Bump protobufjs from 7.1.2 to 7.2.4

Bumps [protobufjs](https://github.com/protobufjs/protobuf.js) from 7.1.2 to 7.2.4. - [Release notes](https://github.com/protobufjs/protobuf.js/releases) - [Changelog](https://github.com/protobufjs/protobuf.js/blob/master/CHANGELOG.md) - [Commits](https://github.com/protobufjs/protobuf.js/compare/protobufjs-v7.1.2...protobufjs-v7.2.4) --- updated-dependencies: - dependency-name: protobufjs dependency-type: direct:development ... Signed-off-by: dependabot[bot] <[email protected]>
2023-07-08 00:36:26 +00:00
757 changed files with 8155 additions and 23078 deletions
@@ -40,16 +40,18 @@ body:
      label: Programming Language and version (e.g. C++, Python, Java)
    validations:
      required: true
-  - type: input
+  - type: textarea
    id: current_model
    attributes:
      label: Describe the actual behavior
      render: shell
    validations:
      required: true
-  - type: input
+  - type: textarea
    id: expected_model
    attributes:
      label: Describe the expected behaviour
      render: shell
    validations:
      required: true
  - type: textarea
@@ -41,16 +41,18 @@ body:
      label: Task name (e.g. Image classification, Gesture recognition etc.)
    validations:
      required: true
-  - type: input
+  - type: textarea
    id: current_model
    attributes:
      label: Describe the actual behavior
      render: shell
    validations:
      required: true
-  - type: input
+  - type: textarea
    id: expected_model
    attributes:
      label: Describe the expected behaviour
      render: shell
    validations:
      required: true
  - type: textarea
@@ -31,16 +31,18 @@ body:
      label: URL that shows the problem
    validations:
      required: false
-  - type: input
+  - type: textarea
    id: current_model
    attributes:
      label: Describe the actual behavior
      render: shell
    validations:
      required: false
-  - type: input
+  - type: textarea
    id: expected_model
    attributes:
      label: Describe the expected behaviour
      render: shell
    validations:
      required: false
  - type: textarea
@@ -28,33 +28,37 @@ body:
        - 'No'
    validations:
      required: false
-  - type: input
+  - type: textarea
    id: behaviour
    attributes:
      label: Describe the feature and the current behaviour/state
      render: shell
    validations:
      required: true
-  - type: input
+  - type: textarea
    id: api_change
    attributes:
      label: Will this change the current API? How?
      render: shell
    validations:
      required: false
-  - type: input
+  - type: textarea
    id: benifit
    attributes:
      label: Who will benefit with this feature?
    validations:
       required: false
-  - type: input
+  - type: textarea
    id: use_case
    attributes:
      label: Please specify the use cases for this feature
      render: shell
    validations:
       required: true
-  - type: input
+  - type: textarea
    id: info_other
    attributes:
      label: Any Other info
      render: shell
    validations:
      required: false
@@ -87,13 +87,14 @@ body:
      placeholder:
    validations:
      required: false
-  - type: input
+  - type: textarea
    id: what-happened
    attributes:
      label: Describe the problem
      description: Provide the exact sequence of commands / steps that you executed before running into the [problem](https://google.github.io/mediapipe/getting_started/getting_started.html)
      placeholder: Tell us what you see!
      value: "A bug happened!"
