1 [default = false];
+}
@@ -17,6 +17,9 @@
 #include "mediapipe/calculators/image/recolor_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/formats/image_frame.h"
+#include "mediapipe/framework/formats/image_frame_opencv.h"
+#include "mediapipe/framework/port/opencv_core_inc.h"
+#include "mediapipe/framework/port/opencv_imgproc_inc.h"
 #include "mediapipe/framework/port/ret_check.h"
 #include "mediapipe/framework/port/status.h"
 #include "mediapipe/util/color.pb.h"
@@ -39,8 +42,6 @@ namespace mediapipe {
 // The luminance of the input image is used to adjust the blending weight,
 // to help preserve image textures.
 //
-// TODO implement cpu support.
-//
 // Inputs:
 //   One of the following IMAGE tags:
 //   IMAGE: An ImageFrame input image, RGB or RGBA.
@@ -71,6 +72,8 @@ namespace mediapipe {
 //    }
 //  }
 //
+// Note: Cannot mix-match CPU & GPU inputs/outputs.
+//       CPU-in & CPU-out <or> GPU-in & GPU-out
 class RecolorCalculator : public CalculatorBase {
 public:
  RecolorCalculator() = default;
@@ -138,6 +141,11 @@ REGISTER_CALCULATOR(RecolorCalculator);
    cc->Outputs().Tag("IMAGE").Set<ImageFrame>();
  }

+  // Confirm only one of the input streams is present.
+  RET_CHECK(cc->Inputs().HasTag("IMAGE") ^ cc->Inputs().HasTag("IMAGE_GPU"));
+  // Confirm only one of the output streams is present.
+  RET_CHECK(cc->Outputs().HasTag("IMAGE") ^ cc->Outputs().HasTag("IMAGE_GPU"));
+
  if (use_gpu) {
 #if !defined(MEDIAPIPE_DISABLE_GPU)
    MP_RETURN_IF_ERROR(mediapipe::GlCalculatorHelper::UpdateContract(cc));
@@ -193,7 +201,62 @@ REGISTER_CALCULATOR(RecolorCalculator);
 }

 ::mediapipe::Status RecolorCalculator::RenderCpu(CalculatorContext* cc) {
-  return ::mediapipe::UnimplementedError("CPU support is not implemented yet.");
+  if (cc->Inputs().Tag("MASK").IsEmpty()) {
+    return ::mediapipe::OkStatus();
+  }
+  // Get inputs and setup output.
+  const auto& input_img = cc->Inputs().Tag("IMAGE").Get<ImageFrame>();
+  const auto& mask_img = cc->Inputs().Tag("MASK").Get<ImageFrame>();
+
+  cv::Mat input_mat = formats::MatView(&input_img);
+  cv::Mat mask_mat = formats::MatView(&mask_img);
+
+  RET_CHECK(input_mat.channels() == 3);  // RGB only.
+
+  if (mask_mat.channels() > 1) {
+    std::vector<cv::Mat> channels;
+    cv::split(mask_mat, channels);
+    if (mask_channel_ == mediapipe::RecolorCalculatorOptions_MaskChannel_ALPHA)
+      mask_mat = channels[3];
+    else
+      mask_mat = channels[0];
+  }
+  cv::Mat mask_full;
+  cv::resize(mask_mat, mask_full, input_mat.size());
+
+  auto output_img = absl::make_unique<ImageFrame>(
+      input_img.Format(), input_mat.cols, input_mat.rows);
+  cv::Mat output_mat = mediapipe::formats::MatView(output_img.get());
+
+  // From GPU shader:
+  /*
+      vec4 weight = texture2D(mask, sample_coordinate);
+      vec4 color1 = texture2D(frame, sample_coordinate);
+      vec4 color2 = vec4(recolor, 1.0);
+
+      float luminance = dot(color1.rgb, vec3(0.299, 0.587, 0.114));
+      float mix_value = weight.MASK_COMPONENT * luminance;
+
+      fragColor = mix(color1, color2, mix_value);
+  */
+  for (int i = 0; i < output_mat.rows; ++i) {
+    for (int j = 0; j < output_mat.cols; ++j) {
+      float weight = mask_full.at<uchar>(i, j) * (1.0 / 255.0);
+      cv::Vec3f color1 = input_mat.at<cv::Vec3b>(i, j);
+      cv::Vec3f color2 = {color_[0], color_[1], color_[2]};
+
+      float luminance =
+          (color1[0] * 0.299 + color1[1] * 0.587 + color1[2] * 0.114) / 255;
+      float mix_value = weight * luminance;
+
+      cv::Vec3b mix_color = color1 * (1.0 - mix_value) + color2 * mix_value;
+      output_mat.at<cv::Vec3b>(i, j) = mix_color;
+    }
+  }
+
+  cc->Outputs().Tag("IMAGE").Add(output_img.release(), cc->InputTimestamp());
+
+  return ::mediapipe::OkStatus();
 }

 ::mediapipe::Status RecolorCalculator::RenderGpu(CalculatorContext* cc) {
@@ -303,9 +366,9 @@ void RecolorCalculator::GlRender() {

  if (!options.has_color()) RET_CHECK_FAIL() << "Missing color option.";

-  color_.push_back(options.color().r() / 255.0);
-  color_.push_back(options.color().g() / 255.0);
-  color_.push_back(options.color().b() / 255.0);
+  color_.push_back(options.color().r());
+  color_.push_back(options.color().g());
+  color_.push_back(options.color().b());

  return ::mediapipe::OkStatus();
 }
@@ -378,8 +441,8 @@ void RecolorCalculator::GlRender() {
  glUseProgram(program_);
  glUniform1i(glGetUniformLocation(program_, "frame"), 1);
  glUniform1i(glGetUniformLocation(program_, "mask"), 2);
-  glUniform3f(glGetUniformLocation(program_, "recolor"), color_[0], color_[1],
-              color_[2]);
+  glUniform3f(glGetUniformLocation(program_, "recolor"), color_[0] / 255.0,
+              color_[1] / 255.0, color_[2] / 255.0);
 #endif  //  !MEDIAPIPE_DISABLE_GPU

  return ::mediapipe::OkStatus();
@@ -260,11 +260,11 @@ ScaleImageCalculator::~ScaleImageCalculator() {}
                                      &crop_width_, &crop_height_,  //
                                      &col_start_, &row_start_));
  MP_RETURN_IF_ERROR(
-      scale_image::FindOutputDimensions(crop_width_, crop_height_,            //
-                                        options_.target_width(),              //
-                                        options_.target_height(),             //
-                                        options_.preserve_aspect_ratio(),     //
-                                        options_.scale_to_multiple_of_two(),  //
+      scale_image::FindOutputDimensions(crop_width_, crop_height_,         //
+                                        options_.target_width(),           //
+                                        options_.target_height(),          //
+                                        options_.preserve_aspect_ratio(),  //
+                                        options_.scale_to_multiple_of(),   //
                                        &output_width_, &output_height_));
  MP_RETURN_IF_ERROR(FindInterpolationAlgorithm(options_.algorithm(),
                                                &interpolation_algorithm_));
@@ -361,17 +361,21 @@ ScaleImageCalculator::~ScaleImageCalculator() {}
      output_format_ = input_format_;
    }

+    const bool is_positive_and_even =
+        (options_.scale_to_multiple_of() >= 1) &&
+        (options_.scale_to_multiple_of() % 2 == 0);
+
    if (output_format_ == ImageFormat::YCBCR420P) {
-      RET_CHECK(options_.scale_to_multiple_of_two())
+      RET_CHECK(is_positive_and_even)
          << "ScaleImageCalculator always outputs width and height that are "
             "divisible by 2 when output format is YCbCr420P. To scale to "
             "width and height of odd numbers, the output format must be SRGB.";
    } else if (options_.preserve_aspect_ratio()) {
-      RET_CHECK(options_.scale_to_multiple_of_two())
+      RET_CHECK(options_.scale_to_multiple_of() == 2)
          << "ScaleImageCalculator always outputs width and height that are "
-             "divisible by 2 when perserving aspect ratio. To scale to width "
-             "and height of odd numbers, please set "
-             "preserve_aspect_ratio to false.";
+             "divisible by 2 when preserving aspect ratio. If you'd like to "
+             "set scale_to_multiple_of to something other than 2, please "
+             "set preserve_aspect_ratio to false.";
    }

    if (input_width_ > 0 && input_height_ > 0 &&
@@ -474,13 +478,20 @@ ScaleImageCalculator::~ScaleImageCalculator() {}
          input_width_, "x", input_height_));
    }
    if (input_format_ != image_frame.Format()) {
+      std::string image_frame_format_desc, input_format_desc;
+#ifdef MEDIAPIPE_MOBILE
+      image_frame_format_desc = std::to_string(image_frame.Format());
+      input_format_desc = std::to_string(input_format_);
+#else
      const proto_ns::EnumDescriptor* desc = ImageFormat::Format_descriptor();
+      image_frame_format_desc =
+          desc->FindValueByNumber(image_frame.Format())->DebugString();
+      input_format_desc = desc->FindValueByNumber(input_format_)->DebugString();
+#endif  // MEDIAPIPE_MOBILE
      return tool::StatusFail(absl::StrCat(
          "If a header specifies a format, then image frames on "
          "the stream must have that format.  Actual format ",
-          desc->FindValueByNumber(image_frame.Format())->DebugString(),
-          " but expected ",
-          desc->FindValueByNumber(input_format_)->DebugString()));
+          image_frame_format_desc, " but expected ", input_format_desc));
    }
  }
  return ::mediapipe::OkStatus();
@@ -11,9 +11,10 @@ import "mediapipe/framework/formats/image_format.proto";
 // 2) Scale and convert the image to fit inside target_width x target_height
 //    using the specified scaling algorithm.  (maintaining the aspect
 //    ratio if preserve_aspect_ratio is true).
-// The output width and height will be divisible by 2. It is possible to output
-// width and height that are odd number when the output format is SRGB and not
-// perserving the aspect ratio. See scale_to_multiple_of_two option for details.
+// The output width and height will be divisible by 2, by default. It is
+// possible to output width and height that are odd numbers when the output
+// format is SRGB and the aspect ratio is left unpreserved. See
+// scale_to_multiple_of for details.
 message ScaleImageCalculatorOptions {
  extend CalculatorOptions {
    optional ScaleImageCalculatorOptions ext = 66237115;
@@ -23,7 +24,7 @@ message ScaleImageCalculatorOptions {
  // depending on the other options below.  If unset, use the same width
  // or height as the input.  If only one is set then determine the other
  // from the aspect ratio (after cropping).  The output width and height
-  // will be divisible by 2.
+  // will be divisible by 2, by default.
  optional int32 target_width = 1;
  optional int32 target_height = 2;

@@ -31,12 +32,14 @@ message ScaleImageCalculatorOptions {
  // fits inside the box represented by target_width and target_height.
  // Otherwise it is scaled to fit target_width and target_height
  // completely.  In any case, the aspect ratio that is preserved is
-  // that after cropping to the minimum/maximum aspect ratio.
+  // that after cropping to the minimum/maximum aspect ratio. Additionally, if
+  // true, the output width and height will be divisible by 2.
  optional bool preserve_aspect_ratio = 3 [default = true];

  // If ratio is positive, crop the image to this minimum and maximum
  // aspect ratio (preserving the center of the frame).  This is done
-  // before scaling.
+  // before scaling.  The string must contain "/", so to disable cropping,
+  // set both to "0/1".
  //   For example, for a min_aspect_ratio of "9/16" and max of "16/9" the
  //   following cropping will occur:
  //       1920x1080 (which is 16:9) is not cropped
@@ -94,11 +97,13 @@ message ScaleImageCalculatorOptions {
  // SRGB or YCBCR420P.
  optional ImageFormat.Format input_format = 12;

-  // If true, the output width and height will be divisible by 2. Otherwise it
-  // will use the exact specified output width and height, which is only
-  // supported when the output format is SRGB and preserve_aspect_ratio option
-  // is set to false.
-  optional bool scale_to_multiple_of_two = 13 [default = true];
+  // If set to 2, the target width and height will be rounded-down
+  // to the nearest even number. If set to any positive value other than 2,
+  // preserve_aspect_ratio must be false and the target width and height will be
+  // rounded-down to multiples of the given value. If set to any value less than
+  // 1, it will be treated like 1.
+  // NOTE: If set to an odd number, the output format must be SRGB.
+  optional int32 scale_to_multiple_of = 13 [default = 2];

  // If true, assume the input YUV is BT.709 (this is the HDTV standard, so most
  // content is likely using it). If false use the previous assumption of BT.601
@@ -88,17 +88,27 @@ double ParseRational(const std::string& rational) {
  return ::mediapipe::OkStatus();
 }

-::mediapipe::Status FindOutputDimensions(int input_width,                //
-                                         int input_height,               //
-                                         int target_width,               //
-                                         int target_height,              //
-                                         bool preserve_aspect_ratio,     //
-                                         bool scale_to_multiple_of_two,  //
+::mediapipe::Status FindOutputDimensions(int input_width,             //
+                                         int input_height,            //
+                                         int target_width,            //
+                                         int target_height,           //
+                                         bool preserve_aspect_ratio,  //
+                                         int scale_to_multiple_of,    //
                                         int* output_width,
                                         int* output_height) {
  CHECK(output_width);
  CHECK(output_height);

+  if (preserve_aspect_ratio) {
+    RET_CHECK(scale_to_multiple_of == 2)
+        << "FindOutputDimensions always outputs width and height that are "
+           "divisible by 2 when preserving aspect ratio. If you'd like to "
+           "set scale_to_multiple_of to something other than 2, please "
+           "set preserve_aspect_ratio to false.";
+  }
+
+  if (scale_to_multiple_of < 1) scale_to_multiple_of = 1;
+
  if (!preserve_aspect_ratio || (target_width <= 0 && target_height <= 0)) {
    if (target_width <= 0) {
      target_width = input_width;
@@ -106,13 +116,13 @@ double ParseRational(const std::string& rational) {
    if (target_height <= 0) {
      target_height = input_height;
    }
-    if (scale_to_multiple_of_two) {
-      *output_width = (target_width / 2) * 2;
-      *output_height = (target_height / 2) * 2;
-    } else {
-      *output_width = target_width;
-      *output_height = target_height;
-    }
+
+    target_width -= target_width % scale_to_multiple_of;
+    target_height -= target_height % scale_to_multiple_of;
+
+    *output_width = target_width;
+    *output_height = target_height;
+
    return ::mediapipe::OkStatus();
  }

@@ -35,17 +35,19 @@ namespace scale_image {
                                       int* col_start, int* row_start);

 // Given an input width and height, a target width and height, whether to
-// preserve the aspect ratio, and whether to round down to a multiple of 2,
-// determine the output width and height. If target_width or target_height is
-// non-positive, then they will be set to the input_width and input_height
-// respectively. The output_width and output_height will be reduced as necessary
-// to preserve_aspect_ratio and to scale_to_multipe_of_two if these options are
-// specified.
+// preserve the aspect ratio, and whether to round-down to the multiple of a
+// given number nearest to the targets, determine the output width and height.
+// If target_width or target_height is non-positive, then they will be set to
+// the input_width and input_height respectively. If scale_to_multiple_of is
+// less than 1, it will be treated like 1. The output_width and
+// output_height will be reduced as necessary to preserve_aspect_ratio if the
+// option is specified. If preserving the aspect ratio is desired, you must set
+// scale_to_multiple_of to 2.
 ::mediapipe::Status FindOutputDimensions(int input_width, int input_height,  //
                                         int target_width,
-                                         int target_height,              //
-                                         bool preserve_aspect_ratio,     //
-                                         bool scale_to_multiple_of_two,  //
+                                         int target_height,           //
+                                         bool preserve_aspect_ratio,  //
+                                         int scale_to_multiple_of,    //
                                         int* output_width, int* output_height);

 }  // namespace scale_image
@@ -79,49 +79,49 @@ TEST(ScaleImageUtilsTest, FindOutputDimensionsPreserveRatio) {
  int output_width;
  int output_height;
  // Not scale.
-  MP_ASSERT_OK(FindOutputDimensions(200, 100, -1, -1, true, true, &output_width,
+  MP_ASSERT_OK(FindOutputDimensions(200, 100, -1, -1, true, 2, &output_width,
                                    &output_height));
  EXPECT_EQ(200, output_width);
  EXPECT_EQ(100, output_height);
  // Not scale with odd input size.
-  MP_ASSERT_OK(FindOutputDimensions(201, 101, -1, -1, false, false,
-                                    &output_width, &output_height));
+  MP_ASSERT_OK(FindOutputDimensions(201, 101, -1, -1, false, 1, &output_width,
+                                    &output_height));
  EXPECT_EQ(201, output_width);
  EXPECT_EQ(101, output_height);
  // Scale down by 1/2.
-  MP_ASSERT_OK(FindOutputDimensions(200, 100, 100, -1, true, true,
-                                    &output_width, &output_height));
+  MP_ASSERT_OK(FindOutputDimensions(200, 100, 100, -1, true, 2, &output_width,
+                                    &output_height));
  EXPECT_EQ(100, output_width);
  EXPECT_EQ(50, output_height);
  // Scale up, doubling dimensions.
-  MP_ASSERT_OK(FindOutputDimensions(200, 100, -1, 200, true, true,
-                                    &output_width, &output_height));
+  MP_ASSERT_OK(FindOutputDimensions(200, 100, -1, 200, true, 2, &output_width,
+                                    &output_height));
  EXPECT_EQ(400, output_width);
  EXPECT_EQ(200, output_height);
  // Fits a 2:1 image into a 150 x 150 box. Output dimensions are always
  // visible by 2.
-  MP_ASSERT_OK(FindOutputDimensions(200, 100, 150, 150, true, true,
-                                    &output_width, &output_height));
+  MP_ASSERT_OK(FindOutputDimensions(200, 100, 150, 150, true, 2, &output_width,
+                                    &output_height));
  EXPECT_EQ(150, output_width);
  EXPECT_EQ(74, output_height);
  // Fits a 2:1 image into a 400 x 50 box.
-  MP_ASSERT_OK(FindOutputDimensions(200, 100, 400, 50, true, true,
-                                    &output_width, &output_height));
+  MP_ASSERT_OK(FindOutputDimensions(200, 100, 400, 50, true, 2, &output_width,
+                                    &output_height));
  EXPECT_EQ(100, output_width);
  EXPECT_EQ(50, output_height);
  // Scale to multiple number with odd targe size.
-  MP_ASSERT_OK(FindOutputDimensions(200, 100, 101, -1, true, true,
-                                    &output_width, &output_height));
+  MP_ASSERT_OK(FindOutputDimensions(200, 100, 101, -1, true, 2, &output_width,
+                                    &output_height));
  EXPECT_EQ(100, output_width);
  EXPECT_EQ(50, output_height);
  // Scale to multiple number with odd targe size.
-  MP_ASSERT_OK(FindOutputDimensions(200, 100, 101, -1, true, false,
-                                    &output_width, &output_height));
+  MP_ASSERT_OK(FindOutputDimensions(200, 100, 101, -1, true, 2, &output_width,
+                                    &output_height));
  EXPECT_EQ(100, output_width);
  EXPECT_EQ(50, output_height);
  // Scale to odd size.
-  MP_ASSERT_OK(FindOutputDimensions(200, 100, 151, 101, false, false,
-                                    &output_width, &output_height));
+  MP_ASSERT_OK(FindOutputDimensions(200, 100, 151, 101, false, 1, &output_width,
+                                    &output_height));
  EXPECT_EQ(151, output_width);
  EXPECT_EQ(101, output_height);
 }
@@ -131,22 +131,62 @@ TEST(ScaleImageUtilsTest, FindOutputDimensionsNoAspectRatio) {
  int output_width;
  int output_height;
  // Scale width only.
-  MP_ASSERT_OK(FindOutputDimensions(200, 100, 100, -1, false, true,
-                                    &output_width, &output_height));
+  MP_ASSERT_OK(FindOutputDimensions(200, 100, 100, -1, false, 2, &output_width,
+                                    &output_height));
  EXPECT_EQ(100, output_width);
  EXPECT_EQ(100, output_height);
  // Scale height only.
-  MP_ASSERT_OK(FindOutputDimensions(200, 100, -1, 200, false, true,
-                                    &output_width, &output_height));
+  MP_ASSERT_OK(FindOutputDimensions(200, 100, -1, 200, false, 2, &output_width,
+                                    &output_height));
  EXPECT_EQ(200, output_width);
  EXPECT_EQ(200, output_height);
  // Scale both dimensions.
-  MP_ASSERT_OK(FindOutputDimensions(200, 100, 150, 200, false, true,
-                                    &output_width, &output_height));
+  MP_ASSERT_OK(FindOutputDimensions(200, 100, 150, 200, false, 2, &output_width,
+                                    &output_height));
  EXPECT_EQ(150, output_width);
  EXPECT_EQ(200, output_height);
 }

+// Tests scale_to_multiple_of.
+TEST(ScaleImageUtilsTest, FindOutputDimensionsDownScaleToMultipleOf) {
+  int output_width;
+  int output_height;
+  // Set no targets, downscale to a multiple of 8.
+  MP_ASSERT_OK(FindOutputDimensions(100, 100, -1, -1, false, 8, &output_width,
+                                    &output_height));
+  EXPECT_EQ(96, output_width);
+  EXPECT_EQ(96, output_height);
+  // Set width target, downscale to a multiple of 8.
+  MP_ASSERT_OK(FindOutputDimensions(200, 100, 100, -1, false, 8, &output_width,
+                                    &output_height));
+  EXPECT_EQ(96, output_width);
+  EXPECT_EQ(96, output_height);
+  // Set height target, downscale to a multiple of 8.
+  MP_ASSERT_OK(FindOutputDimensions(201, 101, -1, 201, false, 8, &output_width,
+                                    &output_height));
+  EXPECT_EQ(200, output_width);
+  EXPECT_EQ(200, output_height);
+  // Set both targets, downscale to a multiple of 8.
+  MP_ASSERT_OK(FindOutputDimensions(200, 100, 150, 200, false, 8, &output_width,
+                                    &output_height));
+  EXPECT_EQ(144, output_width);
+  EXPECT_EQ(200, output_height);
+  // Doesn't throw error if keep aspect is true and downscale multiple is 2.
+  MP_ASSERT_OK(FindOutputDimensions(200, 100, 400, 200, true, 2, &output_width,
+                                    &output_height));
+  EXPECT_EQ(400, output_width);
+  EXPECT_EQ(200, output_height);
+  // Throws error if keep aspect is true, but downscale multiple is not 2.
+  ASSERT_THAT(FindOutputDimensions(200, 100, 400, 200, true, 4, &output_width,
+                                   &output_height),
+              testing::Not(testing::status::IsOk()));
+  // Downscaling to multiple ignored if multiple is less than 2.
+  MP_ASSERT_OK(FindOutputDimensions(200, 100, 401, 201, false, 1, &output_width,
+                                    &output_height));
+  EXPECT_EQ(401, output_width);
+  EXPECT_EQ(201, output_height);
+}
+
 }  // namespace
 }  // namespace scale_image
 }  // namespace mediapipe
@@ -21,6 +21,7 @@ filegroup(
        "dino.jpg",
        "dino_quality_50.jpg",
        "dino_quality_80.jpg",
+        "front_camera_pixel2.jpg",
    ],
    visibility = ["//visibility:public"],
 )
@@ -13,12 +13,12 @@
 # limitations under the License.
 #

+load("//mediapipe/framework/port:build_config.bzl", "mediapipe_cc_proto_library")
+
 licenses(["notice"])  # Apache 2.0

 package(default_visibility = ["//visibility:private"])

-load("//mediapipe/framework/port:build_config.bzl", "mediapipe_cc_proto_library")
-
 proto_library(
    name = "graph_tensors_packet_generator_proto",
    srcs = ["graph_tensors_packet_generator.proto"],
@@ -104,6 +104,17 @@ proto_library(
    deps = ["//mediapipe/framework:calculator_proto"],
 )

+proto_library(
+    name = "unpack_media_sequence_calculator_proto",
+    srcs = ["unpack_media_sequence_calculator.proto"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/calculators/core:packet_resampler_calculator_proto",
+        "//mediapipe/framework:calculator_proto",
+        "//mediapipe/util:audio_decoder_proto",
+    ],
+)
+
 proto_library(
    name = "vector_float_to_tensor_calculator_options_proto",
    srcs = ["vector_float_to_tensor_calculator_options.proto"],
@@ -261,6 +272,17 @@ mediapipe_cc_proto_library(
    deps = [":unpack_media_sequence_calculator_proto"],
 )

+mediapipe_cc_proto_library(
+    name = "vector_int_to_tensor_calculator_options_cc_proto",
+    srcs = ["vector_int_to_tensor_calculator_options.proto"],
+    cc_deps = [
+        "//mediapipe/framework:calculator_cc_proto",
+        "@org_tensorflow//tensorflow/core:protos_all_cc",
+    ],
+    visibility = ["//visibility:public"],
+    deps = [":vector_int_to_tensor_calculator_options_proto"],
+)
+
 mediapipe_cc_proto_library(
    name = "vector_float_to_tensor_calculator_options_cc_proto",
    srcs = ["vector_float_to_tensor_calculator_options.proto"],
@@ -274,7 +296,7 @@ cc_library(
    srcs = ["graph_tensors_packet_generator.cc"],
    visibility = ["//visibility:public"],
    deps = [
-        "//mediapipe/calculators/tensorflow:graph_tensors_packet_generator_cc_proto",
+        ":graph_tensors_packet_generator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
@@ -289,7 +311,7 @@ cc_library(
    srcs = ["image_frame_to_tensor_calculator.cc"],
    visibility = ["//visibility:public"],
    deps = [
-        "//mediapipe/calculators/tensorflow:image_frame_to_tensor_calculator_cc_proto",
+        ":image_frame_to_tensor_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/formats:image_frame",
        "//mediapipe/framework/port:ret_check",
@@ -311,7 +333,7 @@ cc_library(
    visibility = ["//visibility:public"],
    deps = [
        "//mediapipe/framework/formats:time_series_header_cc_proto",
-        "//mediapipe/calculators/tensorflow:matrix_to_tensor_calculator_options_cc_proto",
+        ":matrix_to_tensor_calculator_options_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/formats:matrix",
        "//mediapipe/framework/port:status",
@@ -332,7 +354,7 @@ cc_library(
    srcs = ["lapped_tensor_buffer_calculator.cc"],
    visibility = ["//visibility:public"],
    deps = [
-        "//mediapipe/calculators/tensorflow:lapped_tensor_buffer_calculator_cc_proto",
+        ":lapped_tensor_buffer_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
@@ -414,7 +436,7 @@ cc_library(
    visibility = ["//visibility:public"],
    deps = [
        ":tensorflow_session",
-        "//mediapipe/calculators/tensorflow:tensorflow_inference_calculator_cc_proto",
+        ":tensorflow_inference_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/tool:status_util",
        "@com_google_absl//absl/strings",
@@ -492,7 +514,7 @@ cc_library(
    visibility = ["//visibility:public"],
    deps = [
        ":tensorflow_session",
-        "//mediapipe/calculators/tensorflow:tensorflow_session_from_frozen_graph_generator_cc_proto",
+        ":tensorflow_session_from_frozen_graph_generator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/tool:status_util",
        "//mediapipe/framework/port:status",
@@ -551,7 +573,7 @@ cc_library(
    visibility = ["//visibility:public"],
    deps = [
        ":tensorflow_session",
-        "//mediapipe/calculators/tensorflow:tensorflow_session_from_saved_model_generator_cc_proto",
+        ":tensorflow_session_from_saved_model_generator_cc_proto",
        "//mediapipe/framework:packet_generator",
        "//mediapipe/framework:packet_type",
        "//mediapipe/framework/tool:status_util",
@@ -575,7 +597,7 @@ cc_library(
    srcs = ["tensor_squeeze_dimensions_calculator.cc"],
    visibility = ["//visibility:public"],
    deps = [
-        "//mediapipe/calculators/tensorflow:tensor_squeeze_dimensions_calculator_cc_proto",
+        ":tensor_squeeze_dimensions_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
@@ -589,7 +611,7 @@ cc_library(
    srcs = ["tensor_to_image_frame_calculator.cc"],
    visibility = ["//visibility:public"],
    deps = [
-        "//mediapipe/calculators/tensorflow:tensor_to_image_frame_calculator_cc_proto",
+        ":tensor_to_image_frame_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/formats:image_frame",
        "//mediapipe/framework/port:ret_check",
@@ -605,7 +627,7 @@ cc_library(
    visibility = ["//visibility:public"],
    deps = [
        "//mediapipe/framework/formats:time_series_header_cc_proto",
-        "//mediapipe/calculators/tensorflow:tensor_to_matrix_calculator_cc_proto",
+        ":tensor_to_matrix_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/formats:matrix",
        "//mediapipe/framework/port:status",
@@ -621,6 +643,22 @@ cc_library(
    alwayslink = 1,
 )

+cc_library(
+    name = "tfrecord_reader_calculator",
+    srcs = ["tfrecord_reader_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/port:integral_types",
+        "//mediapipe/framework/port:logging",
+        "//mediapipe/framework/port:ret_check",
+        "//mediapipe/framework/port:status",
+        "@org_tensorflow//tensorflow/core:lib",
+        "@org_tensorflow//tensorflow/core:protos_all_cc",
+    ],
+    alwayslink = 1,
+)
+
 cc_library(
    name = "tensor_to_vector_float_calculator",
    srcs = ["tensor_to_vector_float_calculator.cc"],
@@ -629,7 +667,7 @@ cc_library(
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/port:status",
        "//mediapipe/framework/port:ret_check",
-        "//mediapipe/calculators/tensorflow:tensor_to_vector_float_calculator_options_cc_proto",
+        ":tensor_to_vector_float_calculator_options_cc_proto",
    ] + select({
        "//conditions:default": [
            "@org_tensorflow//tensorflow/core:framework",
@@ -663,11 +701,11 @@ cc_library(
 )

 cc_library(
-    name = "vector_float_to_tensor_calculator",
-    srcs = ["vector_float_to_tensor_calculator.cc"],
+    name = "vector_int_to_tensor_calculator",
+    srcs = ["vector_int_to_tensor_calculator.cc"],
    visibility = ["//visibility:public"],
    deps = [
-        "//mediapipe/calculators/tensorflow:vector_float_to_tensor_calculator_options_cc_proto",
+        ":vector_int_to_tensor_calculator_options_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
@@ -676,12 +714,41 @@ cc_library(
    alwayslink = 1,
 )

+cc_library(
+    name = "vector_float_to_tensor_calculator",
+    srcs = ["vector_float_to_tensor_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        ":vector_float_to_tensor_calculator_options_cc_proto",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/port:ret_check",
+        "//mediapipe/framework/port:status",
+        "@org_tensorflow//tensorflow/core:framework",
+    ],
+    alwayslink = 1,
+)
+
+cc_library(
+    name = "unpack_yt8m_sequence_example_calculator",
+    srcs = ["unpack_yt8m_sequence_example_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        ":lapped_tensor_buffer_calculator_cc_proto",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:packet",
+        "//mediapipe/framework/port:status",
+        "@org_tensorflow//tensorflow/core:protos_all_cc",
+    ],
+    alwayslink = 1,
+)
+
 cc_test(
    name = "graph_tensors_packet_generator_test",
    srcs = ["graph_tensors_packet_generator_test.cc"],
+    linkstatic = 1,
    deps = [
        ":graph_tensors_packet_generator",
-        "//mediapipe/calculators/tensorflow:graph_tensors_packet_generator_cc_proto",
+        ":graph_tensors_packet_generator_cc_proto",
        "//mediapipe/framework:packet",
        "//mediapipe/framework:packet_generator_cc_proto",
        "//mediapipe/framework:packet_set",
@@ -695,6 +762,7 @@ cc_test(
    name = "image_frame_to_tensor_calculator_test",
    size = "small",
    srcs = ["image_frame_to_tensor_calculator_test.cc"],
+    linkstatic = 1,
    deps = [
        ":image_frame_to_tensor_calculator",
        "//mediapipe/framework:calculator_framework",
@@ -711,9 +779,10 @@ cc_test(
    name = "matrix_to_tensor_calculator_test",
    size = "small",
    srcs = ["matrix_to_tensor_calculator_test.cc"],
+    linkstatic = 1,
    deps = [
        ":matrix_to_tensor_calculator",
-        "//mediapipe/calculators/tensorflow:matrix_to_tensor_calculator_options_cc_proto",
+        ":matrix_to_tensor_calculator_options_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:calculator_runner",
        "//mediapipe/framework/formats:matrix",
@@ -727,9 +796,10 @@ cc_test(
    name = "lapped_tensor_buffer_calculator_test",
    size = "small",
    srcs = ["lapped_tensor_buffer_calculator_test.cc"],
+    linkstatic = 1,
    deps = [
        ":lapped_tensor_buffer_calculator",
-        "//mediapipe/calculators/tensorflow:lapped_tensor_buffer_calculator_cc_proto",
+        ":lapped_tensor_buffer_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:calculator_runner",
        "//mediapipe/framework/port:gtest_main",
@@ -817,7 +887,7 @@ cc_test(
        ":tensorflow_inference_calculator",
        ":tensorflow_session",
        ":tensorflow_session_from_frozen_graph_generator",
-        "//mediapipe/calculators/tensorflow:tensorflow_session_from_frozen_graph_generator_cc_proto",
+        ":tensorflow_session_from_frozen_graph_generator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:packet",
        "//mediapipe/framework:packet_generator_cc_proto",
@@ -847,7 +917,7 @@ cc_test(
        ":tensorflow_inference_calculator",
        ":tensorflow_session",
        ":tensorflow_session_from_saved_model_generator",
-        "//mediapipe/calculators/tensorflow:tensorflow_session_from_saved_model_generator_cc_proto",
+        ":tensorflow_session_from_saved_model_generator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:packet",
        "//mediapipe/framework:packet_generator_cc_proto",
@@ -857,14 +927,8 @@ cc_test(
        "//mediapipe/framework/tool:tag_map_helper",
        "//mediapipe/framework/tool:validate_type",
        "@com_google_absl//absl/strings",
+        "@org_tensorflow//tensorflow/core:all_kernels",
        "@org_tensorflow//tensorflow/core:direct_session",
-        "@org_tensorflow//tensorflow/core/kernels:array",
-        "@org_tensorflow//tensorflow/core/kernels:bitcast_op",
-        "@org_tensorflow//tensorflow/core/kernels:conv_ops",
-        "@org_tensorflow//tensorflow/core/kernels:io",
-        "@org_tensorflow//tensorflow/core/kernels:state",
-        "@org_tensorflow//tensorflow/core/kernels:string",
-        "@org_tensorflow//tensorflow/core/kernels/data:tensor_dataset_op",
    ],
 )

@@ -888,23 +952,18 @@ cc_test(
        "//mediapipe/framework/tool:tag_map_helper",
        "//mediapipe/framework/tool:validate_type",
        "@com_google_absl//absl/strings",
+        "@org_tensorflow//tensorflow/core:all_kernels",
        "@org_tensorflow//tensorflow/core:direct_session",
-        "@org_tensorflow//tensorflow/core/kernels:array",
-        "@org_tensorflow//tensorflow/core/kernels:bitcast_op",
-        "@org_tensorflow//tensorflow/core/kernels:conv_ops",
-        "@org_tensorflow//tensorflow/core/kernels:io",
-        "@org_tensorflow//tensorflow/core/kernels:state",
-        "@org_tensorflow//tensorflow/core/kernels:string",
-        "@org_tensorflow//tensorflow/core/kernels/data:tensor_dataset_op",
    ],
 )

 cc_test(
    name = "tensor_squeeze_dimensions_calculator_test",
    srcs = ["tensor_squeeze_dimensions_calculator_test.cc"],
+    linkstatic = 1,
    deps = [
        ":tensor_squeeze_dimensions_calculator",
-        "//mediapipe/calculators/tensorflow:tensor_squeeze_dimensions_calculator_cc_proto",
+        ":tensor_squeeze_dimensions_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:calculator_runner",
        "//mediapipe/framework/port:gtest_main",
@@ -917,9 +976,10 @@ cc_test(
    name = "tensor_to_image_frame_calculator_test",
    size = "small",
    srcs = ["tensor_to_image_frame_calculator_test.cc"],
+    linkstatic = 1,
    deps = [
        ":tensor_to_image_frame_calculator",
-        "//mediapipe/calculators/tensorflow:tensor_to_image_frame_calculator_cc_proto",
+        ":tensor_to_image_frame_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:calculator_runner",
        "//mediapipe/framework/formats:image_frame",
@@ -933,9 +993,10 @@ cc_test(
    name = "tensor_to_matrix_calculator_test",
    size = "small",
    srcs = ["tensor_to_matrix_calculator_test.cc"],
+    linkstatic = 1,
    deps = [
        ":tensor_to_matrix_calculator",
-        "//mediapipe/calculators/tensorflow:tensor_to_matrix_calculator_cc_proto",
+        ":tensor_to_matrix_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:calculator_runner",
        "//mediapipe/framework/formats:matrix",
@@ -949,9 +1010,10 @@ cc_test(
 cc_test(
    name = "tensor_to_vector_float_calculator_test",
    srcs = ["tensor_to_vector_float_calculator_test.cc"],
+    linkstatic = 1,
    deps = [
        ":tensor_to_vector_float_calculator",
-        "//mediapipe/calculators/tensorflow:tensor_to_vector_float_calculator_options_cc_proto",
+        ":tensor_to_vector_float_calculator_options_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:calculator_runner",
        "//mediapipe/framework/port:gtest_main",
@@ -980,12 +1042,28 @@ cc_test(
    ],
 )

+cc_test(
+    name = "vector_int_to_tensor_calculator_test",
+    srcs = ["vector_int_to_tensor_calculator_test.cc"],
+    linkstatic = 1,
+    deps = [
+        ":vector_int_to_tensor_calculator",
+        ":vector_int_to_tensor_calculator_options_cc_proto",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:calculator_runner",
+        "//mediapipe/framework/port:gtest_main",
+        "@org_tensorflow//tensorflow/core:framework",
+        "@org_tensorflow//tensorflow/core:protos_all_cc",
+    ],
+)
+
 cc_test(
    name = "vector_float_to_tensor_calculator_test",
    srcs = ["vector_float_to_tensor_calculator_test.cc"],
+    linkstatic = 1,
    deps = [
        ":vector_float_to_tensor_calculator",
-        "//mediapipe/calculators/tensorflow:vector_float_to_tensor_calculator_options_cc_proto",
+        ":vector_float_to_tensor_calculator_options_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:calculator_runner",
        "//mediapipe/framework/port:gtest_main",
@@ -1014,7 +1092,7 @@ cc_test(
        ":tensorflow_session",
        ":tensorflow_inference_calculator",
        ":tensorflow_session_from_frozen_graph_generator",
-        "//mediapipe/calculators/tensorflow:tensorflow_session_from_frozen_graph_generator_cc_proto",
+        ":tensorflow_session_from_frozen_graph_generator_cc_proto",
        "//mediapipe/framework/deps:file_path",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:calculator_runner",
@@ -1032,6 +1110,7 @@ cc_test(
        ],
        "//mediapipe:android": [
            "@org_tensorflow//tensorflow/core:android_tensorflow_lib_with_ops_lite_proto_no_rtti_lib",
+            "@org_tensorflow//tensorflow/core:android_tensorflow_test_lib",
        ],
        "//mediapipe:ios": [
            "@org_tensorflow//tensorflow/core:ios_tensorflow_test_lib",
@@ -29,6 +29,11 @@

 namespace mediapipe {

+const char kBufferSize[] = "BUFFER_SIZE";
+const char kOverlap[] = "OVERLAP";
+const char kTimestampOffset[] = "TIMESTAMP_OFFSET";
+const char kCalculatorOptions[] = "CALCULATOR_OPTIONS";
+
 namespace tf = tensorflow;

 // Given an input stream of tensors, concatenates the tensors over timesteps.
@@ -72,6 +77,9 @@ class LappedTensorBufferCalculator : public CalculatorBase {
  ::mediapipe::Status AddBatchDimension(tf::Tensor* input_tensor);

  int steps_until_output_;
+  int buffer_size_;
+  int overlap_;
+  int timestamp_offset_;
  std::unique_ptr<CircularBuffer<Timestamp>> timestamp_buffer_;
  std::unique_ptr<CircularBuffer<tf::Tensor>> buffer_;
  LappedTensorBufferCalculatorOptions options_;
@@ -87,6 +95,21 @@ REGISTER_CALCULATOR(LappedTensorBufferCalculator);
  );
  RET_CHECK_EQ(cc->Inputs().NumEntries(), 1)
      << "Only one output stream is supported.";
+
+  if (cc->InputSidePackets().HasTag(kBufferSize)) {
+    cc->InputSidePackets().Tag(kBufferSize).Set<int>();
+  }
+  if (cc->InputSidePackets().HasTag(kOverlap)) {
+    cc->InputSidePackets().Tag(kOverlap).Set<int>();
+  }
+  if (cc->InputSidePackets().HasTag(kTimestampOffset)) {
+    cc->InputSidePackets().Tag(kTimestampOffset).Set<int>();
+  }
+  if (cc->InputSidePackets().HasTag(kCalculatorOptions)) {
+    cc->InputSidePackets()
+        .Tag(kCalculatorOptions)
+        .Set<LappedTensorBufferCalculatorOptions>();
+  }
  cc->Outputs().Index(0).Set<tf::Tensor>(
      // Output tensorflow::Tensor stream with possibly overlapping steps.
  );
@@ -95,16 +118,33 @@ REGISTER_CALCULATOR(LappedTensorBufferCalculator);

 ::mediapipe::Status LappedTensorBufferCalculator::Open(CalculatorContext* cc) {
  options_ = cc->Options<LappedTensorBufferCalculatorOptions>();
-  RET_CHECK_LT(options_.overlap(), options_.buffer_size());
-  RET_CHECK_GE(options_.timestamp_offset(), 0)
+  if (cc->InputSidePackets().HasTag(kCalculatorOptions)) {
+    options_ = cc->InputSidePackets()
+                   .Tag(kCalculatorOptions)
+                   .Get<LappedTensorBufferCalculatorOptions>();
+  }
+  buffer_size_ = options_.buffer_size();
+  if (cc->InputSidePackets().HasTag(kBufferSize)) {
+    buffer_size_ = cc->InputSidePackets().Tag(kBufferSize).Get<int>();
+  }
+  overlap_ = options_.overlap();
+  if (cc->InputSidePackets().HasTag(kOverlap)) {
+    overlap_ = cc->InputSidePackets().Tag(kOverlap).Get<int>();
+  }
+  timestamp_offset_ = options_.timestamp_offset();
+  if (cc->InputSidePackets().HasTag(kTimestampOffset)) {
+    timestamp_offset_ = cc->InputSidePackets().Tag(kTimestampOffset).Get<int>();
+  }
+
+  RET_CHECK_LT(overlap_, buffer_size_);
+  RET_CHECK_GE(timestamp_offset_, 0)
      << "Negative timestamp_offset is not allowed.";
-  RET_CHECK_LT(options_.timestamp_offset(), options_.buffer_size())
+  RET_CHECK_LT(timestamp_offset_, buffer_size_)
      << "output_frame_num_offset has to be less than buffer_size.";
  timestamp_buffer_ =
-      absl::make_unique<CircularBuffer<Timestamp>>(options_.buffer_size());
-  buffer_ =
-      absl::make_unique<CircularBuffer<tf::Tensor>>(options_.buffer_size());
-  steps_until_output_ = options_.buffer_size();
+      absl::make_unique<CircularBuffer<Timestamp>>(buffer_size_);
+  buffer_ = absl::make_unique<CircularBuffer<tf::Tensor>>(buffer_size_);
+  steps_until_output_ = buffer_size_;
  return ::mediapipe::OkStatus();
 }

@@ -128,11 +168,10 @@ REGISTER_CALCULATOR(LappedTensorBufferCalculator);
        concatenated.get());
    RET_CHECK(concat_status.ok()) << concat_status.ToString();

-    cc->Outputs().Index(0).Add(
-        concatenated.release(),
-        timestamp_buffer_->Get(options_.timestamp_offset()));
+    cc->Outputs().Index(0).Add(concatenated.release(),
+                               timestamp_buffer_->Get(timestamp_offset_));

-    steps_until_output_ = options_.buffer_size() - options_.overlap();
+    steps_until_output_ = buffer_size_ - overlap_;
  }
  return ::mediapipe::OkStatus();
 }
@@ -34,6 +34,7 @@ namespace mediapipe {

 const char kSequenceExampleTag[] = "SEQUENCE_EXAMPLE";
 const char kImageTag[] = "IMAGE";
+const char kFloatContextFeaturePrefixTag[] = "FLOAT_CONTEXT_FEATURE_";
 const char kFloatFeaturePrefixTag[] = "FLOAT_FEATURE_";
 const char kForwardFlowEncodedTag[] = "FORWARD_FLOW_ENCODED";
 const char kBBoxTag[] = "BBOX";
@@ -145,6 +146,9 @@ class PackMediaSequenceCalculator : public CalculatorBase {
        }
        cc->Inputs().Tag(tag).Set<std::vector<Detection>>();
      }
+      if (absl::StartsWith(tag, kFloatContextFeaturePrefixTag)) {
+        cc->Inputs().Tag(tag).Set<std::vector<float>>();
+      }
      if (absl::StartsWith(tag, kFloatFeaturePrefixTag)) {
        cc->Inputs().Tag(tag).Set<std::vector<float>>();
      }
@@ -264,7 +268,7 @@ class PackMediaSequenceCalculator : public CalculatorBase {
    if (options.output_only_if_all_present()) {
      ::mediapipe::Status status = VerifySequence();
      if (!status.ok()) {
-        cc->GetCounter(status.error_message())->Increment();
+        cc->GetCounter(status.ToString())->Increment();
        return status;
      }
    }
@@ -344,6 +348,17 @@ class PackMediaSequenceCalculator : public CalculatorBase {
                             sequence_.get());
        }
      }
+      if (absl::StartsWith(tag, kFloatContextFeaturePrefixTag) &&
+          !cc->Inputs().Tag(tag).IsEmpty()) {
+        std::string key =
+            tag.substr(sizeof(kFloatContextFeaturePrefixTag) /
+                           sizeof(*kFloatContextFeaturePrefixTag) -
+                       1);
+        RET_CHECK_EQ(cc->InputTimestamp(), Timestamp::PostStream());
+        mpms::SetContextFeatureFloats(
+            key, cc->Inputs().Tag(tag).Get<std::vector<float>>(),
+            sequence_.get());
+      }
      if (absl::StartsWith(tag, kFloatFeaturePrefixTag) &&
          !cc->Inputs().Tag(tag).IsEmpty()) {
        std::string key = tag.substr(sizeof(kFloatFeaturePrefixTag) /
@@ -194,6 +194,38 @@ TEST_F(PackMediaSequenceCalculatorTest, PacksTwoFloatLists) {
  }
 }

+TEST_F(PackMediaSequenceCalculatorTest, PacksTwoContextFloatLists) {
+  SetUpCalculator(
+      {"FLOAT_CONTEXT_FEATURE_TEST:test", "FLOAT_CONTEXT_FEATURE_OTHER:test2"},
+      {}, false, true);
+  auto input_sequence = absl::make_unique<tf::SequenceExample>();
+
+  auto vf_ptr = absl::make_unique<std::vector<float>>(2, 3);
+  runner_->MutableInputs()
+      ->Tag("FLOAT_CONTEXT_FEATURE_TEST")
+      .packets.push_back(Adopt(vf_ptr.release()).At(Timestamp::PostStream()));
+  vf_ptr = absl::make_unique<std::vector<float>>(2, 4);
+  runner_->MutableInputs()
+      ->Tag("FLOAT_CONTEXT_FEATURE_OTHER")
+      .packets.push_back(Adopt(vf_ptr.release()).At(Timestamp::PostStream()));
+
+  runner_->MutableSidePackets()->Tag("SEQUENCE_EXAMPLE") =
+      Adopt(input_sequence.release());
+
+  MP_ASSERT_OK(runner_->Run());
+
+  const std::vector<Packet>& output_packets =
+      runner_->Outputs().Tag("SEQUENCE_EXAMPLE").packets;
+  ASSERT_EQ(1, output_packets.size());
+  const tf::SequenceExample& output_sequence =
+      output_packets[0].Get<tf::SequenceExample>();
+
+  ASSERT_THAT(mpms::GetContextFeatureFloats("TEST", output_sequence),
+              testing::ElementsAre(3, 3));
+  ASSERT_THAT(mpms::GetContextFeatureFloats("OTHER", output_sequence),
+              testing::ElementsAre(4, 4));
+}
+
 TEST_F(PackMediaSequenceCalculatorTest, PacksAdditionalContext) {
  tf::Features context;
  (*context.mutable_feature())["TEST"].mutable_bytes_list()->add_value("YES");
@@ -34,7 +34,7 @@
 #include "tensorflow/core/framework/tensor_shape.h"
 #include "tensorflow/core/framework/tensor_util.h"

-#if !defined(__ANDROID__) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_MOBILE) && !defined(__APPLE__)
 #include "tensorflow/core/profiler/lib/traceme.h"
 #endif

@@ -441,7 +441,7 @@ class TensorFlowInferenceCalculator : public CalculatorBase {
    const int64 run_start_time = absl::ToUnixMicros(clock_->TimeNow());
    tf::Status tf_status;
    {
-#if !defined(__ANDROID__) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_MOBILE) && !defined(__APPLE__)
      tensorflow::profiler::TraceMe trace(absl::string_view(cc->NodeName()));
 #endif
      tf_status = session_->Run(input_tensors, output_tensor_names,
@@ -454,7 +454,7 @@ class TensorFlowInferenceCalculator : public CalculatorBase {

    // RET_CHECK on the tf::Status object itself in order to print an
    // informative error message.
-    RET_CHECK(tf_status.ok()) << "Run failed: " << tf_status.error_message();
+    RET_CHECK(tf_status.ok()) << "Run failed: " << tf_status.ToString();

    const int64 run_end_time = absl::ToUnixMicros(clock_->TimeNow());
    cc->GetCounter(kTotalSessionRunsTimeUsecsCounterSuffix)
@@ -31,8 +31,7 @@
 #include "mediapipe/framework/tool/status_util.h"
 #include "tensorflow/core/public/session_options.h"

-#if defined(MEDIAPIPE_LITE) || defined(__ANDROID__) || \
-    defined(__APPLE__) && !TARGET_OS_OSX
+#if defined(MEDIAPIPE_MOBILE)
 #include "mediapipe/util/android/file/base/helpers.h"
 #else
 #include "mediapipe/framework/port/file_helpers.h"
@@ -110,7 +109,7 @@ class TensorFlowSessionFromFrozenGraphCalculator : public CalculatorBase {

    RET_CHECK(graph_def.ParseFromString(graph_def_serialized));
    const tf::Status tf_status = session->session->Create(graph_def);
-    RET_CHECK(tf_status.ok()) << "Create failed: " << tf_status.error_message();
+    RET_CHECK(tf_status.ok()) << "Create failed: " << tf_status.ToString();

    for (const auto& key_value : options.tag_to_tensor_names()) {
      session->tag_to_tensor_map[key_value.first] = key_value.second;
@@ -120,7 +119,7 @@ class TensorFlowSessionFromFrozenGraphCalculator : public CalculatorBase {
          session->session->Run({}, {}, initialization_op_names, {});
      // RET_CHECK on the tf::Status object itself in order to print an
      // informative error message.
-      RET_CHECK(tf_status.ok()) << "Run failed: " << tf_status.error_message();
+      RET_CHECK(tf_status.ok()) << "Run failed: " << tf_status.ToString();
    }

    cc->OutputSidePackets().Tag("SESSION").Set(Adopt(session.release()));
@@ -109,7 +109,7 @@ class TensorFlowSessionFromFrozenGraphGenerator : public PacketGenerator {

    RET_CHECK(graph_def.ParseFromString(graph_def_serialized));
    const tf::Status tf_status = session->session->Create(graph_def);
-    RET_CHECK(tf_status.ok()) << "Create failed: " << tf_status.error_message();
+    RET_CHECK(tf_status.ok()) << "Create failed: " << tf_status.ToString();

    for (const auto& key_value : options.tag_to_tensor_names()) {
      session->tag_to_tensor_map[key_value.first] = key_value.second;
@@ -119,7 +119,7 @@ class TensorFlowSessionFromFrozenGraphGenerator : public PacketGenerator {
          session->session->Run({}, {}, initialization_op_names, {});
      // RET_CHECK on the tf::Status object itself in order to print an
      // informative error message.
-      RET_CHECK(tf_status.ok()) << "Run failed: " << tf_status.error_message();
+      RET_CHECK(tf_status.ok()) << "Run failed: " << tf_status.ToString();
    }

    output_side_packets->Tag("SESSION") = Adopt(session.release());
@@ -17,7 +17,7 @@
 #if !defined(__ANDROID__)
 #include "mediapipe/framework/port/file_helpers.h"
 #endif
-#include "absl/strings/substitute.h"
+#include "absl/strings/str_replace.h"
 #include "mediapipe/calculators/tensorflow/tensorflow_session.h"
 #include "mediapipe/calculators/tensorflow/tensorflow_session_from_saved_model_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
@@ -51,10 +51,11 @@ static constexpr char kStringSavedModelPath[] = "STRING_SAVED_MODEL_PATH";
 #endif
 }

-// If options.convert_signature_to_tags() will convert letters to uppercase
-// and replace /'s with _'s. If set, this enables the standard SavedModel
-// classification, regression, and prediction signatures to be used as
-// uppercase INPUTS and OUTPUTS tags for streams.
+// If options.convert_signature_to_tags() is set, will convert letters to
+// uppercase and replace /'s and -'s with _'s. This enables the standard
+// SavedModel classification, regression, and prediction signatures to be used
+// as uppercase INPUTS and OUTPUTS tags for streams and supports other common
+// patterns.
 const std::string MaybeConvertSignatureToTag(
    const std::string& name,
    const TensorFlowSessionFromSavedModelCalculatorOptions& options) {
@@ -63,7 +64,8 @@ const std::string MaybeConvertSignatureToTag(
    output.resize(name.length());
    std::transform(name.begin(), name.end(), output.begin(),
                   [](unsigned char c) { return std::toupper(c); });
-    output = absl::Substitute(output, "/", "_");
+    output = absl::StrReplaceAll(output, {{"/", "_"}});
+    output = absl::StrReplaceAll(output, {{"-", "_"}});
    return output;
  } else {
    return name;
@@ -140,7 +142,7 @@ class TensorFlowSessionFromSavedModelCalculator : public CalculatorBase {
    if (!status.ok()) {
      return ::mediapipe::Status(
          static_cast<::mediapipe::StatusCode>(status.code()),
-          status.error_message());
+          status.ToString());
    }

    auto session = absl::make_unique<TensorFlowSession>();
@@ -32,8 +32,8 @@ message TensorFlowSessionFromSavedModelCalculatorOptions {
  // The name of the generic signature to load into the mapping from tags to
  // tensor names.
  optional string signature_name = 2 [default = "serving_default"];
-  // Whether to convert the signature keys to uppercase and switch /'s to
-  // _'s, which enables standard signatures to be used as Tags.
+  // Whether to convert the signature keys to uppercase as well as switch /'s
+  // and -'s to _'s, which enables common signatures to be used as Tags.
  optional bool convert_signature_to_tags = 3 [default = true];
  // If true, saved_model_path can have multiple exported models in
  // subdirectories saved_model_path/%08d and the alphabetically last (i.e.,
@@ -12,7 +12,7 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.