      render: shell
    validations:
      required: true
  - type: textarea
@@ -80,16 +80,18 @@ body:
      label: Xcode & Tulsi version (if issue is related to building for iOS)
    validations:
      required: false
-  - type: input
+  - type: textarea
    id: current_model
    attributes:
      label: Describe the actual behavior
      render: shell
    validations:
      required: true
-  - type: input
+  - type: textarea
    id: expected_model
    attributes:
      label: Describe the expected behaviour
      render: shell
    validations:
      required: true
  - type: textarea
@@ -48,16 +48,18 @@ body:
      placeholder: e.g. C++, Python, Java
    validations:
      required: false
-  - type: input
+  - type: textarea
    id: current_model
    attributes:
      label: Describe the actual behavior
      render: shell
    validations:
      required: false
-  - type: input
+  - type: textarea
    id: expected_model
    attributes:
      label: Describe the expected behaviour
      render: shell
    validations:
      required: false
  - type: textarea
@@ -73,9 +73,12 @@ http_archive(
 http_archive(
    name = "zlib",
    build_file = "@//third_party:zlib.BUILD",
-    sha256 = "b3a24de97a8fdbc835b9833169501030b8977031bcb54b3b3ac13740f846ab30",
+    sha256 = "c3e5e9fdd5004dcb542feda5ee4f0ff0744628baf8ed2dd5d66f8ca1197cb1a1",
-    strip_prefix = "zlib-1.2.13",
+    strip_prefix = "zlib-1.2.11",
-    url = "http://zlib.net/fossils/zlib-1.2.13.tar.gz",
+    urls = [
        "http://mirror.bazel.build/zlib.net/fossils/zlib-1.2.11.tar.gz",
        "http://zlib.net/fossils/zlib-1.2.11.tar.gz",  # 2017-01-15
    ],
    patches = [
        "@//third_party:zlib.diff",
    ],
@@ -154,19 +157,19 @@ http_archive(
 # 2020-08-21
 http_archive(
    name = "com_github_glog_glog",
-    strip_prefix = "glog-3a0d4d22c5ae0b9a2216988411cfa6bf860cc372",
+    strip_prefix = "glog-0.6.0",
-    sha256 = "170d08f80210b82d95563f4723a15095eff1aad1863000e8eeb569c96a98fefb",
+    sha256 = "8a83bf982f37bb70825df71a9709fa90ea9f4447fb3c099e1d720a439d88bad6",
    urls = [
-        "https://github.com/google/glog/archive/3a0d4d22c5ae0b9a2216988411cfa6bf860cc372.zip",
+        "https://github.com/google/glog/archive/v0.6.0.tar.gz",
    ],
 )
 http_archive(
    name = "com_github_glog_glog_no_gflags",
-    strip_prefix = "glog-3a0d4d22c5ae0b9a2216988411cfa6bf860cc372",
+    strip_prefix = "glog-0.6.0",
-    sha256 = "170d08f80210b82d95563f4723a15095eff1aad1863000e8eeb569c96a98fefb",
+    sha256 = "8a83bf982f37bb70825df71a9709fa90ea9f4447fb3c099e1d720a439d88bad6",
    build_file = "@//third_party:glog_no_gflags.BUILD",
    urls = [
-        "https://github.com/google/glog/archive/3a0d4d22c5ae0b9a2216988411cfa6bf860cc372.zip",
+        "https://github.com/google/glog/archive/v0.6.0.tar.gz",
    ],
    patches = [
        "@//third_party:com_github_glog_glog.diff",
@@ -482,10 +485,10 @@ http_archive(
 )
 # TensorFlow repo should always go after the other external dependencies.
-# TF on 2023-07-26.
+# TF on 2023-06-13.
-_TENSORFLOW_GIT_COMMIT = "e92261fd4cec0b726692081c4d2966b75abf31dd"
+_TENSORFLOW_GIT_COMMIT = "491681a5620e41bf079a582ac39c585cc86878b9"
 # curl -L https://github.com/tensorflow/tensorflow/archive/<TENSORFLOW_GIT_COMMIT>.tar.gz | shasum -a 256
-_TENSORFLOW_SHA256 = "478a229bd4ec70a5b568ac23b5ea013d9fca46a47d6c43e30365a0412b9febf4"
+_TENSORFLOW_SHA256 = "9f76389af7a2835e68413322c1eaabfadc912f02a76d71dc16be507f9ca3d3ac"
 http_archive(
    name = "org_tensorflow",
    urls = [
@@ -493,7 +496,6 @@ http_archive(
    ],
    patches = [
        "@//third_party:org_tensorflow_compatibility_fixes.diff",
        "@//third_party:org_tensorflow_system_python.diff",
        # Diff is generated with a script, don't update it manually.
        "@//third_party:org_tensorflow_custom_ops.diff",
    ],
@@ -50,7 +50,7 @@ as the primary developer documentation site for MediaPipe as of April 3, 2023.*
 3.  The [`hello world`] example uses a simple MediaPipe graph in the
    `PrintHelloWorld()` function, defined in a [`CalculatorGraphConfig`] proto.
-    ```c++
+    ```C++
    absl::Status PrintHelloWorld() {
      // Configures a simple graph, which concatenates 2 PassThroughCalculators.