-#include "absl/strings/substitute.h"
+#include "absl/strings/str_replace.h"
 #include "mediapipe/calculators/tensorflow/tensorflow_session.h"
 #include "mediapipe/calculators/tensorflow/tensorflow_session_from_saved_model_calculator.pb.h"
 #include "mediapipe/framework/calculator.pb.h"
@@ -17,7 +17,7 @@
 #if !defined(__ANDROID__)
 #include "mediapipe/framework/port/file_helpers.h"
 #endif
-#include "absl/strings/substitute.h"
+#include "absl/strings/str_replace.h"
 #include "mediapipe/calculators/tensorflow/tensorflow_session.h"
 #include "mediapipe/calculators/tensorflow/tensorflow_session_from_saved_model_generator.pb.h"
 #include "mediapipe/framework/deps/file_path.h"
@@ -53,10 +53,11 @@ static constexpr char kStringSavedModelPath[] = "STRING_SAVED_MODEL_PATH";
 #endif
 }

-// If options.convert_signature_to_tags() will convert letters to uppercase
-// and replace /'s with _'s. If set, this enables the standard SavedModel
-// classification, regression, and prediction signatures to be used as
-// uppercase INPUTS and OUTPUTS tags for streams.
+// If options.convert_signature_to_tags() is set, will convert letters to
+// uppercase and replace /'s and -'s with _'s. This enables the standard
+// SavedModel classification, regression, and prediction signatures to be used
+// as uppercase INPUTS and OUTPUTS tags for streams and supports other common
+// patterns.
 const std::string MaybeConvertSignatureToTag(
    const std::string& name,
    const TensorFlowSessionFromSavedModelGeneratorOptions& options) {
@@ -65,7 +66,8 @@ const std::string MaybeConvertSignatureToTag(
    output.resize(name.length());
    std::transform(name.begin(), name.end(), output.begin(),
                   [](unsigned char c) { return std::toupper(c); });
-    output = absl::Substitute(output, "/", "_");
+    output = absl::StrReplaceAll(output, {{"/", "_"}});
+    output = absl::StrReplaceAll(output, {{"-", "_"}});
    return output;
  } else {
    return name;
@@ -135,7 +137,7 @@ class TensorFlowSessionFromSavedModelGenerator : public PacketGenerator {
    if (!status.ok()) {
      return ::mediapipe::Status(
          static_cast<::mediapipe::StatusCode>(status.code()),
-          status.error_message());
+          status.ToString());
    }

    auto session = absl::make_unique<TensorFlowSession>();
@@ -32,8 +32,8 @@ message TensorFlowSessionFromSavedModelGeneratorOptions {
  // The name of the generic signature to load into the mapping from tags to
  // tensor names.
  optional string signature_name = 2 [default = "serving_default"];
-  // Whether to convert the signature keys to uppercase and switch /'s to
-  // _'s, which enables standard signatures to be used as Tags.
+  // Whether to convert the signature keys to uppercase as well as switch /'s
+  // and -'s to _'s, which enables common signatures to be used as Tags.
  optional bool convert_signature_to_tags = 3 [default = true];
  // If true, saved_model_path can have multiple exported models in
  // subdirectories saved_model_path/%08d and the alphabetically last (i.e.,
@@ -12,7 +12,7 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.

-#include "absl/strings/substitute.h"
+#include "absl/strings/str_replace.h"
 #include "mediapipe/calculators/tensorflow/tensorflow_session.h"
 #include "mediapipe/calculators/tensorflow/tensorflow_session_from_saved_model_generator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
@@ -0,0 +1,126 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <memory>
+#include <string>
+#include <utility>
+
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/port/integral_types.h"
+#include "mediapipe/framework/port/logging.h"
+#include "mediapipe/framework/port/ret_check.h"
+#include "mediapipe/framework/port/status.h"
+#include "tensorflow/core/example/example.pb.h"
+#include "tensorflow/core/lib/core/status.h"
+#include "tensorflow/core/lib/io/record_reader.h"
+#include "tensorflow/core/platform/env.h"
+#include "tensorflow/core/platform/file_system.h"
+
+namespace mediapipe {
+
+const char kTFRecordPath[] = "TFRECORD_PATH";
+const char kRecordIndex[] = "RECORD_INDEX";
+const char kExampleTag[] = "EXAMPLE";
+const char kSequenceExampleTag[] = "SEQUENCE_EXAMPLE";
+
+// Reads a tensorflow example/sequence example from a tfrecord file.
+// If the "RECORD_INDEX" input side packet is provided, the calculator is going
+// to fetch the example/sequence example of the tfrecord file at the target
+// record index. Otherwise, the reader always reads the first example/sequence
+// example of the tfrecord file.
+//
+// Example config:
+// node {
+//   calculator: "TFRecordReaderCalculator"
+//   input_side_packet: "TFRECORD_PATH:tfrecord_path"
+//   input_side_packet: "RECORD_INDEX:record_index"
+//   output_side_packet: "SEQUENCE_EXAMPLE:sequence_example"
+// }
+class TFRecordReaderCalculator : public CalculatorBase {
+ public:
+  static ::mediapipe::Status GetContract(CalculatorContract* cc);
+
+  ::mediapipe::Status Open(CalculatorContext* cc) override;
+  ::mediapipe::Status Process(CalculatorContext* cc) override;
+};
+
+::mediapipe::Status TFRecordReaderCalculator::GetContract(
+    CalculatorContract* cc) {
+  cc->InputSidePackets().Tag(kTFRecordPath).Set<std::string>();
+  if (cc->InputSidePackets().HasTag(kRecordIndex)) {
+    cc->InputSidePackets().Tag(kRecordIndex).Set<int>();
+  }
+
+  RET_CHECK(cc->OutputSidePackets().HasTag(kExampleTag) ||
+            cc->OutputSidePackets().HasTag(kSequenceExampleTag))
+      << "TFRecordReaderCalculator must output either Tensorflow example or "
+         "sequence example.";
+  if (cc->OutputSidePackets().HasTag(kExampleTag)) {
+    cc->OutputSidePackets().Tag(kExampleTag).Set<tensorflow::Example>();
+  } else {
+    cc->OutputSidePackets()
+        .Tag(kSequenceExampleTag)
+        .Set<tensorflow::SequenceExample>();
+  }
+  return ::mediapipe::OkStatus();
+}
+
+::mediapipe::Status TFRecordReaderCalculator::Open(CalculatorContext* cc) {
+  std::unique_ptr<tensorflow::RandomAccessFile> file;
+  auto tf_status = tensorflow::Env::Default()->NewRandomAccessFile(
+      cc->InputSidePackets().Tag(kTFRecordPath).Get<std::string>(), &file);
+  RET_CHECK(tf_status.ok())
+      << "Failed to open tfrecord file: " << tf_status.ToString();
+  tensorflow::io::RecordReader reader(file.get(),
+                                      tensorflow::io::RecordReaderOptions());
+  tensorflow::uint64 offset = 0;
+  tensorflow::tstring example_str;
+  const int target_idx =
+      cc->InputSidePackets().HasTag(kRecordIndex)
+          ? cc->InputSidePackets().Tag(kRecordIndex).Get<int>()
+          : 0;
+  int current_idx = 0;
+  while (current_idx <= target_idx) {
+    tf_status = reader.ReadRecord(&offset, &example_str);
+    RET_CHECK(tf_status.ok())
+        << "Failed to read tfrecord: " << tf_status.ToString();
+    if (current_idx == target_idx) {
+      if (cc->OutputSidePackets().HasTag(kExampleTag)) {
+        tensorflow::Example tf_example;
+        tf_example.ParseFromArray(example_str.data(), example_str.size());
+        cc->OutputSidePackets()
+            .Tag(kExampleTag)
+            .Set(MakePacket<tensorflow::Example>(std::move(tf_example)));
+      } else {
+        tensorflow::SequenceExample tf_sequence_example;
+        tf_sequence_example.ParseFromString(example_str);
+        cc->OutputSidePackets()
+            .Tag(kSequenceExampleTag)
+            .Set(MakePacket<tensorflow::SequenceExample>(
+                std::move(tf_sequence_example)));
+      }
+    }
+    ++current_idx;
+  }
+
+  return ::mediapipe::OkStatus();
+}
+
+::mediapipe::Status TFRecordReaderCalculator::Process(CalculatorContext* cc) {
+  return ::mediapipe::OkStatus();
+}
+
+REGISTER_CALCULATOR(TFRecordReaderCalculator);
+
+}  // namespace mediapipe
@@ -0,0 +1,192 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <iterator>
+
+#include "mediapipe/calculators/tensorflow/lapped_tensor_buffer_calculator.pb.h"
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/packet.h"
+#include "mediapipe/framework/port/canonical_errors.h"
+#include "tensorflow/core/example/example.pb.h"
+#include "tensorflow/core/example/feature.pb.h"
+
+namespace mediapipe {
+namespace {
+
+const char kId[] = "id";
+const char kRgb[] = "rgb";
+const char kAudio[] = "audio";
+const char kDesiredSegmentSize[] = "DESIRED_SEGMENT_SIZE";
+const char kYt8mId[] = "YT8M_ID";
+const char kYt8mSequenceExample[] = "YT8M_SEQUENCE_EXAMPLE";
+const char kQuantizedRgbFeature[] = "QUANTIZED_RGB_FEATURE";
+const char kQuantizedAudioFeature[] = "QUANTIZED_AUDIO_FEATURE";
+const char kSegmentSize[] = "SEGMENT_SIZE";
+const char kLappedTensorBufferCalculatorOptions[] =
+    "LAPPED_TENSOR_BUFFER_CALCULATOR_OPTIONS";
+
+std::string GetQuantizedFeature(
+    const tensorflow::SequenceExample& sequence_example, const std::string& key,
+    int index) {
+  const auto& bytes_list = sequence_example.feature_lists()
+                               .feature_list()
+                               .at(key)
+                               .feature()
+                               .Get(index)
+                               .bytes_list()
+                               .value();
+  CHECK_EQ(1, bytes_list.size());
+  return bytes_list.Get(0);
+}
+}  // namespace
+
+// Unpacks YT8M Sequence Example. Note that the audio feature and rgb feature
+// output are quantized. DequantizeByteArrayCalculator can do the dequantization
+// for you.
+//
+// Example config:
+// node {
+//   calculator: "UnpackYt8mSequenceExampleCalculator"
+//   input_side_packet: "YT8M_SEQUENCE_EXAMPLE:yt8m_sequence_example"
+//   output_stream: "QUANTIZED_RGB_FEATURE:quantized_rgb_feature"
+//   output_stream: "QUANTIZED_AUDIO_FEATURE:quantized_audio_feature"
+// }
+class UnpackYt8mSequenceExampleCalculator : public CalculatorBase {
+ public:
+  static ::mediapipe::Status GetContract(CalculatorContract* cc) {
+    cc->InputSidePackets()
+        .Tag(kYt8mSequenceExample)
+        .Set<tensorflow::SequenceExample>();
+    if (cc->InputSidePackets().HasTag(kDesiredSegmentSize)) {
+      cc->InputSidePackets().Tag(kDesiredSegmentSize).Set<int>();
+    }
+    cc->Outputs().Tag(kQuantizedRgbFeature).Set<std::string>();
+    cc->Outputs().Tag(kQuantizedAudioFeature).Set<std::string>();
+    if (cc->OutputSidePackets().HasTag(kYt8mId)) {
+      cc->OutputSidePackets().Tag(kYt8mId).Set<std::string>();
+    }
+    if (cc->OutputSidePackets().HasTag(kLappedTensorBufferCalculatorOptions)) {
+      cc->OutputSidePackets()
+          .Tag(kLappedTensorBufferCalculatorOptions)
+          .Set<::mediapipe::LappedTensorBufferCalculatorOptions>();
+    }
+    if (cc->OutputSidePackets().HasTag(kSegmentSize)) {
+      cc->OutputSidePackets().Tag(kSegmentSize).Set<int>();
+    }
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Open(CalculatorContext* cc) override {
+    const tensorflow::SequenceExample& sequence_example =
+        cc->InputSidePackets()
+            .Tag(kYt8mSequenceExample)
+            .Get<tensorflow::SequenceExample>();
+    const std::string& yt8m_id =
+        sequence_example.context().feature().at(kId).bytes_list().value().Get(
+            0);
+    if (cc->OutputSidePackets().HasTag(kYt8mId)) {
+      cc->OutputSidePackets().Tag(kYt8mId).Set(
+          MakePacket<std::string>(yt8m_id));
+    }
+
+    int rgb_feature_list_length =
+        sequence_example.feature_lists().feature_list().at(kRgb).feature_size();
+    int audio_feature_list_length = sequence_example.feature_lists()
+                                        .feature_list()
+                                        .at(kAudio)
+                                        .feature_size();
+
+    if (rgb_feature_list_length != audio_feature_list_length) {
+      return ::mediapipe::FailedPreconditionError(absl::StrCat(
+          "Data corruption: the length of audio features and rgb features are "
+          "not equal. Please check the sequence example that contains yt8m "
+          "id: ",
+          yt8m_id));
+    }
+    feature_list_length_ = rgb_feature_list_length;
+    if (cc->OutputSidePackets().HasTag(kLappedTensorBufferCalculatorOptions) ||
+        cc->OutputSidePackets().HasTag(kSegmentSize)) {
+      // If the desired segment size is specified, take the min of the length of
+      // the feature list and the desired size to be the output segment size.
+      int segment_size = feature_list_length_;
+      if (cc->InputSidePackets().HasTag(kDesiredSegmentSize)) {
+        int desired_segment_size =
+            cc->InputSidePackets().Tag(kDesiredSegmentSize).Get<int>();
+        RET_CHECK(desired_segment_size > 0)
+            << "The desired segment size must be greater than zero.";
+        segment_size = std::min(
+            feature_list_length_,
+            cc->InputSidePackets().Tag(kDesiredSegmentSize).Get<int>());
+      }
+      if (cc->OutputSidePackets().HasTag(
+              kLappedTensorBufferCalculatorOptions)) {
+        auto lapped_tensor_buffer_calculator_options = absl::make_unique<
+            ::mediapipe::LappedTensorBufferCalculatorOptions>();
+        lapped_tensor_buffer_calculator_options->set_add_batch_dim_to_tensors(
+            true);
+        lapped_tensor_buffer_calculator_options->set_buffer_size(segment_size);
+        lapped_tensor_buffer_calculator_options->set_overlap(segment_size - 1);
+        lapped_tensor_buffer_calculator_options->set_timestamp_offset(
+            segment_size - 1);
+        cc->OutputSidePackets()
+            .Tag(kLappedTensorBufferCalculatorOptions)
+            .Set(Adopt(lapped_tensor_buffer_calculator_options.release()));
+      }
+      if (cc->OutputSidePackets().HasTag(kSegmentSize)) {
+        cc->OutputSidePackets()
+            .Tag(kSegmentSize)
+            .Set(MakePacket<int>(segment_size));
+      }
+    }
+    LOG(INFO) << "Reading the sequence example that contains yt8m id: "
+              << yt8m_id << ". Feature list length: " << feature_list_length_;
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Process(CalculatorContext* cc) override {
+    if (current_index_ >= feature_list_length_) {
+      return ::mediapipe::tool::StatusStop();
+    }
+    const tensorflow::SequenceExample& sequence_example =
+        cc->InputSidePackets()
+            .Tag(kYt8mSequenceExample)
+            .Get<tensorflow::SequenceExample>();
+
+    // Uses microsecond as the unit of time. In the YT8M dataset, each feature
+    // represents a second.
+    const Timestamp timestamp = Timestamp(current_index_ * 1000000);
+    cc->Outputs()
+        .Tag(kQuantizedRgbFeature)
+        .AddPacket(
+            MakePacket<std::string>(
+                GetQuantizedFeature(sequence_example, kRgb, current_index_))
+                .At(timestamp));
+    cc->Outputs()
+        .Tag(kQuantizedAudioFeature)
+        .AddPacket(
+            MakePacket<std::string>(
+                GetQuantizedFeature(sequence_example, kAudio, current_index_))
+                .At(timestamp));
+    ++current_index_;
+    return ::mediapipe::OkStatus();
+  }
+
+ private:
+  int current_index_ = 0;
+  int feature_list_length_ = 0;
+};
+
+REGISTER_CALCULATOR(UnpackYt8mSequenceExampleCalculator);
+
+}  // namespace mediapipe
@@ -23,10 +23,12 @@

 namespace mediapipe {

-namespace tf = ::tensorflow;
-
+namespace {
 auto& INPUT_1D = VectorFloatToTensorCalculatorOptions::INPUT_1D;
 auto& INPUT_2D = VectorFloatToTensorCalculatorOptions::INPUT_2D;
+}  // namespace
+
+namespace tf = ::tensorflow;

 // The calculator expects one input (a packet containing a vector<float> or
 // vector<vector<float>>) and generates one output (a packet containing a
@@ -0,0 +1,203 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//
+// Converts a single int or vector<int> or vector<vector<int>> to 1D (or 2D)
+// tf::Tensor.
+
+#include "mediapipe/calculators/tensorflow/vector_int_to_tensor_calculator_options.pb.h"
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/port/ret_check.h"
+#include "mediapipe/framework/port/status.h"
+#include "tensorflow/core/framework/tensor.h"
+#include "tensorflow/core/framework/types.h"
+
+namespace mediapipe {
+
+const char kVectorInt[] = "VECTOR_INT";
+const char kSingleInt[] = "SINGLE_INT";
+const char kTensorOut[] = "TENSOR_OUT";
+
+namespace {
+auto& INPUT_1D = VectorIntToTensorCalculatorOptions::INPUT_1D;
+auto& INPUT_2D = VectorIntToTensorCalculatorOptions::INPUT_2D;
+}  // namespace
+
+namespace tf = ::tensorflow;
+
+template <typename TensorType>
+void AssignMatrixValue(int r, int c, int value, tf::Tensor* output_tensor) {
+  output_tensor->tensor<TensorType, 2>()(r, c) = value;
+}
+
+// The calculator expects one input (a packet containing a single int or
+// vector<int> or vector<vector<int>>) and generates one output (a packet
+// containing a tf::Tensor containing the same data). The output tensor will be
+// either 1D or 2D with dimensions corresponding to the input vector int. It
+// will hold DT_INT32 or DT_UINT8 or DT_INT64 values.
+//
+// Example config:
+// node {
+//  calculator: "VectorIntToTensorCalculator"
+//   input_stream: "SINGLE_INT:segment_size_int_stream"
+//   output_stream: "TENSOR_OUT:segment_size_tensor"
+// }
+//
+// or
+//
+// node {
+//   calculator: "VectorIntToTensorCalculator"
+//   input_stream: "VECTOR_INT:vector_int_features"
+//   output_stream: "TENSOR_OUT:tensor_features"
+// }
+class VectorIntToTensorCalculator : public CalculatorBase {
+ public:
+  static ::mediapipe::Status GetContract(CalculatorContract* cc);
+
+  ::mediapipe::Status Open(CalculatorContext* cc) override;
+  ::mediapipe::Status Process(CalculatorContext* cc) override;
+
+ private:
+  VectorIntToTensorCalculatorOptions options_;
+};
+REGISTER_CALCULATOR(VectorIntToTensorCalculator);
+
+::mediapipe::Status VectorIntToTensorCalculator::GetContract(
+    CalculatorContract* cc) {
+  const auto& options = cc->Options<VectorIntToTensorCalculatorOptions>();
+  // Start with only one input packet.
+  RET_CHECK_EQ(cc->Inputs().NumEntries(), 1)
+      << "Only one input stream is supported.";
+  if (options.input_size() == INPUT_2D) {
+    cc->Inputs().Tag(kVectorInt).Set<std::vector<std::vector<int>>>();
+  } else if (options.input_size() == INPUT_1D) {
+    if (cc->Inputs().HasTag(kSingleInt)) {
+      cc->Inputs().Tag(kSingleInt).Set<int>();
+    } else {
+      cc->Inputs().Tag(kVectorInt).Set<std::vector<int>>();
+    }
+  } else {
+    LOG(FATAL) << "input size not supported";
+  }
+  RET_CHECK_EQ(cc->Outputs().NumEntries(), 1)
+      << "Only one output stream is supported.";
+  cc->Outputs().Tag(kTensorOut).Set<tf::Tensor>();
+  return ::mediapipe::OkStatus();
+}
+
+::mediapipe::Status VectorIntToTensorCalculator::Open(CalculatorContext* cc) {
+  options_ = cc->Options<VectorIntToTensorCalculatorOptions>();
+  RET_CHECK(options_.tensor_data_type() == tf::DT_UINT8 ||
+            options_.tensor_data_type() == tf::DT_INT32 ||
+            options_.tensor_data_type() == tf::DT_INT64)
+      << "Output tensor data type is not supported.";
+  return ::mediapipe::OkStatus();
+}
+
+::mediapipe::Status VectorIntToTensorCalculator::Process(
+    CalculatorContext* cc) {
+  tf::TensorShape tensor_shape;
+  if (options_.input_size() == INPUT_2D) {
+    const std::vector<std::vector<int>>& input =
+        cc->Inputs()
+            .Tag(kVectorInt)
+            .Value()
+            .Get<std::vector<std::vector<int>>>();
+
+    const int32 rows = input.size();
+    CHECK_GE(rows, 1);
+    const int32 cols = input[0].size();
+    CHECK_GE(cols, 1);
+    for (int i = 1; i < rows; ++i) {
+      CHECK_EQ(input[i].size(), cols);
+    }
+    if (options_.transpose()) {
+      tensor_shape = tf::TensorShape({cols, rows});
+    } else {
+      tensor_shape = tf::TensorShape({rows, cols});
+    }
+    auto output = ::absl::make_unique<tf::Tensor>(options_.tensor_data_type(),
+                                                  tensor_shape);
+    if (options_.transpose()) {
+      for (int r = 0; r < rows; ++r) {
+        for (int c = 0; c < cols; ++c) {
+          switch (options_.tensor_data_type()) {
+            case tf::DT_INT64:
+              AssignMatrixValue<tf::int64>(c, r, input[r][c], output.get());
+              break;
+            case tf::DT_UINT8:
+              AssignMatrixValue<uint8>(c, r, input[r][c], output.get());
+              break;
+            case tf::DT_INT32:
+              AssignMatrixValue<int>(c, r, input[r][c], output.get());
+              break;
+            default:
+              LOG(FATAL) << "tensor data type is not supported.";
+          }
+        }
+      }
+    } else {
+      for (int r = 0; r < rows; ++r) {
+        for (int c = 0; c < cols; ++c) {
+          switch (options_.tensor_data_type()) {
+            case tf::DT_INT64:
+              AssignMatrixValue<tf::int64>(r, c, input[r][c], output.get());
+              break;
+            case tf::DT_UINT8:
+              AssignMatrixValue<uint8>(r, c, input[r][c], output.get());
+              break;
+            case tf::DT_INT32:
+              AssignMatrixValue<int>(r, c, input[r][c], output.get());
+              break;
+            default:
+              LOG(FATAL) << "tensor data type is not supported.";
+          }
+        }
+      }
+    }
+    cc->Outputs().Tag(kTensorOut).Add(output.release(), cc->InputTimestamp());
+  } else if (options_.input_size() == INPUT_1D) {
+    std::vector<int> input;
+    if (cc->Inputs().HasTag(kSingleInt)) {
+      input.push_back(cc->Inputs().Tag(kSingleInt).Get<int>());
+    } else {
+      input = cc->Inputs().Tag(kVectorInt).Value().Get<std::vector<int>>();
+    }
+    CHECK_GE(input.size(), 1);
+    const int32 length = input.size();
+    tensor_shape = tf::TensorShape({length});
+    auto output = ::absl::make_unique<tf::Tensor>(options_.tensor_data_type(),
+                                                  tensor_shape);
+    for (int i = 0; i < length; ++i) {
+      switch (options_.tensor_data_type()) {
+        case tf::DT_INT64:
+          output->tensor<tf::int64, 1>()(i) = input.at(i);
+          break;
+        case tf::DT_UINT8:
+          output->tensor<uint8, 1>()(i) = input.at(i);
+          break;
+        case tf::DT_INT32:
+          output->tensor<int, 1>()(i) = input.at(i);
+          break;
+        default:
+          LOG(FATAL) << "tensor data type is not supported.";
+      }
+    }
+    cc->Outputs().Tag(kTensorOut).Add(output.release(), cc->InputTimestamp());
+  } else {
+    LOG(FATAL) << "input size not supported";
+  }
+  return ::mediapipe::OkStatus();
+}
+
+}  // namespace mediapipe
@@ -0,0 +1,43 @@
+// Copyright 2019 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+syntax = "proto2";
+
+package mediapipe;
+
+import "mediapipe/framework/calculator.proto";
+import "tensorflow/core/framework/types.proto";
+
+message VectorIntToTensorCalculatorOptions {
+  extend mediapipe.CalculatorOptions {
+    optional VectorIntToTensorCalculatorOptions ext = 275364184;
+  }
+  enum InputSize {
+    UNKNOWN = 0;
+    INPUT_1D = 1;
+    INPUT_2D = 2;
+  }
+
+  // If input_size is INPUT_2D, unpack a vector<vector<int>> to a
+  // 2d tensor (matrix). If INPUT_1D, convert a single int or vector<int>
+  // into a 1d tensor (vector).
+  optional InputSize input_size = 1 [default = INPUT_1D];
+
+  // If true, the output tensor is transposed.
+  // Otherwise, the output tensor is not transposed.
+  // It will be ignored if tensor_is_2d is INPUT_1D.
+  optional bool transpose = 2 [default = false];
+
+  optional tensorflow.DataType tensor_data_type = 3 [default = DT_INT32];
+}
@@ -0,0 +1,202 @@
+// Copyright 2018 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "mediapipe/calculators/tensorflow/vector_int_to_tensor_calculator_options.pb.h"
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/calculator_runner.h"
+#include "mediapipe/framework/port/gmock.h"
+#include "mediapipe/framework/port/gtest.h"
+#include "tensorflow/core/framework/tensor.h"
+#include "tensorflow/core/framework/types.pb.h"
+
+namespace mediapipe {
+
+namespace {
+
+namespace tf = ::tensorflow;
+
+class VectorIntToTensorCalculatorTest : public ::testing::Test {
+ protected:
+  void SetUpRunner(
+      const VectorIntToTensorCalculatorOptions::InputSize input_size,
+      const tensorflow::DataType tensor_data_type, const bool transpose,
+      const bool single_value) {
+    CalculatorGraphConfig::Node config;
+    config.set_calculator("VectorIntToTensorCalculator");
+    if (single_value) {
+      config.add_input_stream("SINGLE_INT:input_int");
+    } else {
+      config.add_input_stream("VECTOR_INT:input_int");
+    }
+    config.add_output_stream("TENSOR_OUT:output_tensor");
+    auto options = config.mutable_options()->MutableExtension(
+        VectorIntToTensorCalculatorOptions::ext);
+    options->set_input_size(input_size);
+    options->set_transpose(transpose);
+    options->set_tensor_data_type(tensor_data_type);
+    runner_ = ::absl::make_unique<CalculatorRunner>(config);
+  }
+
+  void TestConvertFromVectoVectorInt(const bool transpose) {
+    SetUpRunner(VectorIntToTensorCalculatorOptions::INPUT_2D,
+                tensorflow::DT_INT32, transpose, false);
+    auto input = ::absl::make_unique<std::vector<std::vector<int>>>(
+        2, std::vector<int>(2));
+    for (int i = 0; i < 2; ++i) {
+      for (int j = 0; j < 2; ++j) {
+        input->at(i).at(j) = i * 2 + j;
+      }
+    }
+
+    const int64 time = 1234;
+    runner_->MutableInputs()
+        ->Tag("VECTOR_INT")
+        .packets.push_back(Adopt(input.release()).At(Timestamp(time)));
+
+    EXPECT_TRUE(runner_->Run().ok());
+
+    const std::vector<Packet>& output_packets =
+        runner_->Outputs().Tag("TENSOR_OUT").packets;
+    EXPECT_EQ(1, output_packets.size());
+    EXPECT_EQ(time, output_packets[0].Timestamp().Value());
+    const tf::Tensor& output_tensor = output_packets[0].Get<tf::Tensor>();
+
+    EXPECT_EQ(2, output_tensor.dims());
+    EXPECT_EQ(tf::DT_INT32, output_tensor.dtype());
+    const auto matrix = output_tensor.matrix<int>();
+
+    for (int i = 0; i < 2; ++i) {
+      for (int j = 0; j < 2; ++j) {
+        if (!transpose) {
+          EXPECT_EQ(i * 2 + j, matrix(i, j));
+        } else {
+          EXPECT_EQ(j * 2 + i, matrix(i, j));
+        }
+      }
+    }
+  }
+
+  std::unique_ptr<CalculatorRunner> runner_;
+};
+
+TEST_F(VectorIntToTensorCalculatorTest, TestSingleValue) {
+  SetUpRunner(VectorIntToTensorCalculatorOptions::INPUT_1D,
+              tensorflow::DT_INT32, false, true);
+  const int64 time = 1234;
+  runner_->MutableInputs()
+      ->Tag("SINGLE_INT")
+      .packets.push_back(MakePacket<int>(1).At(Timestamp(time)));
+
+  EXPECT_TRUE(runner_->Run().ok());
+
+  const std::vector<Packet>& output_packets =
+      runner_->Outputs().Tag("TENSOR_OUT").packets;
+  EXPECT_EQ(1, output_packets.size());
+  EXPECT_EQ(time, output_packets[0].Timestamp().Value());
+  const tf::Tensor& output_tensor = output_packets[0].Get<tf::Tensor>();
+
+  EXPECT_EQ(1, output_tensor.dims());
+  EXPECT_EQ(tf::DT_INT32, output_tensor.dtype());
+  const auto vec = output_tensor.vec<int32>();
+  EXPECT_EQ(1, vec(0));
+}
+
+TEST_F(VectorIntToTensorCalculatorTest, TesOneDim) {
+  SetUpRunner(VectorIntToTensorCalculatorOptions::INPUT_1D,
+              tensorflow::DT_INT32, false, false);
+  auto input = ::absl::make_unique<std::vector<int>>(5);
+  for (int i = 0; i < 5; ++i) {
+    input->at(i) = i;
+  }
+  const int64 time = 1234;
+  runner_->MutableInputs()
+      ->Tag("VECTOR_INT")
+      .packets.push_back(Adopt(input.release()).At(Timestamp(time)));
+
+  EXPECT_TRUE(runner_->Run().ok());
+
+  const std::vector<Packet>& output_packets =
+      runner_->Outputs().Tag("TENSOR_OUT").packets;
+  EXPECT_EQ(1, output_packets.size());
+  EXPECT_EQ(time, output_packets[0].Timestamp().Value());
+  const tf::Tensor& output_tensor = output_packets[0].Get<tf::Tensor>();
+
+  EXPECT_EQ(1, output_tensor.dims());
+  EXPECT_EQ(tf::DT_INT32, output_tensor.dtype());
+  const auto vec = output_tensor.vec<int32>();
+
+  for (int i = 0; i < 5; ++i) {
+    EXPECT_EQ(i, vec(i));
+  }
+}
+
+TEST_F(VectorIntToTensorCalculatorTest, TestTwoDims) {
+  for (bool transpose : {false, true}) {
+    TestConvertFromVectoVectorInt(transpose);
+  }
+}
+
+TEST_F(VectorIntToTensorCalculatorTest, TestInt64) {
+  SetUpRunner(VectorIntToTensorCalculatorOptions::INPUT_1D,
+              tensorflow::DT_INT64, false, true);
+  const int64 time = 1234;
+  runner_->MutableInputs()
+      ->Tag("SINGLE_INT")
+      .packets.push_back(MakePacket<int>(2 ^ 31).At(Timestamp(time)));
+
+  EXPECT_TRUE(runner_->Run().ok());
+
+  const std::vector<Packet>& output_packets =
+      runner_->Outputs().Tag("TENSOR_OUT").packets;
+  EXPECT_EQ(1, output_packets.size());
+  EXPECT_EQ(time, output_packets[0].Timestamp().Value());
+  const tf::Tensor& output_tensor = output_packets[0].Get<tf::Tensor>();
+
+  EXPECT_EQ(1, output_tensor.dims());
+  EXPECT_EQ(tf::DT_INT64, output_tensor.dtype());
+  const auto vec = output_tensor.vec<tf::int64>();
+  EXPECT_EQ(2 ^ 31, vec(0));
+}
+
+TEST_F(VectorIntToTensorCalculatorTest, TestUint8) {
+  SetUpRunner(VectorIntToTensorCalculatorOptions::INPUT_1D,
+              tensorflow::DT_UINT8, false, false);
+  auto input = ::absl::make_unique<std::vector<int>>(5);
+  for (int i = 0; i < 5; ++i) {
+    input->at(i) = i;
+  }
+  const int64 time = 1234;
+  runner_->MutableInputs()
+      ->Tag("VECTOR_INT")
+      .packets.push_back(Adopt(input.release()).At(Timestamp(time)));
+
+  EXPECT_TRUE(runner_->Run().ok());
+
+  const std::vector<Packet>& output_packets =
+      runner_->Outputs().Tag("TENSOR_OUT").packets;
+  EXPECT_EQ(1, output_packets.size());
+  EXPECT_EQ(time, output_packets[0].Timestamp().Value());
+  const tf::Tensor& output_tensor = output_packets[0].Get<tf::Tensor>();
+
+  EXPECT_EQ(1, output_tensor.dims());
+  EXPECT_EQ(tf::DT_UINT8, output_tensor.dtype());
+  const auto vec = output_tensor.vec<uint8>();
+
+  for (int i = 0; i < 5; ++i) {
+    EXPECT_EQ(i, vec(i));
+  }
+}
+
+}  // namespace
+}  // namespace mediapipe
@@ -13,12 +13,12 @@
 # limitations under the License.
 #

+load("//mediapipe/framework/port:build_config.bzl", "mediapipe_cc_proto_library")
+
 licenses(["notice"])  # Apache 2.0

 package(default_visibility = ["//visibility:private"])

-load("//mediapipe/framework/port:build_config.bzl", "mediapipe_cc_proto_library")
-
 proto_library(
    name = "ssd_anchors_calculator_proto",
    srcs = ["ssd_anchors_calculator.proto"],
@@ -222,9 +222,11 @@ cc_library(
    deps = [
        ":util",
        ":tflite_inference_calculator_cc_proto",
+        "@com_google_absl//absl/memory",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/util:resource_util",
        "@org_tensorflow//tensorflow/lite:framework",
+        "@org_tensorflow//tensorflow/lite/delegates/xnnpack:xnnpack_delegate",
        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
        "//mediapipe/framework/stream_handler:fixed_size_input_stream_handler",
        "//mediapipe/framework/port:ret_check",
@@ -238,6 +240,7 @@ cc_library(
            "@org_tensorflow//tensorflow/lite/delegates/gpu/common:shape",
            "@org_tensorflow//tensorflow/lite/delegates/gpu/metal:buffer_convert",
            "@org_tensorflow//tensorflow/lite/delegates/gpu:metal_delegate",
+            "@org_tensorflow//tensorflow/lite/delegates/gpu:metal_delegate_internal",
        ],
        "//conditions:default": [
            "//mediapipe/gpu:gl_calculator_helper",
@@ -248,6 +251,15 @@ cc_library(
            "@org_tensorflow//tensorflow/lite/delegates/gpu/gl:gl_program",
            "@org_tensorflow//tensorflow/lite/delegates/gpu/gl:gl_shader",
        ],
+    }) + select({
+        "//conditions:default": [],
+        "//mediapipe:android": [
+            "@org_tensorflow//tensorflow/lite/delegates/nnapi:nnapi_delegate",
+        ],
+    }) + select({
+        "//conditions:default": [
+            "//mediapipe/util:cpu_util",
+        ],
    }),
    alwayslink = 1,
 )
@@ -302,6 +314,20 @@ cc_library(
    alwayslink = 1,
 )

+cc_library(
+    name = "tflite_model_calculator",
+    srcs = ["tflite_model_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        ":util",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:packet",
+        "//mediapipe/framework/port:ret_check",
+        "@org_tensorflow//tensorflow/lite:framework",
+    ],
+    alwayslink = 1,
+)
+
 cc_library(
    name = "tflite_tensors_to_segmentation_calculator",
    srcs = ["tflite_tensors_to_segmentation_calculator.cc"],
@@ -425,7 +451,7 @@ cc_library(
        "//mediapipe:android": [
            "//mediapipe/util/android/file/base",
        ],
-        "//mediapipe:apple": [
+        "//mediapipe:ios": [
            "//mediapipe/util/android/file/base",
        ],
        "//mediapipe:macos": [
@@ -472,6 +498,9 @@ cc_test(
    deps = [
        ":tflite_inference_calculator",
        ":tflite_inference_calculator_cc_proto",
+        ":tflite_model_calculator",
+        "//mediapipe/calculators/core:constant_side_packet_calculator",
+        "//mediapipe/calculators/util:local_file_contents_calculator",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:calculator_runner",
        "//mediapipe/framework/deps:file_path",
@@ -479,6 +508,9 @@ cc_test(
        "//mediapipe/framework/port:integral_types",
        "//mediapipe/framework/port:parse_text_proto",
        "//mediapipe/framework/tool:validate_type",
+        "@com_google_absl//absl/memory",
+        "@com_google_absl//absl/strings",
+        "@com_google_absl//absl/types:optional",
        "@org_tensorflow//tensorflow/lite:framework",
        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
    ],
@@ -504,3 +536,19 @@ cc_test(
        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
    ],
 )
+
+cc_test(
+    name = "tflite_model_calculator_test",
+    srcs = ["tflite_model_calculator_test.cc"],
+    data = ["testdata/add.bin"],
+    deps = [
+        ":tflite_model_calculator",
+        "//mediapipe/calculators/core:constant_side_packet_calculator",
+        "//mediapipe/calculators/util:local_file_contents_calculator",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:calculator_runner",
+        "//mediapipe/framework/port:gtest_main",
+        "//mediapipe/framework/port:parse_text_proto",
+        "@org_tensorflow//tensorflow/lite:framework",
+    ],
+)
@@ -25,7 +25,7 @@
 #include "tensorflow/lite/error_reporter.h"
 #include "tensorflow/lite/interpreter.h"

-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
 #include "mediapipe/gpu/gl_calculator_helper.h"
 #include "mediapipe/gpu/gpu_buffer.h"
 #include "tensorflow/lite/delegates/gpu/gl/gl_buffer.h"
@@ -34,7 +34,7 @@
 #include "tensorflow/lite/delegates/gpu/gl_delegate.h"
 #endif  //  !MEDIAPIPE_DISABLE_GPU

-#if defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#if defined(MEDIAPIPE_IOS)
 #import <CoreVideo/CoreVideo.h>
 #import <Metal/Metal.h>
 #import <MetalKit/MetalKit.h>
@@ -45,9 +45,9 @@
 #include "tensorflow/lite/delegates/gpu/metal_delegate.h"
 #endif  // iOS

-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
 typedef ::tflite::gpu::gl::GlBuffer GpuTensor;
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
 typedef id<MTLBuffer> GpuTensor;
 #endif

@@ -67,7 +67,7 @@ typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::ColMajor>

 namespace mediapipe {

-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
 using ::tflite::gpu::gl::CreateReadWriteShaderStorageBuffer;
 using ::tflite::gpu::gl::GlProgram;
 using ::tflite::gpu::gl::GlShader;
@@ -77,7 +77,7 @@ struct GPUData {
  GlShader shader;
  GlProgram program;
 };
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
 struct GPUData {
  int elements = 1;
  GpuTensor buffer;
@@ -146,10 +146,10 @@ class TfLiteConverterCalculator : public CalculatorBase {

  std::unique_ptr<tflite::Interpreter> interpreter_ = nullptr;

-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  mediapipe::GlCalculatorHelper gpu_helper_;
  std::unique_ptr<GPUData> gpu_data_out_;
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
  MPPMetalHelper* gpu_helper_ = nullptr;
  std::unique_ptr<GPUData> gpu_data_out_;
 #endif
@@ -181,7 +181,7 @@ REGISTER_CALCULATOR(TfLiteConverterCalculator);

  if (cc->Inputs().HasTag("IMAGE")) cc->Inputs().Tag("IMAGE").Set<ImageFrame>();
  if (cc->Inputs().HasTag("MATRIX")) cc->Inputs().Tag("MATRIX").Set<Matrix>();
-#if !defined(MEDIAPIPE_DISABLE_GPU)
+#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__EMSCRIPTEN__)
  if (cc->Inputs().HasTag("IMAGE_GPU")) {
    cc->Inputs().Tag("IMAGE_GPU").Set<mediapipe::GpuBuffer>();
    use_gpu |= true;
@@ -190,7 +190,7 @@ REGISTER_CALCULATOR(TfLiteConverterCalculator);

  if (cc->Outputs().HasTag("TENSORS"))
    cc->Outputs().Tag("TENSORS").Set<std::vector<TfLiteTensor>>();
-#if !defined(MEDIAPIPE_DISABLE_GPU)
+#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__EMSCRIPTEN__)
  if (cc->Outputs().HasTag("TENSORS_GPU")) {
    cc->Outputs().Tag("TENSORS_GPU").Set<std::vector<GpuTensor>>();
    use_gpu |= true;
@@ -198,9 +198,9 @@ REGISTER_CALCULATOR(TfLiteConverterCalculator);
 #endif  //  !MEDIAPIPE_DISABLE_GPU

  if (use_gpu) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
    MP_RETURN_IF_ERROR(mediapipe::GlCalculatorHelper::UpdateContract(cc));
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
    MP_RETURN_IF_ERROR([MPPMetalHelper updateContract:cc]);
 #endif
  }
@@ -218,7 +218,7 @@ REGISTER_CALCULATOR(TfLiteConverterCalculator);

  if (cc->Inputs().HasTag("IMAGE_GPU") ||
      cc->Outputs().HasTag("IMAGE_OUT_GPU")) {
-#if !defined(MEDIAPIPE_DISABLE_GPU)
+#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__EMSCRIPTEN__)
    use_gpu_ = true;
 #else
    RET_CHECK_FAIL() << "GPU processing not enabled.";
@@ -231,9 +231,9 @@ REGISTER_CALCULATOR(TfLiteConverterCalculator);
              cc->Outputs().HasTag("TENSORS_GPU"));
    // Cannot use quantization.
    use_quantized_tensors_ = false;
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
    MP_RETURN_IF_ERROR(gpu_helper_.Open(cc));
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
    gpu_helper_ = [[MPPMetalHelper alloc] initWithCalculatorContext:cc];
    RET_CHECK(gpu_helper_);
 #endif
@@ -264,10 +264,10 @@ REGISTER_CALCULATOR(TfLiteConverterCalculator);
 }

 ::mediapipe::Status TfLiteConverterCalculator::Close(CalculatorContext* cc) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  gpu_helper_.RunInGlContext([this] { gpu_data_out_.reset(); });
 #endif
-#if defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#if defined(MEDIAPIPE_IOS)
  gpu_data_out_.reset();
 #endif
  return ::mediapipe::OkStatus();
@@ -294,11 +294,15 @@ REGISTER_CALCULATOR(TfLiteConverterCalculator);
      if (use_quantized_tensors_) {
        RET_CHECK(image_frame.Format() != mediapipe::ImageFormat::VEC32F1)
            << "Only 8-bit input images are supported for quantization.";
+        quant.type = kTfLiteAffineQuantization;
+        quant.params = nullptr;
        // Optional: Set 'quant' quantization params here if needed.
        interpreter_->SetTensorParametersReadWrite(0, kTfLiteUInt8, "",
                                                   {channels_preserved}, quant);
      } else {
-        // Default TfLiteQuantization used for no quantization.
+        // Initialize structure for no quantization.
+        quant.type = kTfLiteNoQuantization;
+        quant.params = nullptr;
        interpreter_->SetTensorParametersReadWrite(0, kTfLiteFloat32, "",
                                                   {channels_preserved}, quant);
      }
@@ -383,7 +387,7 @@ REGISTER_CALCULATOR(TfLiteConverterCalculator);

 ::mediapipe::Status TfLiteConverterCalculator::ProcessGPU(
    CalculatorContext* cc) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  // GpuBuffer to tflite::gpu::GlBuffer conversion.
  const auto& input = cc->Inputs().Tag("IMAGE_GPU").Get<mediapipe::GpuBuffer>();
  MP_RETURN_IF_ERROR(
@@ -419,43 +423,38 @@ REGISTER_CALCULATOR(TfLiteConverterCalculator);
  cc->Outputs()
      .Tag("TENSORS_GPU")
      .Add(output_tensors.release(), cc->InputTimestamp());
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
  // GpuBuffer to id<MTLBuffer> conversion.
  const auto& input = cc->Inputs().Tag("IMAGE_GPU").Get<mediapipe::GpuBuffer>();
-  {
-    id<MTLTexture> src_texture = [gpu_helper_ metalTextureWithGpuBuffer:input];
-    id<MTLCommandBuffer> command_buffer = [gpu_helper_ commandBuffer];
-    command_buffer.label = @"TfLiteConverterCalculatorConvert";
-    id<MTLComputeCommandEncoder> compute_encoder =
-        [command_buffer computeCommandEncoder];
-    [compute_encoder setComputePipelineState:gpu_data_out_->pipeline_state];
-    [compute_encoder setTexture:src_texture atIndex:0];
-    [compute_encoder setBuffer:gpu_data_out_->buffer offset:0 atIndex:1];
-    MTLSize threads_per_group = MTLSizeMake(kWorkgroupSize, kWorkgroupSize, 1);
-    MTLSize threadgroups =
-        MTLSizeMake(NumGroups(input.width(), kWorkgroupSize),
-                    NumGroups(input.height(), kWorkgroupSize), 1);
-    [compute_encoder dispatchThreadgroups:threadgroups
-                    threadsPerThreadgroup:threads_per_group];
-    [compute_encoder endEncoding];
-    [command_buffer commit];
-    [command_buffer waitUntilCompleted];
-  }
+  id<MTLCommandBuffer> command_buffer = [gpu_helper_ commandBuffer];
+
+  id<MTLTexture> src_texture = [gpu_helper_ metalTextureWithGpuBuffer:input];
+  command_buffer.label = @"TfLiteConverterCalculatorConvertAndBlit";
+  id<MTLComputeCommandEncoder> compute_encoder =
+      [command_buffer computeCommandEncoder];
+  [compute_encoder setComputePipelineState:gpu_data_out_->pipeline_state];
+  [compute_encoder setTexture:src_texture atIndex:0];
+  [compute_encoder setBuffer:gpu_data_out_->buffer offset:0 atIndex:1];
+  MTLSize threads_per_group = MTLSizeMake(kWorkgroupSize, kWorkgroupSize, 1);
+  MTLSize threadgroups =
+      MTLSizeMake(NumGroups(input.width(), kWorkgroupSize),
+                  NumGroups(input.height(), kWorkgroupSize), 1);
+  [compute_encoder dispatchThreadgroups:threadgroups
+                  threadsPerThreadgroup:threads_per_group];
+  [compute_encoder endEncoding];

  // Copy into outputs.
  // TODO Avoid this copy.
  auto output_tensors = absl::make_unique<std::vector<GpuTensor>>();
  output_tensors->resize(1);
-  {
-    id<MTLDevice> device = gpu_helper_.mtlDevice;
-    output_tensors->at(0) =
-        [device newBufferWithLength:gpu_data_out_->elements * sizeof(float)
-                            options:MTLResourceStorageModeShared];
-    [MPPMetalUtil blitMetalBufferTo:output_tensors->at(0)
-                               from:gpu_data_out_->buffer
-                           blocking:true
-                      commandBuffer:[gpu_helper_ commandBuffer]];
-  }
+  id<MTLDevice> device = gpu_helper_.mtlDevice;
+  output_tensors->at(0) =
+      [device newBufferWithLength:gpu_data_out_->elements * sizeof(float)
+                          options:MTLResourceStorageModeShared];
+  [MPPMetalUtil blitMetalBufferTo:output_tensors->at(0)
+                             from:gpu_data_out_->buffer
+                         blocking:false
+                    commandBuffer:command_buffer];

  cc->Outputs()
      .Tag("TENSORS_GPU")
@@ -468,7 +467,7 @@ REGISTER_CALCULATOR(TfLiteConverterCalculator);
 }

 ::mediapipe::Status TfLiteConverterCalculator::InitGpu(CalculatorContext* cc) {
-#if !defined(MEDIAPIPE_DISABLE_GPU)
+#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__EMSCRIPTEN__)
  // Get input image sizes.
  const auto& input = cc->Inputs().Tag("IMAGE_GPU").Get<mediapipe::GpuBuffer>();
  mediapipe::ImageFormat::Format format =
@@ -485,7 +484,7 @@ REGISTER_CALCULATOR(TfLiteConverterCalculator);
    RET_CHECK_FAIL() << "Num input channels is less than desired output.";
 #endif  //  !MEDIAPIPE_DISABLE_GPU

-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  MP_RETURN_IF_ERROR(gpu_helper_.RunInGlContext(
      [this, &include_alpha, &input, &single_channel]() -> ::mediapipe::Status {
        // Device memory.
@@ -529,7 +528,9 @@ REGISTER_CALCULATOR(TfLiteConverterCalculator);
                                                   &gpu_data_out_->program));
        return ::mediapipe::OkStatus();
      }));
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+
+#elif defined(MEDIAPIPE_IOS)
+
  RET_CHECK(include_alpha)
      << "iOS GPU inference currently accepts only RGBA input.";

@@ -610,7 +611,7 @@ REGISTER_CALCULATOR(TfLiteConverterCalculator);
  CHECK_GE(max_num_channels_, 1);
  CHECK_LE(max_num_channels_, 4);
  CHECK_NE(max_num_channels_, 2);
-#if defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#if defined(MEDIAPIPE_IOS)
  if (cc->Inputs().HasTag("IMAGE_GPU"))
    // Currently on iOS, tflite gpu input tensor must be 4 channels,
    // so input image must be 4 channels also (checked in InitGpu).
@@ -17,17 +17,23 @@
 #include <string>
 #include <vector>

+#include "absl/memory/memory.h"
 #include "mediapipe/calculators/tflite/tflite_inference_calculator.pb.h"
 #include "mediapipe/calculators/tflite/util.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/port/ret_check.h"
+
+#if !defined(__EMSCRIPTEN__)
+#include "mediapipe/util/cpu_util.h"
+#endif  // !__EMSCRIPTEN__
+
 #include "mediapipe/util/resource_util.h"
 #include "tensorflow/lite/error_reporter.h"
 #include "tensorflow/lite/interpreter.h"
 #include "tensorflow/lite/kernels/register.h"
 #include "tensorflow/lite/model.h"

-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
 #include "mediapipe/gpu/gl_calculator_helper.h"
 #include "mediapipe/gpu/gpu_buffer.h"
 #include "tensorflow/lite/delegates/gpu/common/shape.h"
@@ -35,9 +41,9 @@
 #include "tensorflow/lite/delegates/gpu/gl/gl_program.h"
 #include "tensorflow/lite/delegates/gpu/gl/gl_shader.h"
 #include "tensorflow/lite/delegates/gpu/gl_delegate.h"
-#endif  //  !MEDIAPIPE_DISABLE_GPU
+#endif  //  !MEDIAPIPE_DISABLE_GL_COMPUTE

-#if defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#if defined(MEDIAPIPE_IOS)
 #import <CoreVideo/CoreVideo.h>
 #import <Metal/Metal.h>
 #import <MetalKit/MetalKit.h>
@@ -48,13 +54,22 @@
 #include "tensorflow/lite/delegates/gpu/common/shape.h"
 #include "tensorflow/lite/delegates/gpu/metal/buffer_convert.h"
 #include "tensorflow/lite/delegates/gpu/metal_delegate.h"
+#include "tensorflow/lite/delegates/gpu/metal_delegate_internal.h"
 #endif  // iOS
+#include "tensorflow/lite/delegates/xnnpack/xnnpack_delegate.h"
+#if defined(MEDIAPIPE_ANDROID)
+#include "tensorflow/lite/delegates/nnapi/nnapi_delegate.h"
+#endif  // ANDROID

 namespace {
+// Commonly used to compute the number of blocks to launch in a kernel.
+int NumGroups(const int size, const int group_size) {  // NOLINT
+  return (size + group_size - 1) / group_size;
+}

-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
 typedef ::tflite::gpu::gl::GlBuffer GpuTensor;
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
 typedef id<MTLBuffer> GpuTensor;
 #endif

@@ -62,19 +77,41 @@ typedef id<MTLBuffer> GpuTensor;
 size_t RoundUp(size_t n, size_t m) { return ((n + m - 1) / m) * m; }  // NOLINT
 }  // namespace

+#if defined(MEDIAPIPE_EDGE_TPU)
+#include "edgetpu.h"
+
+// Creates and returns an Edge TPU interpreter to run the given edgetpu model.
+std::unique_ptr<tflite::Interpreter> BuildEdgeTpuInterpreter(
+    const tflite::FlatBufferModel& model,
+    tflite::ops::builtin::BuiltinOpResolver* resolver,
+    edgetpu::EdgeTpuContext* edgetpu_context) {
+  resolver->AddCustom(edgetpu::kCustomOp, edgetpu::RegisterCustomOp());
+  std::unique_ptr<tflite::Interpreter> interpreter;
+  if (tflite::InterpreterBuilder(model, *resolver)(&interpreter) != kTfLiteOk) {
+    std::cerr << "Failed to build edge TPU interpreter." << std::endl;
+  }
+  interpreter->SetExternalContext(kTfLiteEdgeTpuContext, edgetpu_context);
+  interpreter->SetNumThreads(1);
+  if (interpreter->AllocateTensors() != kTfLiteOk) {
+    std::cerr << "Failed to allocate edge TPU tensors." << std::endl;
+  }
+  return interpreter;
+}
+#endif  // MEDIAPIPE_EDGE_TPU
+
 // TfLiteInferenceCalculator File Layout:
 //  * Header
 //  * Core
 //  * Aux
 namespace mediapipe {