      CalculatorGraphConfig config = ParseTextProtoOrDie<CalculatorGraphConfig>(R"(
@@ -126,7 +126,7 @@ as the primary developer documentation site for MediaPipe as of April 3, 2023.*
    ```c++
    mediapipe::Packet packet;
    while (poller.Next(&packet)) {
-      ABSL_LOG(INFO) << packet.Get<string>();
+      LOG(INFO) << packet.Get<string>();
    }
    ```
@@ -138,7 +138,7 @@ Create a `BUILD` file in the `$APPLICATION_PATH` and add the following build
 rules:
 ```
-MIN_IOS_VERSION = "12.0"
+MIN_IOS_VERSION = "11.0"
 load(
    "@build_bazel_rules_apple//apple:ios.bzl",
@@ -14,155 +14,81 @@
 licenses(["notice"])  # Apache 2.0
-load("@mediapipe//mediapipe:platforms.bzl", "config_setting_and_platform")
+# Note: yes, these need to use "//external:android/crosstool", not
 # @androidndk//:default_crosstool.
 # Generic Android
 config_setting(
    name = "android",
-    constraint_values = [
+    values = {"crosstool_top": "//external:android/crosstool"},
        "@platforms//os:android",
    ],
    visibility = ["//visibility:public"],
 )
 # Android x86 32-bit.
 config_setting_and_platform(
    name = "android_x86",
    constraint_values = [
        "@platforms//os:android",
        "@platforms//cpu:x86_32",
    ],
    visibility = ["//visibility:public"],
 )
 # Android x86 64-bit.
 config_setting_and_platform(
    name = "android_x86_64",
    constraint_values = [
        "@platforms//os:android",
        "@platforms//cpu:x86_64",
    ],
    visibility = ["//visibility:public"],
 )
 # Android ARMv7.
 config_setting_and_platform(
    name = "android_arm",
    constraint_values = [
        "@platforms//os:android",
        "@platforms//cpu:armv7",
    ],
    visibility = ["//visibility:public"],
 )
 # Android ARM64.
 config_setting_and_platform(
    name = "android_arm64",
    constraint_values = [
        "@platforms//os:android",
        "@platforms//cpu:arm64",
    ],
    visibility = ["//visibility:public"],
 )
 # Generic MacOS.
 config_setting(
    name = "android_x86",
    values = {
        "crosstool_top": "//external:android/crosstool",
        "cpu": "x86",
    },
    visibility = ["//visibility:public"],
 )
 config_setting(
    name = "android_x86_64",
    values = {
        "crosstool_top": "//external:android/crosstool",
        "cpu": "x86_64",
    },
    visibility = ["//visibility:public"],
 )
 config_setting(
    name = "android_armeabi",
    values = {
        "crosstool_top": "//external:android/crosstool",
        "cpu": "armeabi",
    },
    visibility = ["//visibility:public"],
 )
 config_setting(
    name = "android_arm",
    values = {
        "crosstool_top": "//external:android/crosstool",
        "cpu": "armeabi-v7a",
    },
    visibility = ["//visibility:public"],
 )
 config_setting(
    name = "android_arm64",
    values = {
        "crosstool_top": "//external:android/crosstool",
        "cpu": "arm64-v8a",
    },
    visibility = ["//visibility:public"],
 )
 # Note: this cannot just match "apple_platform_type": "macos" because that option
 # defaults to "macos" even when building on Linux!
 alias(
    name = "macos",
-    constraint_values = [
+    actual = select({
-        "@platforms//os:macos",
+        ":macos_i386": ":macos_i386",
-    ],
+        ":macos_x86_64": ":macos_x86_64",
        ":macos_arm64": ":macos_arm64",
        "//conditions:default": ":macos_i386",  # Arbitrarily chosen from above.
    }),
    visibility = ["//visibility:public"],
 )
-# MacOS x86 64-bit.