-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
 using ::tflite::gpu::gl::CopyBuffer;
 using ::tflite::gpu::gl::CreateReadWriteShaderStorageBuffer;
 using ::tflite::gpu::gl::GlBuffer;
 #endif

-#if !defined(MEDIAPIPE_DISABLE_GPU)
+#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__EMSCRIPTEN__)
 struct GPUData {
  int elements = 1;
  GpuTensor buffer;
@@ -82,6 +119,23 @@ struct GPUData {
 };
 #endif

+// Returns number of threads to configure XNNPACK delegate with.
+// (Equal to user provided value if specified.  Otherwise, it returns number of
+// high cores (hard-coded to 1 for __EMSCRIPTEN__))
+int GetXnnpackNumThreads(
+    const mediapipe::TfLiteInferenceCalculatorOptions& opts) {
+  static constexpr int kDefaultNumThreads = -1;
+  if (opts.has_delegate() && opts.delegate().has_xnnpack() &&
+      opts.delegate().xnnpack().num_threads() != kDefaultNumThreads) {
+    return opts.delegate().xnnpack().num_threads();
+  }
+#if !defined(__EMSCRIPTEN__)
+  return InferHigherCoreIds().size();
+#else
+  return 1;
+#endif  // !__EMSCRIPTEN__
+}
+
 // Calculator Header Section

 // Runs inference on the provided input TFLite tensors and TFLite model.
@@ -108,6 +162,9 @@ struct GPUData {
 // Input side packet:
 //  CUSTOM_OP_RESOLVER (optional) - Use a custom op resolver,
 //                                  instead of the builtin one.
+//  MODEL (optional) - Use to specify TfLite model
+//                     (std::unique_ptr<tflite::FlatBufferModel,
+//                       std::function<void(tflite::FlatBufferModel*)>>)
 //
 // Example use:
 // node {
@@ -117,7 +174,21 @@ struct GPUData {
 //   options: {
 //     [mediapipe.TfLiteInferenceCalculatorOptions.ext] {
 //       model_path: "modelname.tflite"
-//       use_gpu: true
+//       delegate { gpu {} }
+//     }
+//   }
+// }
+//
+// or
+//
+// node {
+//   calculator: "TfLiteInferenceCalculator"
+//   input_stream: "TENSORS:tensor_image"
+//   input_side_packet: "MODEL:model"
+//   output_stream: "TENSORS:tensors"
+//   options: {
+//     [mediapipe.TfLiteInferenceCalculatorOptions.ext] {
+//       delegate { gpu {} }
 //     }
 //   }
 // }
@@ -132,6 +203,12 @@ struct GPUData {
 //
 class TfLiteInferenceCalculator : public CalculatorBase {
 public:
+  using TfLiteDelegatePtr =
+      std::unique_ptr<TfLiteDelegate, std::function<void(TfLiteDelegate*)>>;
+  using TfLiteModelPtr =
+      std::unique_ptr<tflite::FlatBufferModel,
+                      std::function<void(tflite::FlatBufferModel*)>>;
+
  static ::mediapipe::Status GetContract(CalculatorContract* cc);

  ::mediapipe::Status Open(CalculatorContext* cc) override;
@@ -139,26 +216,31 @@ class TfLiteInferenceCalculator : public CalculatorBase {
  ::mediapipe::Status Close(CalculatorContext* cc) override;

 private:
-  ::mediapipe::Status LoadOptions(CalculatorContext* cc);
  ::mediapipe::Status LoadModel(CalculatorContext* cc);
+  ::mediapipe::StatusOr<Packet> GetModelAsPacket(const CalculatorContext& cc);
  ::mediapipe::Status LoadDelegate(CalculatorContext* cc);

+  Packet model_packet_;
  std::unique_ptr<tflite::Interpreter> interpreter_;
-  std::unique_ptr<tflite::FlatBufferModel> model_;
-  TfLiteDelegate* delegate_ = nullptr;
+  TfLiteDelegatePtr delegate_;

-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  mediapipe::GlCalculatorHelper gpu_helper_;
-  std::unique_ptr<GPUData> gpu_data_in_;
+  std::vector<std::unique_ptr<GPUData>> gpu_data_in_;
  std::vector<std::unique_ptr<GPUData>> gpu_data_out_;
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
  MPPMetalHelper* gpu_helper_ = nullptr;
-  std::unique_ptr<GPUData> gpu_data_in_;
+  std::vector<std::unique_ptr<GPUData>> gpu_data_in_;
  std::vector<std::unique_ptr<GPUData>> gpu_data_out_;
+  id<MTLComputePipelineState> fp32_to_fp16_program_;
  TFLBufferConvert* converter_from_BPHWC4_ = nil;
 #endif

-  std::string model_path_ = "";
+#if defined(MEDIAPIPE_EDGE_TPU)
+  std::shared_ptr<edgetpu::EdgeTpuContext> edgetpu_context_ =
+      edgetpu::EdgeTpuManager::GetSingleton()->OpenDevice();
+#endif
+
  bool gpu_inference_ = false;
  bool gpu_input_ = false;
  bool gpu_output_ = false;
@@ -175,12 +257,22 @@ REGISTER_CALCULATOR(TfLiteInferenceCalculator);
  RET_CHECK(cc->Outputs().HasTag("TENSORS") ^
            cc->Outputs().HasTag("TENSORS_GPU"));

-  bool use_gpu = false;
+  const auto& options =
+      cc->Options<::mediapipe::TfLiteInferenceCalculatorOptions>();
+  RET_CHECK(!options.model_path().empty() ^
+            cc->InputSidePackets().HasTag("MODEL"))
+      << "Either model as side packet or model path in options is required.";
+
+  bool use_gpu =
+      options.has_delegate() ? options.delegate().has_gpu() : options.use_gpu();

  if (cc->Inputs().HasTag("TENSORS"))
    cc->Inputs().Tag("TENSORS").Set<std::vector<TfLiteTensor>>();
-#if !defined(MEDIAPIPE_DISABLE_GPU)
+#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__EMSCRIPTEN__)
  if (cc->Inputs().HasTag("TENSORS_GPU")) {
+    RET_CHECK(!options.has_delegate() || options.delegate().has_gpu())
+        << "GPU input is compatible with GPU delegate only.";
+
    cc->Inputs().Tag("TENSORS_GPU").Set<std::vector<GpuTensor>>();
    use_gpu |= true;
  }
@@ -188,8 +280,11 @@ REGISTER_CALCULATOR(TfLiteInferenceCalculator);

  if (cc->Outputs().HasTag("TENSORS"))
    cc->Outputs().Tag("TENSORS").Set<std::vector<TfLiteTensor>>();
-#if !defined(MEDIAPIPE_DISABLE_GPU)
+#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__EMSCRIPTEN__)
  if (cc->Outputs().HasTag("TENSORS_GPU")) {
+    RET_CHECK(!options.has_delegate() || options.delegate().has_gpu())
+        << "GPU output is compatible with GPU delegate only.";
+
    cc->Outputs().Tag("TENSORS_GPU").Set<std::vector<GpuTensor>>();
    use_gpu |= true;
  }
@@ -200,15 +295,14 @@ REGISTER_CALCULATOR(TfLiteInferenceCalculator);
        .Tag("CUSTOM_OP_RESOLVER")
        .Set<tflite::ops::builtin::BuiltinOpResolver>();
  }
-
-  const auto& options =
-      cc->Options<::mediapipe::TfLiteInferenceCalculatorOptions>();
-  use_gpu |= options.use_gpu();
+  if (cc->InputSidePackets().HasTag("MODEL")) {
+    cc->InputSidePackets().Tag("MODEL").Set<TfLiteModelPtr>();
+  }

  if (use_gpu) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
    MP_RETURN_IF_ERROR(mediapipe::GlCalculatorHelper::UpdateContract(cc));
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
    MP_RETURN_IF_ERROR([MPPMetalHelper updateContract:cc]);
 #endif
  }
@@ -222,10 +316,12 @@ REGISTER_CALCULATOR(TfLiteInferenceCalculator);
 ::mediapipe::Status TfLiteInferenceCalculator::Open(CalculatorContext* cc) {
  cc->SetOffset(TimestampDiff(0));

-  MP_RETURN_IF_ERROR(LoadOptions(cc));
+  const auto& options =
+      cc->Options<::mediapipe::TfLiteInferenceCalculatorOptions>();
+  gpu_inference_ = options.use_gpu();

  if (cc->Inputs().HasTag("TENSORS_GPU")) {
-#if !defined(MEDIAPIPE_DISABLE_GPU)
+#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__EMSCRIPTEN__)
    gpu_input_ = true;
    gpu_inference_ = true;  // Inference must be on GPU also.
 #else
@@ -235,7 +331,7 @@ REGISTER_CALCULATOR(TfLiteInferenceCalculator);
  }

  if (cc->Outputs().HasTag("TENSORS_GPU")) {
-#if !defined(MEDIAPIPE_DISABLE_GPU)
+#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__EMSCRIPTEN__)
    gpu_output_ = true;
    RET_CHECK(cc->Inputs().HasTag("TENSORS_GPU"))
        << "GPU output must also have GPU Input.";
@@ -248,20 +344,24 @@ REGISTER_CALCULATOR(TfLiteInferenceCalculator);
  MP_RETURN_IF_ERROR(LoadModel(cc));

  if (gpu_inference_) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
    MP_RETURN_IF_ERROR(gpu_helper_.Open(cc));
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
    gpu_helper_ = [[MPPMetalHelper alloc] initWithCalculatorContext:cc];
    RET_CHECK(gpu_helper_);
 #endif
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
    MP_RETURN_IF_ERROR(gpu_helper_.RunInGlContext(
        [this, &cc]() -> ::mediapipe::Status { return LoadDelegate(cc); }));
 #else
    MP_RETURN_IF_ERROR(LoadDelegate(cc));
 #endif
+  } else {
+#if defined(__EMSCRIPTEN__) || defined(MEDIAPIPE_ANDROID)
+    MP_RETURN_IF_ERROR(LoadDelegate(cc));
+#endif  // __EMSCRIPTEN__ || ANDROID
  }
-
  return ::mediapipe::OkStatus();
 }

@@ -269,25 +369,44 @@ REGISTER_CALCULATOR(TfLiteInferenceCalculator);
  // 1. Receive pre-processed tensor inputs.
  if (gpu_input_) {
    // Read GPU input into SSBO.
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
    const auto& input_tensors =
        cc->Inputs().Tag("TENSORS_GPU").Get<std::vector<GpuTensor>>();
-    RET_CHECK_EQ(input_tensors.size(), 1);
+    RET_CHECK_GT(input_tensors.size(), 0);
    MP_RETURN_IF_ERROR(gpu_helper_.RunInGlContext(
        [this, &input_tensors]() -> ::mediapipe::Status {
          // Explicit copy input.
-          RET_CHECK_CALL(CopyBuffer(input_tensors[0], gpu_data_in_->buffer));
+          gpu_data_in_.resize(input_tensors.size());
+          for (int i = 0; i < input_tensors.size(); ++i) {
+            RET_CHECK_CALL(
+                CopyBuffer(input_tensors[i], gpu_data_in_[i]->buffer));
+          }
+
          return ::mediapipe::OkStatus();
        }));
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
    const auto& input_tensors =
        cc->Inputs().Tag("TENSORS_GPU").Get<std::vector<GpuTensor>>();
-    RET_CHECK_EQ(input_tensors.size(), 1);
-    // Explicit copy input.
-    [MPPMetalUtil blitMetalBufferTo:gpu_data_in_->buffer
-                               from:input_tensors[0]
-                           blocking:true
-                      commandBuffer:[gpu_helper_ commandBuffer]];
+    RET_CHECK_GT(input_tensors.size(), 0);
+    // Explicit copy input with conversion float 32 bits to 16 bits.
+    gpu_data_in_.resize(input_tensors.size());
+    id<MTLCommandBuffer> command_buffer = [gpu_helper_ commandBuffer];
+    command_buffer.label = @"TfLiteInferenceCalculatorConvert";
+    id<MTLComputeCommandEncoder> compute_encoder =
+        [command_buffer computeCommandEncoder];
+    [compute_encoder setComputePipelineState:fp32_to_fp16_program_];
+    for (int i = 0; i < input_tensors.size(); ++i) {
+      [compute_encoder setBuffer:input_tensors[i] offset:0 atIndex:0];
+      [compute_encoder setBuffer:gpu_data_in_[i]->buffer offset:0 atIndex:1];
+      constexpr int kWorkgroupSize = 64;  // Block size for GPU shader.
+      MTLSize threads_per_group = MTLSizeMake(kWorkgroupSize, 1, 1);
+      const int threadgroups =
+          NumGroups(gpu_data_in_[i]->elements, kWorkgroupSize);
+      [compute_encoder dispatchThreadgroups:MTLSizeMake(threadgroups, 1, 1)
+                      threadsPerThreadgroup:threads_per_group];
+    }
+    [compute_encoder endEncoding];
+    [command_buffer commit];
 #else
    RET_CHECK_FAIL() << "GPU processing not enabled.";
 #endif
@@ -315,13 +434,13 @@ REGISTER_CALCULATOR(TfLiteInferenceCalculator);

  // 2. Run inference.
  if (gpu_inference_) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
    MP_RETURN_IF_ERROR(
        gpu_helper_.RunInGlContext([this]() -> ::mediapipe::Status {
          RET_CHECK_EQ(interpreter_->Invoke(), kTfLiteOk);
          return ::mediapipe::OkStatus();
        }));
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
    RET_CHECK_EQ(interpreter_->Invoke(), kTfLiteOk);
 #endif
  } else {
@@ -330,7 +449,7 @@ REGISTER_CALCULATOR(TfLiteInferenceCalculator);

  // 3. Output processed tensors.
  if (gpu_output_) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
    // Output result tensors (GPU).
    auto output_tensors = absl::make_unique<std::vector<GpuTensor>>();
    MP_RETURN_IF_ERROR(gpu_helper_.RunInGlContext(
@@ -347,7 +466,7 @@ REGISTER_CALCULATOR(TfLiteInferenceCalculator);
    cc->Outputs()
        .Tag("TENSORS_GPU")
        .Add(output_tensors.release(), cc->InputTimestamp());
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
    // Output result tensors (GPU).
    auto output_tensors = absl::make_unique<std::vector<GpuTensor>>();
    output_tensors->resize(gpu_data_out_.size());
@@ -368,7 +487,6 @@ REGISTER_CALCULATOR(TfLiteInferenceCalculator);
    }
    [convert_command endEncoding];
    [command_buffer commit];
-    [command_buffer waitUntilCompleted];
    cc->Outputs()
        .Tag("TENSORS_GPU")
        .Add(output_tensors.release(), cc->InputTimestamp());
@@ -392,70 +510,67 @@ REGISTER_CALCULATOR(TfLiteInferenceCalculator);

 ::mediapipe::Status TfLiteInferenceCalculator::Close(CalculatorContext* cc) {
  if (delegate_) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
-    MP_RETURN_IF_ERROR(gpu_helper_.RunInGlContext([this]() -> Status {
-      TfLiteGpuDelegateDelete(delegate_);
-      gpu_data_in_.reset();
+    if (gpu_inference_) {
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
+      MP_RETURN_IF_ERROR(gpu_helper_.RunInGlContext([this]() -> Status {
+        delegate_ = nullptr;
+        for (int i = 0; i < gpu_data_in_.size(); ++i) {
+          gpu_data_in_[i].reset();
+        }
+        for (int i = 0; i < gpu_data_out_.size(); ++i) {
+          gpu_data_out_[i].reset();
+        }
+        return ::mediapipe::OkStatus();
+      }));
+#elif defined(MEDIAPIPE_IOS)
+      delegate_ = nullptr;
+      for (int i = 0; i < gpu_data_in_.size(); ++i) {
+        gpu_data_in_[i].reset();
+      }
      for (int i = 0; i < gpu_data_out_.size(); ++i) {
        gpu_data_out_[i].reset();
      }
-      return ::mediapipe::OkStatus();
-    }));
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
-    TFLGpuDelegateDelete(delegate_);
-    gpu_data_in_.reset();
-    for (int i = 0; i < gpu_data_out_.size(); ++i) {
-      gpu_data_out_[i].reset();
-    }
 #endif
-    delegate_ = nullptr;
+    } else {
+      delegate_ = nullptr;
+    }
  }
+#if defined(MEDIAPIPE_EDGE_TPU)
+  edgetpu_context_.reset();
+#endif
  return ::mediapipe::OkStatus();
 }

 // Calculator Auxiliary Section

-::mediapipe::Status TfLiteInferenceCalculator::LoadOptions(
-    CalculatorContext* cc) {
-  // Get calculator options specified in the graph.
-  const auto& options =
-      cc->Options<::mediapipe::TfLiteInferenceCalculatorOptions>();
-
-  // Get model name.
-  if (!options.model_path().empty()) {
-    auto model_path = options.model_path();
-
-    ASSIGN_OR_RETURN(model_path_, mediapipe::PathToResourceAsFile(model_path));
-  } else {
-    LOG(ERROR) << "Must specify path to TFLite model.";
-    return ::mediapipe::Status(::mediapipe::StatusCode::kNotFound,
-                               "Must specify path to TFLite model.");
-  }
-
-  // Get execution modes.
-  gpu_inference_ = options.use_gpu();
-
-  return ::mediapipe::OkStatus();
-}
-
 ::mediapipe::Status TfLiteInferenceCalculator::LoadModel(
    CalculatorContext* cc) {
-  model_ = tflite::FlatBufferModel::BuildFromFile(model_path_.c_str());
-  RET_CHECK(model_);
+  ASSIGN_OR_RETURN(model_packet_, GetModelAsPacket(*cc));
+  const auto& model = *model_packet_.Get<TfLiteModelPtr>();

+  tflite::ops::builtin::BuiltinOpResolver op_resolver;
  if (cc->InputSidePackets().HasTag("CUSTOM_OP_RESOLVER")) {
-    const auto& op_resolver =
-        cc->InputSidePackets()
-            .Tag("CUSTOM_OP_RESOLVER")
-            .Get<tflite::ops::builtin::BuiltinOpResolver>();
-    tflite::InterpreterBuilder(*model_, op_resolver)(&interpreter_);
-  } else {
-    const tflite::ops::builtin::BuiltinOpResolver op_resolver;
-    tflite::InterpreterBuilder(*model_, op_resolver)(&interpreter_);
+    op_resolver = cc->InputSidePackets()
+                      .Tag("CUSTOM_OP_RESOLVER")
+                      .Get<tflite::ops::builtin::BuiltinOpResolver>();
  }
+#if defined(MEDIAPIPE_EDGE_TPU)
+  interpreter_ =
+      BuildEdgeTpuInterpreter(model, &op_resolver, edgetpu_context_.get());
+#else
+  tflite::InterpreterBuilder(model, op_resolver)(&interpreter_);
+#endif  // MEDIAPIPE_EDGE_TPU

  RET_CHECK(interpreter_);

+#if defined(__EMSCRIPTEN__) || defined(MEDIAPIPE_EDGE_TPU)
+  interpreter_->SetNumThreads(1);
+#else
+  interpreter_->SetNumThreads(
+      cc->Options<mediapipe::TfLiteInferenceCalculatorOptions>()
+          .cpu_num_thread());
+#endif  // __EMSCRIPTEN__
+
  if (gpu_output_) {
    use_quantized_tensors_ = false;
  } else {
@@ -469,9 +584,79 @@ REGISTER_CALCULATOR(TfLiteInferenceCalculator);
  return ::mediapipe::OkStatus();
 }

+::mediapipe::StatusOr<Packet> TfLiteInferenceCalculator::GetModelAsPacket(
+    const CalculatorContext& cc) {
+  const auto& options =
+      cc.Options<mediapipe::TfLiteInferenceCalculatorOptions>();
+  if (!options.model_path().empty()) {
+    std::string model_path = options.model_path();
+
+    ASSIGN_OR_RETURN(model_path, mediapipe::PathToResourceAsFile(model_path));
+
+    auto model = tflite::FlatBufferModel::BuildFromFile(model_path.c_str());
+    RET_CHECK(model) << "Failed to load model from path.";
+    return MakePacket<TfLiteModelPtr>(TfLiteModelPtr(
+        model.release(), [](tflite::FlatBufferModel* model) { delete model; }));
+  }
+  if (cc.InputSidePackets().HasTag("MODEL")) {
+    return cc.InputSidePackets().Tag("MODEL");
+  }
+  return ::mediapipe::Status(
+      ::mediapipe::StatusCode::kNotFound,
+      "Must specify TFLite model as path or loaded model.");
+}
+
 ::mediapipe::Status TfLiteInferenceCalculator::LoadDelegate(
    CalculatorContext* cc) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+  const auto& calculator_opts =
+      cc->Options<mediapipe::TfLiteInferenceCalculatorOptions>();
+  if (calculator_opts.has_delegate() &&
+      calculator_opts.delegate().has_tflite()) {
+    // Default tflite inference requeqsted - no need to modify graph.
+    return ::mediapipe::OkStatus();
+  }
+
+  if (!gpu_inference_) {
+#if defined(MEDIAPIPE_ANDROID)
+    const bool nnapi_requested = calculator_opts.has_delegate()
+                                     ? calculator_opts.delegate().has_nnapi()
+                                     : calculator_opts.use_nnapi();
+    if (nnapi_requested) {
+      // Attempt to use NNAPI.
+      // If not supported, the default CPU delegate will be created and used.
+      interpreter_->SetAllowFp16PrecisionForFp32(1);
+      delegate_ =
+          TfLiteDelegatePtr(tflite::NnApiDelegate(), [](TfLiteDelegate*) {
+            // No need to free according to tflite::NnApiDelegate()
+            // documentation.
+          });
+      RET_CHECK_EQ(interpreter_->ModifyGraphWithDelegate(delegate_.get()),
+                   kTfLiteOk);
+      return ::mediapipe::OkStatus();
+    }
+#endif  // MEDIAPIPE_ANDROID
+
+#if defined(__EMSCRIPTEN__)
+    const bool xnnpack_requested = true;
+#else
+    const bool xnnpack_requested = calculator_opts.has_delegate() &&
+                                   calculator_opts.delegate().has_xnnpack();
+#endif  // __EMSCRIPTEN__
+
+    if (xnnpack_requested) {
+      TfLiteXNNPackDelegateOptions xnnpack_opts{};
+      xnnpack_opts.num_threads = GetXnnpackNumThreads(calculator_opts);
+      delegate_ = TfLiteDelegatePtr(TfLiteXNNPackDelegateCreate(&xnnpack_opts),
+                                    &TfLiteXNNPackDelegateDelete);
+      RET_CHECK_EQ(interpreter_->ModifyGraphWithDelegate(delegate_.get()),
+                   kTfLiteOk);
+    }
+
+    // Return, no need for GPU delegate below.
+    return ::mediapipe::OkStatus();
+  }
+
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  // Configure and create the delegate.
  TfLiteGpuDelegateOptions options = TfLiteGpuDelegateOptionsDefault();
  options.compile_options.precision_loss_allowed = 1;
@@ -479,28 +664,30 @@ REGISTER_CALCULATOR(TfLiteInferenceCalculator);
      TFLITE_GL_OBJECT_TYPE_FASTEST;
  options.compile_options.dynamic_batch_enabled = 0;
  options.compile_options.inline_parameters = 1;
-  if (!delegate_) delegate_ = TfLiteGpuDelegateCreate(&options);
+  if (!delegate_)
+    delegate_ = TfLiteDelegatePtr(TfLiteGpuDelegateCreate(&options),
+                                  &TfLiteGpuDelegateDelete);

  if (gpu_input_) {
    // Get input image sizes.
-    gpu_data_in_ = absl::make_unique<GPUData>();
    const auto& input_indices = interpreter_->inputs();
-    RET_CHECK_EQ(input_indices.size(), 1);  // TODO accept > 1.
-    const TfLiteTensor* tensor = interpreter_->tensor(input_indices[0]);
-    gpu_data_in_->elements = 1;
-    for (int d = 0; d < tensor->dims->size; ++d) {
-      gpu_data_in_->elements *= tensor->dims->data[d];
+    gpu_data_in_.resize(input_indices.size());
+    for (int i = 0; i < input_indices.size(); ++i) {
+      const TfLiteTensor* tensor = interpreter_->tensor(input_indices[i]);
+      gpu_data_in_[i] = absl::make_unique<GPUData>();
+      gpu_data_in_[i]->elements = 1;
+      for (int d = 0; d < tensor->dims->size; ++d) {
+        gpu_data_in_[i]->elements *= tensor->dims->data[d];
+      }
+      // Create and bind input buffer.
+      RET_CHECK_CALL(
+          ::tflite::gpu::gl::CreateReadWriteShaderStorageBuffer<float>(
+              gpu_data_in_[i]->elements, &gpu_data_in_[i]->buffer));
+      RET_CHECK_EQ(TfLiteGpuDelegateBindBufferToTensor(
+                       delegate_.get(), gpu_data_in_[i]->buffer.id(),
+                       interpreter_->inputs()[i]),
+                   kTfLiteOk);
    }
-    CHECK_GE(tensor->dims->data[3], 1);
-    CHECK_LE(tensor->dims->data[3], 4);
-    CHECK_NE(tensor->dims->data[3], 2);
-    // Create and bind input buffer.
-    RET_CHECK_CALL(::tflite::gpu::gl::CreateReadWriteShaderStorageBuffer<float>(
-        gpu_data_in_->elements, &gpu_data_in_->buffer));
-    RET_CHECK_EQ(TfLiteGpuDelegateBindBufferToTensor(
-                     delegate_, gpu_data_in_->buffer.id(),
-                     interpreter_->inputs()[0]),  // First tensor only
-                 kTfLiteOk);
  }
  if (gpu_output_) {
    // Get output image sizes.
@@ -520,53 +707,85 @@ REGISTER_CALCULATOR(TfLiteInferenceCalculator);
    for (int i = 0; i < gpu_data_out_.size(); ++i) {
      RET_CHECK_CALL(CreateReadWriteShaderStorageBuffer<float>(
          gpu_data_out_[i]->elements, &gpu_data_out_[i]->buffer));
-      RET_CHECK_EQ(
-          TfLiteGpuDelegateBindBufferToTensor(
-              delegate_, gpu_data_out_[i]->buffer.id(), output_indices[i]),
-          kTfLiteOk);
+      RET_CHECK_EQ(TfLiteGpuDelegateBindBufferToTensor(
+                       delegate_.get(), gpu_data_out_[i]->buffer.id(),
+                       output_indices[i]),
+                   kTfLiteOk);
    }
  }

  // Must call this last.
-  RET_CHECK_EQ(interpreter_->ModifyGraphWithDelegate(delegate_), kTfLiteOk);
+  RET_CHECK_EQ(interpreter_->ModifyGraphWithDelegate(delegate_.get()),
+               kTfLiteOk);
 #endif  // OpenGL