+# Note: this also matches on crosstool_top so that it does not produce ambiguous
-config_setting_and_platform(
+# selectors when used together with "android".
    name = "macos_x86_64",
    constraint_values = [
        "@platforms//os:macos",
        "@platforms//cpu:x86_64",
    ],
    visibility = ["//visibility:public"],
 )
 # MacOS ARM64.
 config_setting_and_platform(
    name = "macos_arm64",
    constraint_values = [
        "@platforms//os:macos",
        "@platforms//cpu:arm64",
    ],
    visibility = ["//visibility:public"],
 )
 # Generic iOS.
 config_setting(
    name = "ios",
-    constraint_values = [
+    values = {
-        "@platforms//os:ios",
+        "crosstool_top": "@bazel_tools//tools/cpp:toolchain",
-    ],
+        "apple_platform_type": "ios",
-    visibility = ["//visibility:public"],
+    },
 )
 # iOS device ARM32.
 config_setting_and_platform(
    name = "ios_armv7",
    constraint_values = [
        "@platforms//os:ios",
        "@platforms//cpu:arm",
    ],
    visibility = ["//visibility:public"],
 )
 # iOS device ARM64.
 config_setting_and_platform(
    name = "ios_arm64",
    constraint_values = [
        "@platforms//os:ios",
        "@platforms//cpu:arm64",
    ],
    visibility = ["//visibility:public"],
 )
 # iOS device ARM64E.
 config_setting_and_platform(
    name = "ios_arm64e",
    constraint_values = [
        "@platforms//os:ios",
        "@platforms//cpu:arm64e",
    ],
    visibility = ["//visibility:public"],
 )
 # iOS simulator x86 32-bit.
 config_setting_and_platform(
    name = "ios_i386",
    constraint_values = [
        "@platforms//os:ios",
        "@platforms//cpu:x86_32",
        "@build_bazel_apple_support//constraints:simulator",
    ],
    visibility = ["//visibility:public"],
 )
 # iOS simulator x86 64-bit.
 config_setting_and_platform(
    name = "ios_x86_64",
    constraint_values = [
        "@platforms//os:ios",
        "@platforms//cpu:x86_64",
        "@build_bazel_apple_support//constraints:simulator",
    ],
    visibility = ["//visibility:public"],
 )
 # iOS simulator ARM64.
 config_setting_and_platform(
    name = "ios_sim_arm64",
    constraint_values = [
        "@platforms//os:ios",
        "@platforms//cpu:arm64",
        "@build_bazel_apple_support//constraints:simulator",
    ],
    visibility = ["//visibility:public"],
 )
@@ -176,26 +102,54 @@ alias(
    visibility = ["//visibility:public"],
 )
-# Windows 64-bit.
+config_setting(
-config_setting_and_platform(
+    name = "macos_i386",
-    name = "windows",
+    values = {
-    constraint_values = [
+        "apple_platform_type": "macos",
-        "@platforms//os:windows",
+        "cpu": "darwin",
-        "@platforms//cpu:x86_64",
+    },
    ],
    visibility = ["//visibility:public"],
 )
-# Linux 64-bit.
+config_setting(
-config_setting_and_platform(
+    name = "macos_x86_64",
-    name = "linux",
+    values = {
-    constraint_values = [
+        "apple_platform_type": "macos",
-        "@platforms//os:linux",
+        "cpu": "darwin_x86_64",
-        "@platforms//cpu:x86_64",
+    },
    ],
    visibility = ["//visibility:public"],
 )
 config_setting(
    name = "macos_arm64",
    values = {
        "apple_platform_type": "macos",
        "cpu": "darwin_arm64",
    },
    visibility = ["//visibility:public"],
 )
 [
    config_setting(
        name = arch,
        values = {"cpu": arch},
        visibility = ["//visibility:public"],
    )
    for arch in [
        "ios_i386",
        "ios_x86_64",
        "ios_armv7",
        "ios_arm64",
        "ios_arm64e",
        "ios_sim_arm64",
    ]
 ]
 config_setting(
    name = "windows",
    values = {"cpu": "x64_windows"},
 )
 exports_files(
    ["provisioning_profile.mobileprovision"],
    visibility = ["//visibility:public"],
@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # Placeholder: load py_proto_library
 load("//mediapipe/framework/port:build_config.bzl", "mediapipe_cc_proto_library")
 licenses(["notice"])
@@ -146,7 +145,6 @@ cc_library(
        "//mediapipe/framework/port:logging",