-#if defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#if defined(MEDIAPIPE_IOS)
+  const int kHalfSize = 2;  // sizeof(half)
  // Configure and create the delegate.
-  GpuDelegateOptions options;
-  options.allow_precision_loss = false;  // Must match converter, F=float/T=half
-  options.wait_type = GpuDelegateOptions::WaitType::kPassive;
-  if (!delegate_) delegate_ = TFLGpuDelegateCreate(&options);
+  TFLGpuDelegateOptions options;
+  options.allow_precision_loss = true;
+  options.wait_type = TFLGpuDelegateWaitType::TFLGpuDelegateWaitTypePassive;
+  if (!delegate_)
+    delegate_ = TfLiteDelegatePtr(TFLGpuDelegateCreate(&options),
+                                  &TFLGpuDelegateDelete);
  id<MTLDevice> device = gpu_helper_.mtlDevice;

  if (gpu_input_) {
    // Get input image sizes.
-    gpu_data_in_ = absl::make_unique<GPUData>();
    const auto& input_indices = interpreter_->inputs();
-    RET_CHECK_EQ(input_indices.size(), 1);
-    const TfLiteTensor* tensor = interpreter_->tensor(input_indices[0]);
-    gpu_data_in_->elements = 1;
-    // On iOS GPU, input must be 4 channels, regardless of what model expects.
-    {
-      gpu_data_in_->elements *= tensor->dims->data[0];  // batch
-      gpu_data_in_->elements *= tensor->dims->data[1];  // height
-      gpu_data_in_->elements *= tensor->dims->data[2];  // width
-      gpu_data_in_->elements *= 4;                      // channels
+    gpu_data_in_.resize(input_indices.size());
+    for (int i = 0; i < input_indices.size(); ++i) {
+      const TfLiteTensor* tensor = interpreter_->tensor(input_indices[i]);
+      gpu_data_in_[i] = absl::make_unique<GPUData>();
+      gpu_data_in_[i]->shape.b = tensor->dims->data[0];
+      gpu_data_in_[i]->shape.h = tensor->dims->data[1];
+      gpu_data_in_[i]->shape.w = tensor->dims->data[2];
+      // On iOS GPU, input must be 4 channels, regardless of what model expects.
+      gpu_data_in_[i]->shape.c = 4;
+      gpu_data_in_[i]->elements =
+          gpu_data_in_[i]->shape.b * gpu_data_in_[i]->shape.h *
+          gpu_data_in_[i]->shape.w * gpu_data_in_[i]->shape.c;
+      // Input to model can be RGBA only.
+      if (tensor->dims->data[3] != 4) {
+        LOG(WARNING) << "Please ensure input GPU tensor is 4 channels.";
+      }
+      const std::string shader_source =
+          absl::Substitute(R"(#include <metal_stdlib>
+        using namespace metal;
+        kernel void convertKernel(device float4* const input_buffer [[buffer(0)]],
+                                  device half4* output_buffer [[buffer(1)]],
+                                  uint gid [[thread_position_in_grid]]) {
+          if (gid >= $0) return;
+          output_buffer[gid] = half4(input_buffer[gid]);
+        })",
+                           gpu_data_in_[i]->elements / 4);
+      NSString* library_source =
+          [NSString stringWithUTF8String:shader_source.c_str()];
+      NSError* error = nil;
+      id<MTLLibrary> library =
+          [device newLibraryWithSource:library_source options:nil error:&error];
+      RET_CHECK(library != nil) << "Couldn't create shader library "
+                                << [[error localizedDescription] UTF8String];
+      id<MTLFunction> kernel_func = nil;
+      kernel_func = [library newFunctionWithName:@"convertKernel"];
+      RET_CHECK(kernel_func != nil) << "Couldn't create kernel function.";
+      fp32_to_fp16_program_ =
+          [device newComputePipelineStateWithFunction:kernel_func error:&error];
+      RET_CHECK(fp32_to_fp16_program_ != nil)
+          << "Couldn't create pipeline state "
+          << [[error localizedDescription] UTF8String];
+
+      // Create and bind input buffer.
+      gpu_data_in_[i]->buffer =
+          [device newBufferWithLength:gpu_data_in_[i]->elements * kHalfSize
+                              options:MTLResourceStorageModeShared];
+      RET_CHECK_EQ(interpreter_->ModifyGraphWithDelegate(delegate_.get()),
+                   kTfLiteOk);
+      RET_CHECK_EQ(
+          TFLGpuDelegateBindMetalBufferToTensor(
+              delegate_.get(), input_indices[i], gpu_data_in_[i]->buffer),
+          true);
    }
-    // Input to model can be RGBA only.
-    if (tensor->dims->data[3] != 4) {
-      LOG(WARNING) << "Please ensure input GPU tensor is 4 channels.";
-    }
-    // Create and bind input buffer.
-    gpu_data_in_->buffer =
-        [device newBufferWithLength:gpu_data_in_->elements * sizeof(float)
-                            options:MTLResourceStorageModeShared];
-    RET_CHECK_EQ(interpreter_->ModifyGraphWithDelegate(delegate_), kTfLiteOk);
-    RET_CHECK_EQ(TFLGpuDelegateBindMetalBufferToTensor(
-                     delegate_,
-                     input_indices[0],  // First tensor only
-                     gpu_data_in_->buffer),
-                 true);
  }
  if (gpu_output_) {
    // Get output image sizes.
@@ -607,15 +826,17 @@ REGISTER_CALCULATOR(TfLiteInferenceCalculator);
    interpreter_->SetAllowBufferHandleOutput(true);
    for (int i = 0; i < gpu_data_out_.size(); ++i) {
      gpu_data_out_[i]->buffer =
-          [device newBufferWithLength:gpu_data_out_[i]->elements * sizeof(float)
+          [device newBufferWithLength:gpu_data_out_[i]->elements * kHalfSize
                              options:MTLResourceStorageModeShared];
-      RET_CHECK_EQ(TFLGpuDelegateBindMetalBufferToTensor(
-                       delegate_, output_indices[i], gpu_data_out_[i]->buffer),
-                   true);
+      RET_CHECK_EQ(
+          TFLGpuDelegateBindMetalBufferToTensor(
+              delegate_.get(), output_indices[i], gpu_data_out_[i]->buffer),
+          true);
    }
+
    // Create converter for GPU output.
    converter_from_BPHWC4_ = [[TFLBufferConvert alloc] initWithDevice:device
-                                                            isFloat16:false
+                                                            isFloat16:true
                                                      convertToPBHWC4:false];
    if (converter_from_BPHWC4_ == nil) {
      return mediapipe::InternalError(
@@ -27,7 +27,7 @@ import "mediapipe/framework/calculator.proto";
 //   options {
 //     [mediapipe.TfLiteInferenceCalculatorOptions.ext] {
 //       model_path: "model.tflite"
-//       use_gpu: true
+//       delegate { gpu {} }
 //     }
 //   }
 // }
@@ -37,6 +37,28 @@ message TfLiteInferenceCalculatorOptions {
    optional TfLiteInferenceCalculatorOptions ext = 233867213;
  }

+  message Delegate {
+    // Default inference provided by tflite.
+    message TfLite {}
+    // Delegate to run GPU inference depending on the device.
+    // (Can use OpenGl, OpenCl, Metal depending on the device.)
+    message Gpu {}
+    // Android only.
+    message Nnapi {}
+    message Xnnpack {
+      // Number of threads for XNNPACK delegate. (By default, calculator tries
+      // to choose optimal number of threads depending on the device.)
+      optional int32 num_threads = 1 [default = -1];
+    }
+
+    oneof delegate {
+      TfLite tflite = 1;
+      Gpu gpu = 2;
+      Nnapi nnapi = 3;
+      Xnnpack xnnpack = 4;
+    }
+  }
+
  // Path to the TF Lite model (ex: /path/to/modelname.tflite).
  // On mobile, this is generally just modelname.tflite.
  optional string model_path = 1;
@@ -44,5 +66,22 @@ message TfLiteInferenceCalculatorOptions {
  // Whether the TF Lite GPU or CPU backend should be used. Effective only when
  // input tensors are on CPU. For input tensors on GPU, GPU backend is always
  // used.
-  optional bool use_gpu = 2 [default = false];
+  // DEPRECATED: configure "delegate" instead.
+  optional bool use_gpu = 2 [deprecated = true, default = false];
+
+  // Android only. When true, an NNAPI delegate will be used for inference.
+  // If NNAPI is not available, then the default CPU delegate will be used
+  // automatically.
+  // DEPRECATED: configure "delegate" instead.
+  optional bool use_nnapi = 3 [deprecated = true, default = false];
+
+  // The number of threads available to the interpreter. Effective only when
+  // input tensors are on CPU and 'use_gpu' is false.
+  optional int32 cpu_num_thread = 4 [default = -1];
+
+  // TfLite delegate to run inference.
+  // NOTE: calculator is free to choose delegate if not specified explicitly.
+  // NOTE: use_gpu/use_nnapi are ignored if specified. (Delegate takes
+  // precedence over use_* deprecated options.)
+  optional Delegate delegate = 5;
 }
@@ -16,6 +16,8 @@
 #include <string>
 #include <vector>

+#include "absl/strings/str_replace.h"
+#include "absl/strings/string_view.h"
 #include "mediapipe/calculators/tflite/tflite_inference_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/calculator_runner.h"
@@ -39,13 +41,7 @@ namespace mediapipe {

 using ::tflite::Interpreter;

-class TfLiteInferenceCalculatorTest : public ::testing::Test {
- protected:
-  std::unique_ptr<CalculatorRunner> runner_ = nullptr;
-};
-
-// Tests a simple add model that adds an input tensor to itself.
-TEST_F(TfLiteInferenceCalculatorTest, SmokeTest) {
+void DoSmokeTest(const std::string& graph_proto) {
  const int width = 8;
  const int height = 8;
  const int channels = 3;
@@ -75,21 +71,7 @@ TEST_F(TfLiteInferenceCalculatorTest, SmokeTest) {

  // Prepare single calculator graph to and wait for packets.
  CalculatorGraphConfig graph_config =
-      ::mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(
-          R"(
-            input_stream: "tensor_in"
-            node {
-              calculator: "TfLiteInferenceCalculator"
-              input_stream: "TENSORS:tensor_in"
-              output_stream: "TENSORS:tensor_out"
-              options {
-                [mediapipe.TfLiteInferenceCalculatorOptions.ext] {
-                  use_gpu: false
-                  model_path: "mediapipe/calculators/tflite/testdata/add.bin"
-                }
-              }
-            }
-          )");
+      ParseTextProtoOrDie<CalculatorGraphConfig>(graph_proto);
  std::vector<Packet> output_packets;
  tool::AddVectorSink("tensor_out", &graph_config, &output_packets);
  CalculatorGraph graph(graph_config);
@@ -120,4 +102,72 @@ TEST_F(TfLiteInferenceCalculatorTest, SmokeTest) {
  MP_ASSERT_OK(graph.WaitUntilDone());
 }

+// Tests a simple add model that adds an input tensor to itself.
+TEST(TfLiteInferenceCalculatorTest, SmokeTest) {
+  std::string graph_proto = R"(
+    input_stream: "tensor_in"
+    node {
+      calculator: "TfLiteInferenceCalculator"
+      input_stream: "TENSORS:tensor_in"
+      output_stream: "TENSORS:tensor_out"
+      options {
+        [mediapipe.TfLiteInferenceCalculatorOptions.ext] {
+          model_path: "mediapipe/calculators/tflite/testdata/add.bin"
+          $delegate
+        }
+      }
+    }
+  )";
+  DoSmokeTest(
+      /*graph_proto=*/absl::StrReplaceAll(graph_proto, {{"$delegate", ""}}));
+  DoSmokeTest(/*graph_proto=*/absl::StrReplaceAll(
+      graph_proto, {{"$delegate", "delegate { tflite {} }"}}));
+  DoSmokeTest(/*graph_proto=*/absl::StrReplaceAll(
+      graph_proto, {{"$delegate", "delegate { xnnpack {} }"}}));
+  DoSmokeTest(/*graph_proto=*/absl::StrReplaceAll(
+      graph_proto,
+      {{"$delegate", "delegate { xnnpack { num_threads: 10 } }"}}));
+}
+
+TEST(TfLiteInferenceCalculatorTest, SmokeTest_ModelAsInputSidePacket) {
+  std::string graph_proto = R"(
+    input_stream: "tensor_in"
+
+    node {
+      calculator: "ConstantSidePacketCalculator"
+      output_side_packet: "PACKET:model_path"
+      options: {
+        [mediapipe.ConstantSidePacketCalculatorOptions.ext]: {
+          packet { string_value: "mediapipe/calculators/tflite/testdata/add.bin" }
+        }
+      }
+    }
+
+    node {
+      calculator: "LocalFileContentsCalculator"
+      input_side_packet: "FILE_PATH:model_path"
+      output_side_packet: "CONTENTS:model_blob"
+    }
+
+    node {
+      calculator: "TfLiteModelCalculator"
+      input_side_packet: "MODEL_BLOB:model_blob"
+      output_side_packet: "MODEL:model"
+    }
+
+    node {
+      calculator: "TfLiteInferenceCalculator"
+      input_stream: "TENSORS:tensor_in"
+      output_stream: "TENSORS:tensor_out"
+      input_side_packet: "MODEL:model"
+      options {
+        [mediapipe.TfLiteInferenceCalculatorOptions.ext] {
+          use_gpu: false
+        }
+      }
+    }
+  )";
+  DoSmokeTest(graph_proto);
+}
+
 }  // namespace mediapipe
@@ -0,0 +1,86 @@
+// Copyright 2020 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <functional>
+#include <memory>
+#include <string>
+
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/packet.h"
+#include "mediapipe/framework/port/ret_check.h"
+#include "tensorflow/lite/model.h"
+
+namespace mediapipe {
+
+// Loads TfLite model from model blob specified as input side packet and outputs
+// corresponding side packet.
+//
+// Input side packets:
+//   MODEL_BLOB - TfLite model blob/file-contents (std::string). You can read
+//                model blob from file (using whatever APIs you have) and pass
+//                it to the graph as input side packet or you can use some of
+//                calculators like LocalFileContentsCalculator to get model
+//                blob and use it as input here.
+//
+// Output side packets:
+//   MODEL - TfLite model. (std::unique_ptr<tflite::FlatBufferModel,
+//           std::function<void(tflite::FlatBufferModel*)>>)
+//
+// Example use:
+//
+// node {
+//   calculator: "TfLiteModelCalculator"
+//   input_side_packet: "MODEL_BLOB:model_blob"
+//   output_side_packet: "MODEL:model"
+// }
+//
+class TfLiteModelCalculator : public CalculatorBase {
+ public:
+  using TfLiteModelPtr =
+      std::unique_ptr<tflite::FlatBufferModel,
+                      std::function<void(tflite::FlatBufferModel*)>>;
+
+  static ::mediapipe::Status GetContract(CalculatorContract* cc) {
+    cc->InputSidePackets().Tag("MODEL_BLOB").Set<std::string>();
+    cc->OutputSidePackets().Tag("MODEL").Set<TfLiteModelPtr>();
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Open(CalculatorContext* cc) override {
+    const Packet& model_packet = cc->InputSidePackets().Tag("MODEL_BLOB");
+    const std::string& model_blob = model_packet.Get<std::string>();
+    std::unique_ptr<tflite::FlatBufferModel> model =
+        tflite::FlatBufferModel::BuildFromBuffer(model_blob.data(),
+                                                 model_blob.size());
+    RET_CHECK(model) << "Failed to load TfLite model from blob.";
+
+    cc->OutputSidePackets().Tag("MODEL").Set(
+        MakePacket<TfLiteModelPtr>(TfLiteModelPtr(
+            model.release(), [model_packet](tflite::FlatBufferModel* model) {
+              // Keeping model_packet in order to keep underlying model blob
+              // which can be released only after TfLite model is not needed
+              // anymore (deleted).
+              delete model;
+            })));
+
+    return ::mediapipe::OkStatus();
+  }
+
+  ::mediapipe::Status Process(CalculatorContext* cc) override {
+    return ::mediapipe::OkStatus();
+  }
+};
+REGISTER_CALCULATOR(TfLiteModelCalculator);
+
+}  // namespace mediapipe
@@ -0,0 +1,88 @@
+// Copyright 2020 The MediaPipe Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <memory>
+
+#include "mediapipe/framework/calculator_framework.h"
+#include "mediapipe/framework/calculator_runner.h"
+#include "mediapipe/framework/port/gmock.h"
+#include "mediapipe/framework/port/gtest.h"
+#include "mediapipe/framework/port/parse_text_proto.h"
+#include "mediapipe/framework/port/status_matchers.h"  // NOLINT
+#include "tensorflow/lite/model.h"
+
+namespace mediapipe {
+
+TEST(TfLiteModelCalculatorTest, SmokeTest) {
+  // Prepare single calculator graph to and wait for packets.
+  CalculatorGraphConfig graph_config = ParseTextProtoOrDie<
+      CalculatorGraphConfig>(
+      R"(
+        node {
+          calculator: "ConstantSidePacketCalculator"
+          output_side_packet: "PACKET:model_path"
+          options: {
+            [mediapipe.ConstantSidePacketCalculatorOptions.ext]: {
+              packet {
+                string_value: "mediapipe/calculators/tflite/testdata/add.bin"
+              }
+            }
+          }
+        }
+
+        node {
+          calculator: "LocalFileContentsCalculator"
+          input_side_packet: "FILE_PATH:model_path"
+          output_side_packet: "CONTENTS:model_blob"
+        }
+
+        node {
+          calculator: "TfLiteModelCalculator"
+          input_side_packet: "MODEL_BLOB:model_blob"
+          output_side_packet: "MODEL:model"
+        }
+      )");
+  CalculatorGraph graph(graph_config);
+  MP_ASSERT_OK(graph.StartRun({}));
+  MP_ASSERT_OK(graph.WaitUntilIdle());
+  auto status_or_packet = graph.GetOutputSidePacket("model");
+  MP_ASSERT_OK(status_or_packet);
+  auto model_packet = status_or_packet.ValueOrDie();
+  const auto& model = model_packet.Get<
+      std::unique_ptr<tflite::FlatBufferModel,
+                      std::function<void(tflite::FlatBufferModel*)>>>();
+
+  auto expected_model = tflite::FlatBufferModel::BuildFromFile(
+      "mediapipe/calculators/tflite/testdata/add.bin");
+
+  EXPECT_EQ(model->GetModel()->version(),
+            expected_model->GetModel()->version());
+  EXPECT_EQ(model->GetModel()->buffers()->size(),
+            expected_model->GetModel()->buffers()->size());
+  const int num_subgraphs = expected_model->GetModel()->subgraphs()->size();
+  EXPECT_EQ(model->GetModel()->subgraphs()->size(), num_subgraphs);
+  for (int i = 0; i < num_subgraphs; ++i) {
+    const auto* expected_subgraph =
+        expected_model->GetModel()->subgraphs()->Get(i);
+    const auto* subgraph = model->GetModel()->subgraphs()->Get(i);
+    const int num_tensors = expected_subgraph->tensors()->size();
+    EXPECT_EQ(subgraph->tensors()->size(), num_tensors);
+    for (int j = 0; j < num_tensors; ++j) {
+      EXPECT_EQ(subgraph->tensors()->Get(j)->name()->str(),
+                expected_subgraph->tensors()->Get(j)->name()->str());
+    }
+  }
+}
+
+}  // namespace mediapipe
@@ -24,7 +24,7 @@
 #include "mediapipe/framework/port/ret_check.h"
 #include "mediapipe/util/resource_util.h"
 #include "tensorflow/lite/interpreter.h"
-#if defined(__ANDROID__) || (defined(__APPLE__) && !TARGET_OS_OSX)
+#if defined(MEDIAPIPE_MOBILE)
 #include "mediapipe/util/android/file/base/file.h"
 #include "mediapipe/util/android/file/base/helpers.h"
 #else
@@ -66,8 +66,8 @@ class TfLiteTensorsToClassificationCalculator : public CalculatorBase {
  ::mediapipe::Status Close(CalculatorContext* cc) override;

 private:
+  ::mediapipe::TfLiteTensorsToClassificationCalculatorOptions options_;
  int top_k_ = 0;
-  double min_score_threshold_ = 0;
  std::unordered_map<int, std::string> label_map_;
  bool label_map_loaded_ = false;
 };
@@ -93,15 +93,14 @@ REGISTER_CALCULATOR(TfLiteTensorsToClassificationCalculator);
    CalculatorContext* cc) {
  cc->SetOffset(TimestampDiff(0));

-  auto options = cc->Options<
+  options_ = cc->Options<
      ::mediapipe::TfLiteTensorsToClassificationCalculatorOptions>();

-  top_k_ = options.top_k();
-  min_score_threshold_ = options.min_score_threshold();
-  if (options.has_label_map_path()) {
+  top_k_ = options_.top_k();
+  if (options_.has_label_map_path()) {
    std::string string_path;
    ASSIGN_OR_RETURN(string_path,
-                     PathToResourceAsFile(options.label_map_path()));
+                     PathToResourceAsFile(options_.label_map_path()));
    std::string label_map_string;
    MP_RETURN_IF_ERROR(file::GetContents(string_path, &label_map_string));

@@ -125,29 +124,54 @@ REGISTER_CALCULATOR(TfLiteTensorsToClassificationCalculator);
  RET_CHECK_EQ(input_tensors.size(), 1);

  const TfLiteTensor* raw_score_tensor = &input_tensors[0];
-  RET_CHECK_EQ(raw_score_tensor->dims->size, 2);
-  RET_CHECK_EQ(raw_score_tensor->dims->data[0], 1);
-  int num_classes = raw_score_tensor->dims->data[1];
+  int num_classes = 1;
+  for (int i = 0; i < raw_score_tensor->dims->size; ++i) {
+    num_classes *= raw_score_tensor->dims->data[i];
+  }
+
+  if (options_.binary_classification()) {
+    RET_CHECK_EQ(num_classes, 1);
+    // Number of classes for binary classification.
+    num_classes = 2;
+  }
  if (label_map_loaded_) {
    RET_CHECK_EQ(num_classes, label_map_.size());
  }
  const float* raw_scores = raw_score_tensor->data.f;

  auto classification_list = absl::make_unique<ClassificationList>();
-  for (int i = 0; i < num_classes; ++i) {
-    if (raw_scores[i] < min_score_threshold_) {
-      continue;
-    }
-    Classification* classification = classification_list->add_classification();
-    classification->set_index(i);
-    classification->set_score(raw_scores[i]);
+  if (options_.binary_classification()) {
+    Classification* class_first = classification_list->add_classification();
+    Classification* class_second = classification_list->add_classification();
+    class_first->set_index(0);
+    class_second->set_index(1);
+    class_first->set_score(raw_scores[0]);
+    class_second->set_score(1. - raw_scores[0]);
+
    if (label_map_loaded_) {
-      classification->set_label(label_map_[i]);
+      class_first->set_label(label_map_[0]);
+      class_second->set_label(label_map_[1]);
+    }
+  } else {
+    for (int i = 0; i < num_classes; ++i) {
+      if (options_.has_min_score_threshold() &&
+          raw_scores[i] < options_.min_score_threshold()) {
+        continue;
+      }
+      Classification* classification =
+          classification_list->add_classification();
+      classification->set_index(i);
+      classification->set_score(raw_scores[i]);
+
+      if (label_map_loaded_) {
+        classification->set_label(label_map_[i]);
+      }
    }
  }

  // Note that partial_sort will raise error when top_k_ >
  // classification_list->classification_size().
+  CHECK_GE(classification_list->classification_size(), top_k_);
  auto raw_classification_list = classification_list->mutable_classification();
  if (top_k_ > 0 && classification_list->classification_size() >= top_k_) {
    std::partial_sort(raw_classification_list->begin(),
@@ -32,4 +32,10 @@ message TfLiteTensorsToClassificationCalculatorOptions {
  optional int32 top_k = 2;
  // Path to a label map file for getting the actual name of class ids.
  optional string label_map_path = 3;
+  // Whether the input is a single float for binary classification.
+  // When true, only a single float is expected in the input tensor and the
+  // label map, if provided, is expected to have exactly two labels.
+  // The single score(float) represent the probability of first label, and
+  // 1 - score is the probabilility of the second label.
+  optional bool binary_classification = 4;
 }
@@ -27,7 +27,7 @@
 #include "mediapipe/framework/port/ret_check.h"
 #include "tensorflow/lite/interpreter.h"

-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
 #include "mediapipe/gpu/gl_calculator_helper.h"
 #include "tensorflow/lite/delegates/gpu/gl/gl_buffer.h"
 #include "tensorflow/lite/delegates/gpu/gl/gl_program.h"
@@ -35,7 +35,7 @@
 #include "tensorflow/lite/delegates/gpu/gl_delegate.h"
 #endif  // !MEDIAPIPE_DISABLE_GPU

-#if defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#if defined(MEDIAPIPE_IOS)
 #import <CoreVideo/CoreVideo.h>
 #import <Metal/Metal.h>
 #import <MetalKit/MetalKit.h>
@@ -55,22 +55,22 @@ constexpr int kNumCoordsPerBox = 4;

 namespace mediapipe {

-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
 using ::tflite::gpu::gl::CreateReadWriteShaderStorageBuffer;
 using ::tflite::gpu::gl::GlShader;
 #endif

-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
 typedef ::tflite::gpu::gl::GlBuffer GpuTensor;
 typedef ::tflite::gpu::gl::GlProgram GpuProgram;
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
 typedef id<MTLBuffer> GpuTensor;
 typedef id<MTLComputePipelineState> GpuProgram;
 #endif

 namespace {

-#if !defined(MEDIAPIPE_DISABLE_GPU)
+#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__EMSCRIPTEN__)
 struct GPUData {
  GpuProgram decode_program;
  GpuProgram score_program;
@@ -180,10 +180,10 @@ class TfLiteTensorsToDetectionsCalculator : public CalculatorBase {
  std::vector<Anchor> anchors_;
  bool side_packet_anchors_{};

-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  mediapipe::GlCalculatorHelper gpu_helper_;
  std::unique_ptr<GPUData> gpu_data_;
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
  MPPMetalHelper* gpu_helper_ = nullptr;
  std::unique_ptr<GPUData> gpu_data_;
 #endif
@@ -204,7 +204,7 @@ REGISTER_CALCULATOR(TfLiteTensorsToDetectionsCalculator);
    cc->Inputs().Tag("TENSORS").Set<std::vector<TfLiteTensor>>();
  }

-#if !defined(MEDIAPIPE_DISABLE_GPU)
+#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__EMSCRIPTEN__)
  if (cc->Inputs().HasTag("TENSORS_GPU")) {
    cc->Inputs().Tag("TENSORS_GPU").Set<std::vector<GpuTensor>>();
    use_gpu |= true;
@@ -222,9 +222,9 @@ REGISTER_CALCULATOR(TfLiteTensorsToDetectionsCalculator);
  }

  if (use_gpu) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
    MP_RETURN_IF_ERROR(mediapipe::GlCalculatorHelper::UpdateContract(cc));
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
    MP_RETURN_IF_ERROR([MPPMetalHelper updateContract:cc]);
 #endif
  }
@@ -238,9 +238,9 @@ REGISTER_CALCULATOR(TfLiteTensorsToDetectionsCalculator);

  if (cc->Inputs().HasTag("TENSORS_GPU")) {
    gpu_input_ = true;
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
    MP_RETURN_IF_ERROR(gpu_helper_.Open(cc));
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
    gpu_helper_ = [[MPPMetalHelper alloc] initWithCalculatorContext:cc];
    RET_CHECK(gpu_helper_);
 #endif
@@ -400,7 +400,7 @@ REGISTER_CALCULATOR(TfLiteTensorsToDetectionsCalculator);
 }
 ::mediapipe::Status TfLiteTensorsToDetectionsCalculator::ProcessGPU(
    CalculatorContext* cc, std::vector<Detection>* output_detections) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  const auto& input_tensors =
      cc->Inputs().Tag("TENSORS_GPU").Get<std::vector<GpuTensor>>();
  RET_CHECK_GE(input_tensors.size(), 2);
@@ -463,7 +463,7 @@ REGISTER_CALCULATOR(TfLiteTensorsToDetectionsCalculator);

    return ::mediapipe::OkStatus();
  }));
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)

  const auto& input_tensors =
      cc->Inputs().Tag("TENSORS_GPU").Get<std::vector<GpuTensor>>();
@@ -472,11 +472,11 @@ REGISTER_CALCULATOR(TfLiteTensorsToDetectionsCalculator);
  // Copy inputs.
  [MPPMetalUtil blitMetalBufferTo:gpu_data_->raw_boxes_buffer
                             from:input_tensors[0]
-                         blocking:true
+                         blocking:false
                    commandBuffer:[gpu_helper_ commandBuffer]];
  [MPPMetalUtil blitMetalBufferTo:gpu_data_->raw_scores_buffer
                             from:input_tensors[1]
-                         blocking:true
+                         blocking:false
                    commandBuffer:[gpu_helper_ commandBuffer]];
  if (!anchors_init_) {
    if (side_packet_anchors_) {
@@ -491,48 +491,37 @@ REGISTER_CALCULATOR(TfLiteTensorsToDetectionsCalculator);
      RET_CHECK_EQ(input_tensors.size(), kNumInputTensorsWithAnchors);
      [MPPMetalUtil blitMetalBufferTo:gpu_data_->raw_anchors_buffer
                                 from:input_tensors[2]
-                             blocking:true
+                             blocking:false
                        commandBuffer:[gpu_helper_ commandBuffer]];
    }
    anchors_init_ = true;
  }

  // Run shaders.
-  {
-    id<MTLCommandBuffer> command_buffer = [gpu_helper_ commandBuffer];
-    command_buffer.label = @"TfLiteDecodeBoxes";
-    id<MTLComputeCommandEncoder> decode_command =
-        [command_buffer computeCommandEncoder];
-    [decode_command setComputePipelineState:gpu_data_->decode_program];
-    [decode_command setBuffer:gpu_data_->decoded_boxes_buffer
-                       offset:0
-                      atIndex:0];
-    [decode_command setBuffer:gpu_data_->raw_boxes_buffer offset:0 atIndex:1];
-    [decode_command setBuffer:gpu_data_->raw_anchors_buffer offset:0 atIndex:2];
-    MTLSize decode_threads_per_group = MTLSizeMake(1, 1, 1);
-    MTLSize decode_threadgroups = MTLSizeMake(num_boxes_, 1, 1);
-    [decode_command dispatchThreadgroups:decode_threadgroups
-                   threadsPerThreadgroup:decode_threads_per_group];
-    [decode_command endEncoding];
-    [command_buffer commit];
-    [command_buffer waitUntilCompleted];
-  }
-  {
-    id<MTLCommandBuffer> command_buffer = [gpu_helper_ commandBuffer];
-    command_buffer.label = @"TfLiteScoreBoxes";
-    id<MTLComputeCommandEncoder> score_command =
-        [command_buffer computeCommandEncoder];
-    [score_command setComputePipelineState:gpu_data_->score_program];
-    [score_command setBuffer:gpu_data_->scored_boxes_buffer offset:0 atIndex:0];
-    [score_command setBuffer:gpu_data_->raw_scores_buffer offset:0 atIndex:1];
-    MTLSize score_threads_per_group = MTLSizeMake(1, num_classes_, 1);
-    MTLSize score_threadgroups = MTLSizeMake(num_boxes_, 1, 1);
-    [score_command dispatchThreadgroups:score_threadgroups
+  id<MTLCommandBuffer> command_buffer = [gpu_helper_ commandBuffer];
+  command_buffer.label = @"TfLiteDecodeAndScoreBoxes";
+  id<MTLComputeCommandEncoder> command_encoder =
+      [command_buffer computeCommandEncoder];
+  [command_encoder setComputePipelineState:gpu_data_->decode_program];
+  [command_encoder setBuffer:gpu_data_->decoded_boxes_buffer
+                      offset:0
+                     atIndex:0];
+  [command_encoder setBuffer:gpu_data_->raw_boxes_buffer offset:0 atIndex:1];
+  [command_encoder setBuffer:gpu_data_->raw_anchors_buffer offset:0 atIndex:2];
+  MTLSize decode_threads_per_group = MTLSizeMake(1, 1, 1);
+  MTLSize decode_threadgroups = MTLSizeMake(num_boxes_, 1, 1);
+  [command_encoder dispatchThreadgroups:decode_threadgroups
+                  threadsPerThreadgroup:decode_threads_per_group];
+
+  [command_encoder setComputePipelineState:gpu_data_->score_program];
+  [command_encoder setBuffer:gpu_data_->scored_boxes_buffer offset:0 atIndex:0];
+  [command_encoder setBuffer:gpu_data_->raw_scores_buffer offset:0 atIndex:1];
+  MTLSize score_threads_per_group = MTLSizeMake(1, num_classes_, 1);
+  MTLSize score_threadgroups = MTLSizeMake(num_boxes_, 1, 1);
+  [command_encoder dispatchThreadgroups:score_threadgroups
                  threadsPerThreadgroup:score_threads_per_group];
-    [score_command endEncoding];
-    [command_buffer commit];
-    [command_buffer waitUntilCompleted];
-  }
+  [command_encoder endEncoding];
+  [MPPMetalUtil commitCommandBufferAndWait:command_buffer];

  // Copy decoded boxes from GPU to CPU.
  std::vector<float> boxes(num_boxes_ * num_coords_);
@@ -562,11 +551,11 @@ REGISTER_CALCULATOR(TfLiteTensorsToDetectionsCalculator);

 ::mediapipe::Status TfLiteTensorsToDetectionsCalculator::Close(
    CalculatorContext* cc) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  gpu_helper_.RunInGlContext([this] { gpu_data_.reset(); });
-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
+#elif defined(MEDIAPIPE_IOS)
  gpu_data_.reset();
-#endif                                      //  !MEDIAPIPE_DISABLE_GPU
+#endif

  return ::mediapipe::OkStatus();
 }
@@ -715,7 +704,7 @@ Detection TfLiteTensorsToDetectionsCalculator::ConvertToDetection(

 ::mediapipe::Status TfLiteTensorsToDetectionsCalculator::GpuInit(
    CalculatorContext* cc) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  MP_RETURN_IF_ERROR(gpu_helper_.RunInGlContext([this]()
                                                    -> ::mediapipe::Status {
    gpu_data_ = absl::make_unique<GPUData>();
@@ -928,8 +917,7 @@ void main() {
    return ::mediapipe::OkStatus();
  }));

-#elif defined(__APPLE__) && !TARGET_OS_OSX  // iOS
-  // TODO consolidate Metal and OpenGL shaders via vulkan.
+#elif defined(MEDIAPIPE_IOS)

  gpu_data_ = absl::make_unique<GPUData>();
  id<MTLDevice> device = gpu_helper_.mtlDevice;
@@ -1159,7 +1147,7 @@ kernel void scoreKernel(
    CHECK_LT(num_classes_, max_wg_size) << "# classes must be <" << max_wg_size;
  }

-#endif  // __ANDROID__ or iOS
+#endif  // !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)

  return ::mediapipe::OkStatus();
 }
@@ -21,12 +21,28 @@
 namespace mediapipe {

 // A calculator for converting TFLite tensors from regression models into
-// landmarks.
+// landmarks. Note that if the landmarks in the tensor has more than 3
+// dimensions, only the first 3 dimensions will be converted to x,y,z.
 //
 // Input:
 //  TENSORS - Vector of TfLiteTensor of type kTfLiteFloat32. Only the first
 //            tensor will be used. The size of the values must be
 //            (num_dimension x num_landmarks).
+//
+//  FLIP_HORIZONTALLY (optional): Whether to flip landmarks horizontally or
+//  not. Overrides corresponding side packet and/or field in the calculator
+//  options.
+//
+//  FLIP_VERTICALLY (optional): Whether to flip landmarks vertically or not.
+//  Overrides corresponding side packet and/or field in the calculator options.
+//
+// Input side packet:
+//   FLIP_HORIZONTALLY (optional): Whether to flip landmarks horizontally or
+//   not. Overrides the corresponding field in the calculator options.
+//
+//   FLIP_VERTICALLY (optional): Whether to flip landmarks vertically or not.
+//   Overrides the corresponding field in the calculator options.
+//
 // Output:
 //  LANDMARKS(optional) - Result MediaPipe landmarks.
 //  NORM_LANDMARKS(optional) - Result MediaPipe normalized landmarks.
@@ -60,6 +76,8 @@ class TfLiteTensorsToLandmarksCalculator : public CalculatorBase {
 private:
  ::mediapipe::Status LoadOptions(CalculatorContext* cc);
  int num_landmarks_ = 0;
+  bool flip_vertically_ = false;
+  bool flip_horizontally_ = false;

  ::mediapipe::TfLiteTensorsToLandmarksCalculatorOptions options_;
 };
@@ -74,12 +92,28 @@ REGISTER_CALCULATOR(TfLiteTensorsToLandmarksCalculator);
    cc->Inputs().Tag("TENSORS").Set<std::vector<TfLiteTensor>>();
  }

+  if (cc->Inputs().HasTag("FLIP_HORIZONTALLY")) {
+    cc->Inputs().Tag("FLIP_HORIZONTALLY").Set<bool>();
+  }
+
+  if (cc->Inputs().HasTag("FLIP_VERTICALLY")) {
+    cc->Inputs().Tag("FLIP_VERTICALLY").Set<bool>();
+  }
+
+  if (cc->InputSidePackets().HasTag("FLIP_HORIZONTALLY")) {
+    cc->InputSidePackets().Tag("FLIP_HORIZONTALLY").Set<bool>();
+  }
+
+  if (cc->InputSidePackets().HasTag("FLIP_VERTICALLY")) {
+    cc->InputSidePackets().Tag("FLIP_VERTICALLY").Set<bool>();
+  }
+
  if (cc->Outputs().HasTag("LANDMARKS")) {
-    cc->Outputs().Tag("LANDMARKS").Set<std::vector<Landmark>>();
+    cc->Outputs().Tag("LANDMARKS").Set<LandmarkList>();
  }

  if (cc->Outputs().HasTag("NORM_LANDMARKS")) {
-    cc->Outputs().Tag("NORM_LANDMARKS").Set<std::vector<NormalizedLandmark>>();
+    cc->Outputs().Tag("NORM_LANDMARKS").Set<NormalizedLandmarkList>();
  }

  return ::mediapipe::OkStatus();
@@ -97,17 +131,40 @@ REGISTER_CALCULATOR(TfLiteTensorsToLandmarksCalculator);
        << "Must provide input with/height for getting normalized landmarks.";
  }
  if (cc->Outputs().HasTag("LANDMARKS") &&
-      (options_.flip_vertically() || options_.flip_horizontally())) {
+      (options_.flip_vertically() || options_.flip_horizontally() ||
+       cc->InputSidePackets().HasTag("FLIP_HORIZONTALLY") ||
+       cc->InputSidePackets().HasTag("FLIP_VERTICALLY"))) {
    RET_CHECK(options_.has_input_image_height() &&
              options_.has_input_image_width())
        << "Must provide input with/height for using flip_vertically option "
           "when outputing landmarks in absolute coordinates.";
  }
+
+  flip_horizontally_ =
+      cc->InputSidePackets().HasTag("FLIP_HORIZONTALLY")
+          ? cc->InputSidePackets().Tag("FLIP_HORIZONTALLY").Get<bool>()
+          : options_.flip_horizontally();
+
+  flip_vertically_ =
+      cc->InputSidePackets().HasTag("FLIP_VERTICALLY")
+          ? cc->InputSidePackets().Tag("FLIP_VERTICALLY").Get<bool>()
+          : options_.flip_vertically();
+
  return ::mediapipe::OkStatus();
 }

 ::mediapipe::Status TfLiteTensorsToLandmarksCalculator::Process(
    CalculatorContext* cc) {
+  // Override values if specified so.
+  if (cc->Inputs().HasTag("FLIP_HORIZONTALLY") &&
+      !cc->Inputs().Tag("FLIP_HORIZONTALLY").IsEmpty()) {
+    flip_horizontally_ = cc->Inputs().Tag("FLIP_HORIZONTALLY").Get<bool>();
+  }
+  if (cc->Inputs().HasTag("FLIP_VERTICALLY") &&
+      !cc->Inputs().Tag("FLIP_VERTICALLY").IsEmpty()) {
+    flip_vertically_ = cc->Inputs().Tag("FLIP_VERTICALLY").Get<bool>();
+  }
+
  if (cc->Inputs().Tag("TENSORS").IsEmpty()) {
    return ::mediapipe::OkStatus();
  }
@@ -122,61 +179,59 @@ REGISTER_CALCULATOR(TfLiteTensorsToLandmarksCalculator);
    num_values *= raw_tensor->dims->data[i];
  }
  const int num_dimensions = num_values / num_landmarks_;
-  // Landmarks must have less than 3 dimensions. Otherwise please consider
-  // using matrix.
-  CHECK_LE(num_dimensions, 3);
  CHECK_GT(num_dimensions, 0);

  const float* raw_landmarks = raw_tensor->data.f;

-  auto output_landmarks = absl::make_unique<std::vector<Landmark>>();
+  LandmarkList output_landmarks;

  for (int ld = 0; ld < num_landmarks_; ++ld) {
    const int offset = ld * num_dimensions;
-    Landmark landmark;
+    Landmark* landmark = output_landmarks.add_landmark();

-    if (options_.flip_horizontally()) {
-      landmark.set_x(options_.input_image_width() - raw_landmarks[offset]);
+    if (flip_horizontally_) {
+      landmark->set_x(options_.input_image_width() - raw_landmarks[offset]);
    } else {
-      landmark.set_x(raw_landmarks[offset]);
+      landmark->set_x(raw_landmarks[offset]);
    }
    if (num_dimensions > 1) {
-      if (options_.flip_vertically()) {
-        landmark.set_y(options_.input_image_height() -
-                       raw_landmarks[offset + 1]);
+      if (flip_vertically_) {
+        landmark->set_y(options_.input_image_height() -
+                        raw_landmarks[offset + 1]);
      } else {
-        landmark.set_y(raw_landmarks[offset + 1]);
+        landmark->set_y(raw_landmarks[offset + 1]);
      }
    }
    if (num_dimensions > 2) {
-      landmark.set_z(raw_landmarks[offset + 2]);
+      landmark->set_z(raw_landmarks[offset + 2]);
    }
-    output_landmarks->push_back(landmark);
  }

  // Output normalized landmarks if required.
  if (cc->Outputs().HasTag("NORM_LANDMARKS")) {
-    auto output_norm_landmarks =
-        absl::make_unique<std::vector<NormalizedLandmark>>();
-    for (const auto& landmark : *output_landmarks) {
-      NormalizedLandmark norm_landmark;
-      norm_landmark.set_x(static_cast<float>(landmark.x()) /
-                          options_.input_image_width());
-      norm_landmark.set_y(static_cast<float>(landmark.y()) /
-                          options_.input_image_height());
-      norm_landmark.set_z(landmark.z() / options_.normalize_z());
-
-      output_norm_landmarks->push_back(norm_landmark);
+    NormalizedLandmarkList output_norm_landmarks;
+    // for (const auto& landmark : output_landmarks) {
+    for (int i = 0; i < output_landmarks.landmark_size(); ++i) {
+      const Landmark& landmark = output_landmarks.landmark(i);
+      NormalizedLandmark* norm_landmark = output_norm_landmarks.add_landmark();
+      norm_landmark->set_x(static_cast<float>(landmark.x()) /
+                           options_.input_image_width());
+      norm_landmark->set_y(static_cast<float>(landmark.y()) /
+                           options_.input_image_height());
+      norm_landmark->set_z(landmark.z() / options_.normalize_z());
    }
    cc->Outputs()
        .Tag("NORM_LANDMARKS")
-        .Add(output_norm_landmarks.release(), cc->InputTimestamp());
+        .AddPacket(MakePacket<NormalizedLandmarkList>(output_norm_landmarks)
+                       .At(cc->InputTimestamp()));
  }
+
  // Output absolute landmarks.
  if (cc->Outputs().HasTag("LANDMARKS")) {
    cc->Outputs()
        .Tag("LANDMARKS")
-        .Add(output_landmarks.release(), cc->InputTimestamp());
+        .AddPacket(MakePacket<LandmarkList>(output_landmarks)
+                       .At(cc->InputTimestamp()));
  }

  return ::mediapipe::OkStatus();
@@ -28,7 +28,7 @@
 #include "mediapipe/util/resource_util.h"
 #include "tensorflow/lite/interpreter.h"

-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
 #include "mediapipe/gpu/gl_calculator_helper.h"
 #include "mediapipe/gpu/gl_simple_shaders.h"
 #include "mediapipe/gpu/shader_util.h"
@@ -53,7 +53,7 @@ float Clamp(float val, float min, float max) {

 namespace mediapipe {

-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
 using ::tflite::gpu::gl::CopyBuffer;
 using ::tflite::gpu::gl::CreateReadWriteRgbaImageTexture;
 using ::tflite::gpu::gl::CreateReadWriteShaderStorageBuffer;
@@ -129,7 +129,7 @@ class TfLiteTensorsToSegmentationCalculator : public CalculatorBase {
  int tensor_channels_ = 0;

  bool use_gpu_ = false;
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  mediapipe::GlCalculatorHelper gpu_helper_;
  std::unique_ptr<GlProgram> mask_program_with_prev_;
  std::unique_ptr<GlProgram> mask_program_no_prev_;
@@ -159,7 +159,7 @@ REGISTER_CALCULATOR(TfLiteTensorsToSegmentationCalculator);
  }

  // Inputs GPU.
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  if (cc->Inputs().HasTag("TENSORS_GPU")) {
    cc->Inputs().Tag("TENSORS_GPU").Set<std::vector<GlBuffer>>();
    use_gpu |= true;
@@ -178,7 +178,7 @@ REGISTER_CALCULATOR(TfLiteTensorsToSegmentationCalculator);
  if (cc->Outputs().HasTag("MASK")) {
    cc->Outputs().Tag("MASK").Set<ImageFrame>();
  }
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  if (cc->Outputs().HasTag("MASK_GPU")) {
    cc->Outputs().Tag("MASK_GPU").Set<mediapipe::GpuBuffer>();
    use_gpu |= true;
@@ -186,7 +186,7 @@ REGISTER_CALCULATOR(TfLiteTensorsToSegmentationCalculator);
 #endif  //  !MEDIAPIPE_DISABLE_GPU

  if (use_gpu) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
    MP_RETURN_IF_ERROR(mediapipe::GlCalculatorHelper::UpdateContract(cc));
 #endif  //  !MEDIAPIPE_DISABLE_GPU
  }
@@ -199,7 +199,7 @@ REGISTER_CALCULATOR(TfLiteTensorsToSegmentationCalculator);

  if (cc->Inputs().HasTag("TENSORS_GPU")) {
    use_gpu_ = true;
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
    MP_RETURN_IF_ERROR(gpu_helper_.Open(cc));
 #endif  //  !MEDIAPIPE_DISABLE_GPU
  }
@@ -207,7 +207,7 @@ REGISTER_CALCULATOR(TfLiteTensorsToSegmentationCalculator);
  MP_RETURN_IF_ERROR(LoadOptions(cc));

  if (use_gpu_) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
    MP_RETURN_IF_ERROR(
        gpu_helper_.RunInGlContext([this, cc]() -> ::mediapipe::Status {
          MP_RETURN_IF_ERROR(InitGpu(cc));
@@ -224,7 +224,7 @@ REGISTER_CALCULATOR(TfLiteTensorsToSegmentationCalculator);
 ::mediapipe::Status TfLiteTensorsToSegmentationCalculator::Process(
    CalculatorContext* cc) {
  if (use_gpu_) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
    MP_RETURN_IF_ERROR(
        gpu_helper_.RunInGlContext([this, cc]() -> ::mediapipe::Status {
          MP_RETURN_IF_ERROR(ProcessGpu(cc));
@@ -240,7 +240,7 @@ REGISTER_CALCULATOR(TfLiteTensorsToSegmentationCalculator);

 ::mediapipe::Status TfLiteTensorsToSegmentationCalculator::Close(
    CalculatorContext* cc) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  gpu_helper_.RunInGlContext([this] {
    if (upsample_program_) glDeleteProgram(upsample_program_);
    upsample_program_ = 0;
@@ -367,7 +367,7 @@ REGISTER_CALCULATOR(TfLiteTensorsToSegmentationCalculator);
  if (cc->Inputs().Tag("TENSORS_GPU").IsEmpty()) {
    return ::mediapipe::OkStatus();
  }
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  // Get input streams.
  const auto& input_tensors =
      cc->Inputs().Tag("TENSORS_GPU").Get<std::vector<GlBuffer>>();
@@ -453,7 +453,7 @@ REGISTER_CALCULATOR(TfLiteTensorsToSegmentationCalculator);
 }

 void TfLiteTensorsToSegmentationCalculator::GlRender() {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  static const GLfloat square_vertices[] = {
      -1.0f, -1.0f,  // bottom left
      1.0f,  -1.0f,  // bottom right
@@ -525,7 +525,7 @@ void TfLiteTensorsToSegmentationCalculator::GlRender() {

 ::mediapipe::Status TfLiteTensorsToSegmentationCalculator::InitGpu(
    CalculatorContext* cc) {
-#if !defined(MEDIAPIPE_DISABLE_GPU) && !defined(__APPLE__)
+#if !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  MP_RETURN_IF_ERROR(gpu_helper_.RunInGlContext([this]()
                                                    -> ::mediapipe::Status {
    // A shader to process a segmentation tensor into an output mask,
@@ -15,11 +15,11 @@
 #ifndef MEDIAPIPE_CALCULATORS_TFLITE_UTIL_H_
 #define MEDIAPIPE_CALCULATORS_TFLITE_UTIL_H_

-#define RET_CHECK_CALL(call)                                     \
-  do {                                                           \
-    const auto status = (call);                                  \
-    if (ABSL_PREDICT_FALSE(!status.ok()))                        \
-      return ::mediapipe::InternalError(status.error_message()); \
+#define RET_CHECK_CALL(call)                               \
+  do {                                                     \
+    const auto status = (call);                            \
+    if (ABSL_PREDICT_FALSE(!status.ok()))                  \
+      return ::mediapipe::InternalError(status.message()); \
  } while (0);

 #endif  // MEDIAPIPE_CALCULATORS_TFLITE_UTIL_H_
@@ -12,14 +12,14 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.

+load("//mediapipe/framework/port:build_config.bzl", "mediapipe_cc_proto_library")
+
 licenses(["notice"])  # Apache 2.0

-package(default_visibility = ["//visibility:private"])
+package(default_visibility = ["//visibility:public"])

 exports_files(["LICENSE"])

-load("//mediapipe/framework/port:build_config.bzl", "mediapipe_cc_proto_library")
-
 proto_library(
    name = "annotation_overlay_calculator_proto",
    srcs = ["annotation_overlay_calculator.proto"],
@@ -39,6 +39,15 @@ proto_library(
    ],
 )

+proto_library(
+    name = "timed_box_list_id_to_label_calculator_proto",
+    srcs = ["timed_box_list_id_to_label_calculator.proto"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_proto",
+    ],
+)
+
 proto_library(
    name = "latency_proto",
    srcs = ["latency.proto"],
@@ -72,6 +81,24 @@ proto_library(
    ],
 )

+proto_library(
+    name = "collection_has_min_size_calculator_proto",
+    srcs = ["collection_has_min_size_calculator.proto"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_proto",
+    ],
+)
+
+proto_library(
+    name = "association_calculator_proto",
+    srcs = ["association_calculator.proto"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_proto",
+    ],
+)
+
 mediapipe_cc_proto_library(
    name = "annotation_overlay_calculator_cc_proto",
    srcs = ["annotation_overlay_calculator.proto"],
@@ -95,6 +122,18 @@ mediapipe_cc_proto_library(
    ],
 )

+mediapipe_cc_proto_library(
+    name = "timed_box_list_id_to_label_calculator_cc_proto",
+    srcs = ["timed_box_list_id_to_label_calculator.proto"],
+    cc_deps = [
+        "//mediapipe/framework:calculator_cc_proto",
+    ],
+    visibility = ["//visibility:public"],
+    deps = [
+        ":timed_box_list_id_to_label_calculator_proto",
+    ],
+)
+
 mediapipe_cc_proto_library(
    name = "latency_cc_proto",
    srcs = ["latency.proto"],
@@ -141,6 +180,26 @@ mediapipe_cc_proto_library(
    ],
 )

+mediapipe_cc_proto_library(
+    name = "collection_has_min_size_calculator_cc_proto",
+    srcs = ["collection_has_min_size_calculator.proto"],
+    cc_deps = [
+        "//mediapipe/framework:calculator_cc_proto",
+    ],
+    visibility = ["//mediapipe:__subpackages__"],
+    deps = [":collection_has_min_size_calculator_proto"],
+)
+
+mediapipe_cc_proto_library(
+    name = "association_calculator_cc_proto",
+    srcs = ["association_calculator.proto"],
+    cc_deps = [
+        "//mediapipe/framework:calculator_cc_proto",
+    ],
+    visibility = ["//mediapipe:__subpackages__"],
+    deps = [":association_calculator_proto"],
+)
+
 cc_library(
    name = "packet_frequency_calculator",
    srcs = ["packet_frequency_calculator.cc"],
@@ -234,6 +293,7 @@ cc_library(
        "//mediapipe/framework/port:status",
        "//mediapipe/framework/port:vector",
        "//mediapipe/util:annotation_renderer",
+        "//mediapipe/util:render_data_cc_proto",
    ] + select({
        "//mediapipe/gpu:disable_gpu": [],
        "//conditions:default": [
@@ -261,7 +321,35 @@ cc_library(
        "//mediapipe:android": [
            "//mediapipe/util/android/file/base",
        ],
-        "//mediapipe:apple": [
+        "//mediapipe:ios": [
+            "//mediapipe/util/android/file/base",
+        ],
+        "//mediapipe:macos": [
+            "//mediapipe/framework/port:file_helpers",
+        ],
+        "//conditions:default": [
+            "//mediapipe/framework/port:file_helpers",
+        ],
+    }),
+    alwayslink = 1,
+)
+
+cc_library(
+    name = "timed_box_list_id_to_label_calculator",
+    srcs = ["timed_box_list_id_to_label_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        ":timed_box_list_id_to_label_calculator_cc_proto",
+        "//mediapipe/framework/port:status",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:packet",
+        "//mediapipe/util/tracking:box_tracker_cc_proto",
+        "//mediapipe/util:resource_util",
+    ] + select({
+        "//mediapipe:android": [
+            "//mediapipe/util/android/file/base",
+        ],
+        "//mediapipe:ios": [
            "//mediapipe/util/android/file/base",
        ],
        "//mediapipe:macos": [
@@ -360,6 +448,16 @@ mediapipe_cc_proto_library(
    deps = [":landmark_projection_calculator_proto"],
 )