        "//mediapipe/framework/port:status",
        "//mediapipe/util:time_series_util",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/strings",
        "@com_google_audio_tools//audio/dsp/mfcc",
        "@eigen_archive//:eigen3",
@@ -165,9 +163,8 @@ cc_library(
        "//mediapipe/framework/formats:matrix",
        "//mediapipe/framework/formats:time_series_header_cc_proto",
        "//mediapipe/framework/port:integral_types",
        "//mediapipe/framework/port:logging",
        "//mediapipe/util:time_series_util",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_absl//absl/strings",
        "@com_google_audio_tools//audio/dsp:resampler",
        "@com_google_audio_tools//audio/dsp:resampler_q",
@@ -188,7 +185,6 @@ cc_library(
        "//mediapipe/framework/port:core_proto",
        "//mediapipe/framework/port:status",
        "//mediapipe/util:time_series_util",
        "@com_google_absl//absl/log:absl_check",
    ],
    alwayslink = 1,
 )
@@ -228,7 +224,6 @@ cc_library(
        "//mediapipe/framework/formats:time_series_header_cc_proto",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/util:time_series_util",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_audio_tools//audio/dsp:window_functions",
        "@eigen_archive//:eigen3",
    ],
@@ -299,7 +294,6 @@ cc_test(
        "//mediapipe/framework/port:integral_types",
        "//mediapipe/framework/port:status",
        "//mediapipe/util:time_series_test_util",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_audio_tools//audio/dsp:number_util",
        "@eigen_archive//:eigen3",
    ],
@@ -333,7 +327,6 @@ cc_binary(
        "//mediapipe/framework:packet",
        "//mediapipe/framework/formats:matrix",
        "//mediapipe/framework/formats:time_series_header_cc_proto",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_benchmark//:benchmark",
    ],
 )
@@ -352,7 +345,6 @@ cc_test(
        "//mediapipe/framework/port:integral_types",
        "//mediapipe/framework/port:status",
        "//mediapipe/util:time_series_test_util",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_audio_tools//audio/dsp:window_functions",
        "@eigen_archive//:eigen3",
    ],
@@ -23,7 +23,6 @@
 #include <vector>
 #include "Eigen/Core"
 #include "absl/log/absl_check.h"
 #include "absl/strings/str_cat.h"
 #include "absl/strings/string_view.h"
 #include "absl/strings/substitute.h"
@@ -139,7 +138,7 @@ absl::Status FramewiseTransformCalculatorBase::Process(CalculatorContext* cc) {
    TransformFrame(input_frame, &output_frame);
    // Copy output from vector<float> to Eigen::Vector.
-    ABSL_CHECK_EQ(output_frame.size(), num_output_channels_);
+    CHECK_EQ(output_frame.size(), num_output_channels_);
    Eigen::Map<const Eigen::MatrixXd> output_frame_map(&output_frame[0],
                                                       output_frame.size(), 1);
    output->col(frame) = output_frame_map.cast<float>();
@@ -16,8 +16,6 @@
 #include "mediapipe/calculators/audio/rational_factor_resample_calculator.h"
 #include "absl/log/absl_check.h"
 #include "absl/log/absl_log.h"
 #include "audio/dsp/resampler_q.h"
 using audio_dsp::Resampler;
@@ -47,9 +45,9 @@ void CopyVectorToChannel(const std::vector<float>& vec, Matrix* matrix,
  if (matrix->cols() == 0) {
    matrix->resize(matrix->rows(), vec.size());
  } else {
-    ABSL_CHECK_EQ(vec.size(), matrix->cols());
+    CHECK_EQ(vec.size(), matrix->cols());
  }
-  ABSL_CHECK_LT(channel, matrix->rows());
+  CHECK_LT(channel, matrix->rows());
  matrix->row(channel) =
      Eigen::Map<const Eigen::ArrayXf>(vec.data(), vec.size());
 }
@@ -79,7 +77,7 @@ absl::Status RationalFactorResampleCalculator::Open(CalculatorContext* cc) {
      r = ResamplerFromOptions(source_sample_rate_, target_sample_rate_,
                               resample_options);
      if (!r) {
-        ABSL_LOG(ERROR) << "Failed to initialize resampler.";
+        LOG(ERROR) << "Failed to initialize resampler.";
        return absl::UnknownError("Failed to initialize resampler.");
      }