+mediapipe_cc_proto_library(
+    name = "landmarks_to_floats_calculator_cc_proto",
+    srcs = ["landmarks_to_floats_calculator.proto"],
+    cc_deps = [
+        "//mediapipe/framework:calculator_cc_proto",
+    ],
+    visibility = ["//visibility:public"],
+    deps = [":landmarks_to_floats_calculator_proto"],
+)
+
 mediapipe_cc_proto_library(
    name = "rect_transformation_calculator_cc_proto",
    srcs = ["rect_transformation_calculator.proto"],
@@ -372,7 +470,12 @@ mediapipe_cc_proto_library(

 cc_library(
    name = "detections_to_rects_calculator",
-    srcs = ["detections_to_rects_calculator.cc"],
+    srcs = [
+        "detections_to_rects_calculator.cc",
+    ],
+    hdrs = [
+        "detections_to_rects_calculator.h",
+    ],
    visibility = ["//visibility:public"],
    deps = [
        ":detections_to_rects_calculator_cc_proto",
@@ -383,6 +486,7 @@ cc_library(
        "//mediapipe/framework/formats:rect_cc_proto",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
+        "@com_google_absl//absl/types:optional",
    ],
    alwayslink = 1,
 )
@@ -454,6 +558,28 @@ proto_library(
    ],
 )

+proto_library(
+    name = "timed_box_list_to_render_data_calculator_proto",
+    srcs = ["timed_box_list_to_render_data_calculator.proto"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_proto",
+        "//mediapipe/util:color_proto",
+        "//mediapipe/util:render_data_proto",
+    ],
+)
+
+proto_library(
+    name = "labels_to_render_data_calculator_proto",
+    srcs = ["labels_to_render_data_calculator.proto"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_proto",
+        "//mediapipe/util:color_proto",
+        "//mediapipe/util:render_data_proto",
+    ],
+)
+
 proto_library(
    name = "thresholding_calculator_proto",
    srcs = ["thresholding_calculator.proto"],
@@ -483,6 +609,15 @@ proto_library(
    ],
 )

+proto_library(
+    name = "landmarks_to_floats_calculator_proto",
+    srcs = ["landmarks_to_floats_calculator.proto"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_proto",
+    ],
+)
+
 proto_library(
    name = "rect_transformation_calculator_proto",
    srcs = ["rect_transformation_calculator.proto"],
@@ -577,6 +712,57 @@ cc_library(
    alwayslink = 1,
 )

+mediapipe_cc_proto_library(
+    name = "timed_box_list_to_render_data_calculator_cc_proto",
+    srcs = ["timed_box_list_to_render_data_calculator.proto"],
+    cc_deps = [
+        "//mediapipe/framework:calculator_cc_proto",
+        "//mediapipe/util:color_cc_proto",
+        "//mediapipe/util:render_data_cc_proto",
+    ],
+    visibility = ["//visibility:public"],
+    deps = [":timed_box_list_to_render_data_calculator_proto"],
+)
+
+cc_library(
+    name = "timed_box_list_to_render_data_calculator",
+    srcs = ["timed_box_list_to_render_data_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        ":timed_box_list_to_render_data_calculator_cc_proto",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:calculator_options_cc_proto",
+        "//mediapipe/framework/port:ret_check",
+        "//mediapipe/util:color_cc_proto",
+        "//mediapipe/util:render_data_cc_proto",
+        "//mediapipe/util/tracking:box_tracker_cc_proto",
+        "//mediapipe/util/tracking:tracking_cc_proto",
+        "@com_google_absl//absl/memory",
+        "@com_google_absl//absl/strings",
+    ],
+    alwayslink = 1,
+)
+
+cc_library(
+    name = "labels_to_render_data_calculator",
+    srcs = ["labels_to_render_data_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        ":labels_to_render_data_calculator_cc_proto",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:calculator_options_cc_proto",
+        "//mediapipe/framework/formats:classification_cc_proto",
+        "//mediapipe/framework/formats:video_stream_header",
+        "//mediapipe/framework/port:ret_check",
+        "//mediapipe/framework/port:status",
+        "//mediapipe/framework/port:statusor",
+        "//mediapipe/util:color_cc_proto",
+        "//mediapipe/util:render_data_cc_proto",
+        "@com_google_absl//absl/strings",
+    ],
+    alwayslink = 1,
+)
+
 cc_library(
    name = "rect_to_render_data_calculator",
    srcs = ["rect_to_render_data_calculator.cc"],
@@ -658,6 +844,22 @@ cc_library(
    alwayslink = 1,
 )

+cc_library(
+    name = "landmarks_to_floats_calculator",
+    srcs = ["landmarks_to_floats_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        ":landmarks_to_floats_calculator_cc_proto",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/formats:landmark_cc_proto",
+        "//mediapipe/framework/formats:matrix",
+        "//mediapipe/framework/port:ret_check",
+        "//mediapipe/framework/port:status",
+        "@eigen_archive//:eigen",
+    ],
+    alwayslink = 1,
+)
+
 cc_test(
    name = "detection_letterbox_removal_calculator_test",
    srcs = ["detection_letterbox_removal_calculator_test.cc"],
@@ -714,6 +916,7 @@ cc_library(
    visibility = ["//visibility:public"],
    deps = [
        ":top_k_scores_calculator_cc_proto",
+        "//mediapipe/framework/formats:classification_cc_proto",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "//mediapipe/framework/port:statusor",
@@ -723,7 +926,7 @@ cc_library(
        "//mediapipe:android": [
            "//mediapipe/util/android/file/base",
        ],
-        "//mediapipe:apple": [
+        "//mediapipe:ios": [
            "//mediapipe/util/android/file/base",
        ],
        "//mediapipe:macos": [
@@ -750,3 +953,180 @@ cc_test(
        "//mediapipe/framework/port:status",
    ],
 )
+
+mediapipe_cc_proto_library(
+    name = "labels_to_render_data_calculator_cc_proto",
+    srcs = ["labels_to_render_data_calculator.proto"],
+    cc_deps = [
+        "//mediapipe/framework:calculator_cc_proto",
+        "//mediapipe/util:color_cc_proto",
+    ],
+    visibility = ["//visibility:public"],
+    deps = [":labels_to_render_data_calculator_proto"],
+)
+
+cc_library(
+    name = "local_file_contents_calculator",
+    srcs = ["local_file_contents_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/port:ret_check",
+        "//mediapipe/framework/port:status",
+        "//mediapipe/util:resource_util",
+    ],
+    alwayslink = 1,
+)
+
+cc_library(
+    name = "local_file_pattern_contents_calculator",
+    srcs = ["local_file_pattern_contents_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/port:file_helpers",
+        "//mediapipe/framework/port:ret_check",
+        "//mediapipe/framework/port:status",
+    ],
+    alwayslink = 1,
+)
+
+cc_library(
+    name = "filter_collection_calculator",
+    srcs = ["filter_collection_calculator.cc"],
+    hdrs = ["filter_collection_calculator.h"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/formats:classification_cc_proto",
+        "//mediapipe/framework/formats:landmark_cc_proto",
+        "//mediapipe/framework/formats:rect_cc_proto",
+        "//mediapipe/framework/port:ret_check",
+        "//mediapipe/framework/port:status",
+        "@com_google_absl//absl/strings",
+    ],
+    alwayslink = 1,
+)
+
+cc_library(
+    name = "collection_has_min_size_calculator",
+    srcs = ["collection_has_min_size_calculator.cc"],
+    hdrs = ["collection_has_min_size_calculator.h"],
+    visibility = ["//visibility:public"],
+    deps = [
+        ":collection_has_min_size_calculator_cc_proto",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/formats:landmark_cc_proto",
+        "//mediapipe/framework/formats:rect_cc_proto",
+        "//mediapipe/framework/port:ret_check",
+        "//mediapipe/framework/port:status",
+    ],
+    alwayslink = 1,
+)
+
+cc_test(
+    name = "collection_has_min_size_calculator_test",
+    srcs = ["collection_has_min_size_calculator_test.cc"],
+    deps = [
+        ":collection_has_min_size_calculator",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:calculator_runner",
+        "//mediapipe/framework/port:gtest_main",
+        "//mediapipe/framework/port:parse_text_proto",
+    ],
+)
+
+cc_library(
+    name = "association_calculator",
+    hdrs = ["association_calculator.h"],
+    visibility = ["//visibility:public"],
+    deps = [
+        ":association_calculator_cc_proto",
+        "//mediapipe/framework:calculator_context",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:collection_item_id",
+        "//mediapipe/framework/port:rectangle",
+        "//mediapipe/framework/port:status",
+        "@com_google_absl//absl/memory",
+    ],
+    alwayslink = 1,
+)
+
+cc_library(
+    name = "association_norm_rect_calculator",
+    srcs = ["association_norm_rect_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        ":association_calculator",
+        "//mediapipe/framework:calculator_context",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/formats:rect_cc_proto",
+        "//mediapipe/framework/port:rectangle",
+        "//mediapipe/framework/port:status",
+    ],
+    alwayslink = 1,
+)
+
+cc_library(
+    name = "association_detection_calculator",
+    srcs = ["association_detection_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        ":association_calculator",
+        "//mediapipe/framework:calculator_context",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/formats:detection_cc_proto",
+        "//mediapipe/framework/formats:location",
+        "//mediapipe/framework/port:rectangle",
+        "//mediapipe/framework/port:status",
+    ],
+    alwayslink = 1,
+)
+
+cc_test(
+    name = "association_calculator_test",
+    srcs = ["association_calculator_test.cc"],
+    deps = [
+        ":association_detection_calculator",
+        ":association_norm_rect_calculator",
+        "//mediapipe/framework:calculator_cc_proto",
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework:calculator_runner",
+        "//mediapipe/framework:collection_item_id",
+        "//mediapipe/framework:packet",
+        "//mediapipe/framework/deps:message_matchers",
+        "//mediapipe/framework/formats:detection_cc_proto",
+        "//mediapipe/framework/formats:location_data_cc_proto",
+        "//mediapipe/framework/formats:rect_cc_proto",
+        "//mediapipe/framework/port:gtest_main",
+        "//mediapipe/framework/port:parse_text_proto",
+    ],
+)
+
+cc_library(
+    name = "detections_to_timed_box_list_calculator",
+    srcs = ["detections_to_timed_box_list_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/formats:detection_cc_proto",
+        "//mediapipe/framework/formats:location_data_cc_proto",
+        "//mediapipe/framework/port:ret_check",
+        "//mediapipe/framework/port:status",
+        "//mediapipe/util/tracking:box_tracker",
+    ],
+    alwayslink = 1,
+)
+
+cc_library(
+    name = "detection_unique_id_calculator",
+    srcs = ["detection_unique_id_calculator.cc"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//mediapipe/framework:calculator_framework",
+        "//mediapipe/framework/formats:detection_cc_proto",
+        "//mediapipe/framework/port:ret_check",
+        "//mediapipe/framework/port:status",
+    ],
+    alwayslink = 1,
+)
@@ -26,6 +26,7 @@
 #include "mediapipe/framework/port/vector.h"
 #include "mediapipe/util/annotation_renderer.h"
 #include "mediapipe/util/color.pb.h"
+#include "mediapipe/util/render_data.pb.h"

 #if !defined(MEDIAPIPE_DISABLE_GPU)
 #include "mediapipe/gpu/gl_calculator_helper.h"
@@ -38,11 +39,13 @@ namespace mediapipe {

 namespace {

-constexpr char kInputFrameTag[] = "INPUT_FRAME";
-constexpr char kOutputFrameTag[] = "OUTPUT_FRAME";
+constexpr char kInputFrameTag[] = "IMAGE";
+constexpr char kOutputFrameTag[] = "IMAGE";

-constexpr char kInputFrameTagGpu[] = "INPUT_FRAME_GPU";
-constexpr char kOutputFrameTagGpu[] = "OUTPUT_FRAME_GPU";
+constexpr char kInputVectorTag[] = "VECTOR";
+
+constexpr char kInputFrameTagGpu[] = "IMAGE_GPU";
+constexpr char kOutputFrameTagGpu[] = "IMAGE_GPU";

 enum { ATTRIB_VERTEX, ATTRIB_TEXTURE_POSITION, NUM_ATTRIBUTES };

@@ -52,22 +55,25 @@ size_t RoundUp(size_t n, size_t m) { return ((n + m - 1) / m) * m; }  // NOLINT
 // When using GPU, this color will become transparent when the calculator
 // merges the annotation overlay with the image frame. As a result, drawing in
 // this color is not supported and it should be set to something unlikely used.
-constexpr int kAnnotationBackgroundColor[] = {100, 101, 102};
+constexpr uchar kAnnotationBackgroundColor = 2;  // Grayscale value.
 }  // namespace

 // A calculator for rendering data on images.
 //
 // Inputs:
-//  1. INPUT_FRAME or INPUT_FRAME_GPU (optional): An ImageFrame (or GpuBuffer)
+//  1. IMAGE or IMAGE_GPU (optional): An ImageFrame (or GpuBuffer)
 //     containing the input image.
 //     If output is CPU, and input isn't provided, the renderer creates a
 //     blank canvas with the width, height and color provided in the options.
 //  2. RenderData proto on variable number of input streams. All the RenderData
 //     at a particular timestamp is drawn on the image in the order of their
 //     input streams. No tags required.
+//  3. std::vector<RenderData> on variable number of input streams. RenderData
+//     objects at a particular timestamp are drawn on the image in order of the
+//     input vector items. These input streams are tagged with "VECTOR".
 //
 // Output:
-//  1. OUTPUT_FRAME or OUTPUT_FRAME_GPU: A rendered ImageFrame (or GpuBuffer).
+//  1. IMAGE or IMAGE_GPU: A rendered ImageFrame (or GpuBuffer).
 //
 // For CPU input frames, only SRGBA, SRGB and GRAY8 format are supported. The
 // output format is the same as input except for GRAY8 where the output is in
@@ -81,11 +87,13 @@ constexpr int kAnnotationBackgroundColor[] = {100, 101, 102};
 // Example config (CPU):
 // node {
 //   calculator: "AnnotationOverlayCalculator"
-//   input_stream: "INPUT_FRAME:image_frames"
+//   input_stream: "IMAGE:image_frames"
 //   input_stream: "render_data_1"
 //   input_stream: "render_data_2"
 //   input_stream: "render_data_3"
-//   output_stream: "OUTPUT_FRAME:decorated_frames"
+//   input_stream: "VECTOR:0:render_data_vec_0"
+//   input_stream: "VECTOR:1:render_data_vec_1"
+//   output_stream: "IMAGE:decorated_frames"
 //   options {
 //     [mediapipe.AnnotationOverlayCalculatorOptions.ext] {
 //     }
@@ -95,11 +103,13 @@ constexpr int kAnnotationBackgroundColor[] = {100, 101, 102};
 // Example config (GPU):
 // node {
 //   calculator: "AnnotationOverlayCalculator"
-//   input_stream: "INPUT_FRAME_GPU:image_frames"
+//   input_stream: "IMAGE_GPU:image_frames"
 //   input_stream: "render_data_1"
 //   input_stream: "render_data_2"
 //   input_stream: "render_data_3"
-//   output_stream: "OUTPUT_FRAME_GPU:decorated_frames"
+//   input_stream: "VECTOR:0:render_data_vec_0"
+//   input_stream: "VECTOR:1:render_data_vec_1"
+//   output_stream: "IMAGE_GPU:decorated_frames"
 //   options {
 //     [mediapipe.AnnotationOverlayCalculatorOptions.ext] {
 //     }
@@ -138,9 +148,6 @@ class AnnotationOverlayCalculator : public CalculatorBase {
  // Underlying helper renderer library.
  std::unique_ptr<AnnotationRenderer> renderer_;

-  // Number of input streams with render data.
-  int num_render_streams_;
-
  // Indicates if image frame is available as input.
  bool image_frame_available_ = false;

@@ -171,25 +178,28 @@ REGISTER_CALCULATOR(AnnotationOverlayCalculator);
    return ::mediapipe::InternalError("GPU output must have GPU input.");
  }

-  // Assume all inputs are render streams; adjust below.
-  int num_render_streams = cc->Inputs().NumEntries();
-
  // Input image to render onto copy of.
 #if !defined(MEDIAPIPE_DISABLE_GPU)
  if (cc->Inputs().HasTag(kInputFrameTagGpu)) {
    cc->Inputs().Tag(kInputFrameTagGpu).Set<mediapipe::GpuBuffer>();
-    num_render_streams = cc->Inputs().NumEntries() - 1;
    use_gpu |= true;
  }
 #endif  //  !MEDIAPIPE_DISABLE_GPU
  if (cc->Inputs().HasTag(kInputFrameTag)) {
    cc->Inputs().Tag(kInputFrameTag).Set<ImageFrame>();
-    num_render_streams = cc->Inputs().NumEntries() - 1;
  }

  // Data streams to render.
-  for (int i = 0; i < num_render_streams; ++i) {
-    cc->Inputs().Index(i).Set<RenderData>();
+  for (CollectionItemId id = cc->Inputs().BeginId(); id < cc->Inputs().EndId();
+       ++id) {
+    auto tag_and_index = cc->Inputs().TagAndIndexFromId(id);
+    std::string tag = tag_and_index.first;
+    if (tag == kInputVectorTag) {
+      cc->Inputs().Get(id).Set<std::vector<RenderData>>();
+    } else if (tag.empty()) {
+      // Empty tag defaults to accepting a single object of RenderData type.
+      cc->Inputs().Get(id).Set<RenderData>();
+    }
  }

  // Rendered image.
@@ -228,12 +238,10 @@ REGISTER_CALCULATOR(AnnotationOverlayCalculator);
  if (cc->Inputs().HasTag(kInputFrameTagGpu) ||
      cc->Inputs().HasTag(kInputFrameTag)) {
    image_frame_available_ = true;
-    num_render_streams_ = cc->Inputs().NumEntries() - 1;
  } else {
    image_frame_available_ = false;
    RET_CHECK(options_.has_canvas_width_px());
    RET_CHECK(options_.has_canvas_height_px());
-    num_render_streams_ = cc->Inputs().NumEntries();
  }

  // Initialize the helper renderer library.
@@ -285,12 +293,28 @@ REGISTER_CALCULATOR(AnnotationOverlayCalculator);
  renderer_->AdoptImage(image_mat.get());

  // Render streams onto render target.
-  for (int i = 0; i < num_render_streams_; ++i) {
-    if (cc->Inputs().Index(i).IsEmpty()) {
+  for (CollectionItemId id = cc->Inputs().BeginId(); id < cc->Inputs().EndId();
+       ++id) {
+    auto tag_and_index = cc->Inputs().TagAndIndexFromId(id);
+    std::string tag = tag_and_index.first;
+    if (!tag.empty() && tag != kInputVectorTag) {
      continue;
    }
-    const RenderData& render_data = cc->Inputs().Index(i).Get<RenderData>();
-    renderer_->RenderDataOnImage(render_data);
+    if (cc->Inputs().Get(id).IsEmpty()) {
+      continue;
+    }
+    if (tag.empty()) {
+      // Empty tag defaults to accepting a single object of RenderData type.
+      const RenderData& render_data = cc->Inputs().Get(id).Get<RenderData>();
+      renderer_->RenderDataOnImage(render_data);
+    } else {
+      RET_CHECK_EQ(kInputVectorTag, tag);
+      const std::vector<RenderData>& render_data_vec =
+          cc->Inputs().Get(id).Get<std::vector<RenderData>>();
+      for (const RenderData& render_data : render_data_vec) {
+        renderer_->RenderDataOnImage(render_data);
+      }
+    }
  }

  if (use_gpu_) {
@@ -467,11 +491,9 @@ REGISTER_CALCULATOR(AnnotationOverlayCalculator);
    if (format != mediapipe::ImageFormat::SRGBA &&
        format != mediapipe::ImageFormat::SRGB)
      RET_CHECK_FAIL() << "Unsupported GPU input format: " << format;
-
-    image_mat = absl::make_unique<cv::Mat>(
-        height_, width_, CV_8UC3,
-        cv::Scalar(kAnnotationBackgroundColor[0], kAnnotationBackgroundColor[1],
-                   kAnnotationBackgroundColor[2]));
+    image_mat = absl::make_unique<cv::Mat>(height_, width_, CV_8UC3);
+    memset(image_mat->data, kAnnotationBackgroundColor,
+           height_ * width_ * image_mat->elemSize());
  } else {
    image_mat = absl::make_unique<cv::Mat>(
        options_.canvas_height_px(), options_.canvas_width_px(), CV_8UC3,
@@ -593,9 +615,9 @@ REGISTER_CALCULATOR(AnnotationOverlayCalculator);
  glUniform1i(glGetUniformLocation(program_, "input_frame"), 1);
  glUniform1i(glGetUniformLocation(program_, "overlay"), 2);
  glUniform3f(glGetUniformLocation(program_, "transparent_color"),
-              kAnnotationBackgroundColor[0] / 255.0,
-              kAnnotationBackgroundColor[1] / 255.0,
-              kAnnotationBackgroundColor[2] / 255.0);
+              kAnnotationBackgroundColor / 255.0,
+              kAnnotationBackgroundColor / 255.0,
+              kAnnotationBackgroundColor / 255.0);

  // Init texture for opencv rendered frame.
  const auto& input_frame =
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
MediaPipe Teamandjqtang	4c68eb4a70	Project import generated by Copybara. GitOrigin-RevId: da3cb82c964457b1c719c915a48e545b980af64b	2020-04-06 21:28:19 -07:00
MediaPipe Teamandjqtang	a3d36eee32	Project import generated by Copybara. GitOrigin-RevId: 53a42bf7ad836321123cb7b6c80b0f2e13fbf83e	2020-04-06 19:14:13 -07:00
MediaPipe Teamandjqtang	1722d4b8a2	Project import generated by Copybara. GitOrigin-RevId: 43cd697ec87dcc5cab5051f27960bb77a057399d	2020-03-20 15:28:51 -07:00
MediaPipe Teamandjqtang	3b6d3c4058	Project import generated by Copybara. GitOrigin-RevId: 4419aaa472eeb91123d1f8576188166ee0e5ea69	2020-03-10 18:14:25 -07:00
MediaPipe Teamandjqtang	252a5713c7	Project import generated by Copybara. GitOrigin-RevId: 6f964e58d874e47fb6207aa97d060a4cd6428527	2020-03-02 10:35:07 -08:00
MediaPipe TeamandHadon Nash	de4fbc10e6	Project import generated by Copybara. GitOrigin-RevId: 852dfb05d450167899c0dd5ef7c45622a12e865b	2020-02-10 14:13:25 -08:00
MediaPipe Teamandjqtang	d144e564d8	Project import generated by Copybara. GitOrigin-RevId: df2c4ee5ecd342bd88f332389348615b47a0244c	2020-01-17 17:05:43 -08:00
MediaPipe Teamandchris	dd02df1dbe	Project import generated by Copybara. GitOrigin-RevId: b695dda274aa3ac3c7d054e150bd9eb5c1285b19	2020-01-17 15:49:22 -08:00
MediaPipe Teamandjqtang	66b377c825	Project import generated by Copybara. GitOrigin-RevId: 1dd19723270084e701a90f974e35754b3fe20265	2020-01-13 14:42:47 -08:00
MediaPipe Teamandjqtang	bf5185f122	Project import generated by Copybara. GitOrigin-RevId: 72933af9ce469acd89cbf41898dcc06c65df7c8a	2020-01-11 11:16:13 -08:00
MediaPipe Teamandjqtang	a2823541e6	Project import generated by Copybara. GitOrigin-RevId: 1237f560f10007d74f620349f9fe27b492f5faf6	2020-01-10 15:51:18 -08:00
MediaPipe TeamandHadon Nash	ae6be10afe	Project import generated by Copybara. GitOrigin-RevId: 0517756260533d374df93679965ca662d0ec6943	2020-01-10 13:13:24 -08:00
MediaPipe Teamandjqtang	38ee2603a7	Project import generated by Copybara. GitOrigin-RevId: 87e46800807001e01d686fd7bcc2533714556920	2019-12-09 13:11:22 -08:00
MediaPipe Teamandjqtang	86b3283b2f	Project import generated by Copybara. GitOrigin-RevId: 831b7eb6038549a3a5047e7a113d6a11956e2de9	2019-12-06 16:17:14 -08:00
MediaPipe Teamandjqtang	7d470a1335	Project import generated by Copybara. GitOrigin-RevId: 398d8577074c6e93041c01ed34bd6f27b2773c4f	2019-12-06 16:07:44 -08:00
MediaPipe Teamandmgyong	d16cc3be5b	Project import generated by Copybara. GitOrigin-RevId: d91373b4d4d10abef49cab410caa6aadf0875049	2019-12-06 15:57:20 -08:00
MediaPipe Teamandjqtang	137867d088	Project import generated by Copybara. GitOrigin-RevId: e3566e5029af25b0fc4b1071a49e49ae20aa5df6	2019-12-02 17:54:10 -08:00
MediaPipe Teamandmgyong	446d7cf6b6	Project import generated by Copybara. GitOrigin-RevId: b02a6442fa6234cd2c15fa19f09accd8767adbee	2019-11-21 14:48:32 -08:00
MediaPipe Teamandmgyong	90f72bd851	Project import generated by Copybara. GitOrigin-RevId: 5aa039c4a51ab7b4a1c58c17ad13af4c833e25e7	2019-11-21 14:35:46 -08:00
MediaPipe Teamandmgyong	4285aeddfc	Project import generated by Copybara. GitOrigin-RevId: 651ba7a75bb696877570a8a1b4244b34d59088f8	2019-11-21 14:24:17 -08:00
MediaPipe Teamandmgyong	37287925b0	Project import generated by Copybara. GitOrigin-RevId: ba1d851bc868c2f8037a6fa96ee90e4b8ab9bd40	2019-11-21 14:10:52 -08:00
MediaPipe Teamandmgyong	48bcbb115f	Project import generated by Copybara. GitOrigin-RevId: 50714fe28298d7b707eff7304547d89d6ec34a54	2019-11-21 13:20:47 -08:00
MediaPipe Teamandjqtang	9437483827	Project import generated by Copybara. GitOrigin-RevId: 5aca6b3f07b67e09988a901f50f595ca5f566e67	2019-11-15 13:10:50 -08:00
MediaPipe Teamandjqtang	d030c13931	Project import generated by Copybara. GitOrigin-RevId: dab808e56f90d1ad93e6014869f7fe4646b67fe0	2019-11-11 22:59:01 -08:00
MediaPipe Teamandjqtang	fce372d153	Project import generated by Copybara. GitOrigin-RevId: ac03a471f5b9df34de46dd684202e4365c5ceac3	2019-10-29 15:59:27 -07:00
MediaPipe Teamandjqtang	c6fea4c9d9	Project import generated by Copybara. GitOrigin-RevId: 1a0caa03bbf3673dbe772c8045b687c6b6821bcc	2019-10-25 14:50:09 -07:00
MediaPipe Teamandjqtang	259b48e082	Project import generated by Copybara. GitOrigin-RevId: b137378673f7d66d41bcd46e4fc3a0d9ef254894	2019-10-25 14:29:15 -07:00