    }
@@ -27,6 +27,7 @@
 #include "mediapipe/framework/formats/matrix.h"
 #include "mediapipe/framework/formats/time_series_header.pb.h"
 #include "mediapipe/framework/port/integral_types.h"
 #include "mediapipe/framework/port/logging.h"
 #include "mediapipe/util/time_series_util.h"
 namespace mediapipe {
@@ -22,7 +22,6 @@
 #include <vector>
 #include "Eigen/Core"
 #include "absl/log/absl_log.h"
 #include "audio/dsp/number_util.h"
 #include "mediapipe/calculators/audio/spectrogram_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
@@ -883,11 +882,11 @@ void BM_ProcessDC(benchmark::State& state) {
  const CalculatorRunner::StreamContents& output = runner.Outputs().Index(0);
  const Matrix& output_matrix = output.packets[0].Get<Matrix>();
-  ABSL_LOG(INFO) << "Output matrix=" << output_matrix.rows() << "x"
+  LOG(INFO) << "Output matrix=" << output_matrix.rows() << "x"
-                 << output_matrix.cols();
+            << output_matrix.cols();
-  ABSL_LOG(INFO) << "First values=" << output_matrix(0, 0) << ", "
+  LOG(INFO) << "First values=" << output_matrix(0, 0) << ", "
-                 << output_matrix(1, 0) << ", " << output_matrix(2, 0) << ", "
+            << output_matrix(1, 0) << ", " << output_matrix(2, 0) << ", "
-                 << output_matrix(3, 0);
+            << output_matrix(3, 0);
 }
 BENCHMARK(BM_ProcessDC);
@@ -18,7 +18,6 @@
 #include <memory>
 #include <string>
 #include "absl/log/absl_check.h"
 #include "mediapipe/calculators/audio/stabilized_log_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/formats/matrix.h"
@@ -60,7 +59,7 @@ class StabilizedLogCalculator : public CalculatorBase {
    output_scale_ = stabilized_log_calculator_options.output_scale();
    check_nonnegativity_ =
        stabilized_log_calculator_options.check_nonnegativity();
-    ABSL_CHECK_GE(stabilizer_, 0.0)
+    CHECK_GE(stabilizer_, 0.0)
        << "stabilizer must be >= 0.0, received a value of " << stabilizer_;
    // If the input packets have a header, propagate the header to the output.
@@ -18,7 +18,6 @@
 #include <vector>
 #include "Eigen/Core"
 #include "absl/log/absl_check.h"
 #include "audio/dsp/window_functions.h"
 #include "mediapipe/calculators/audio/time_series_framer_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
@@ -105,7 +104,7 @@ class TimeSeriesFramerCalculator : public CalculatorBase {
    // All numbers are in input samples.
    const int64_t current_output_frame_start = static_cast<int64_t>(
        round(cumulative_output_frames_ * average_frame_step_samples_));
-    ABSL_CHECK_EQ(current_output_frame_start, cumulative_completed_samples_);
+    CHECK_EQ(current_output_frame_start, cumulative_completed_samples_);
    const int64_t next_output_frame_start = static_cast<int64_t>(
        round((cumulative_output_frames_ + 1) * average_frame_step_samples_));
    return next_output_frame_start - current_output_frame_start;
@@ -17,7 +17,6 @@
 #include <random>
 #include <vector>
 #include "absl/log/absl_check.h"
 #include "benchmark/benchmark.h"
 #include "mediapipe/calculators/audio/time_series_framer_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
@@ -71,7 +70,7 @@ void BM_TimeSeriesFramerCalculator(benchmark::State& state) {
    }
    // Initialize graph.
    mediapipe::CalculatorGraph graph;
-    ABSL_CHECK_OK(graph.Initialize(config));
+    CHECK_OK(graph.Initialize(config));
    // Prepare input header.
    auto header = std::make_unique<mediapipe::TimeSeriesHeader>();
    header->set_sample_rate(kSampleRate);
@@ -79,13 +78,13 @@ void BM_TimeSeriesFramerCalculator(benchmark::State& state) {
    state.ResumeTiming();  // Resume benchmark timing.
-    ABSL_CHECK_OK(graph.StartRun({}, {{"input", Adopt(header.release())}}));
+    CHECK_OK(graph.StartRun({}, {{"input", Adopt(header.release())}}));
    for (auto& packet : input_packets) {
-      ABSL_CHECK_OK(graph.AddPacketToInputStream("input", packet));
+      CHECK_OK(graph.AddPacketToInputStream("input", packet));
    }
-    ABSL_CHECK(!graph.HasError());
+    CHECK(!graph.HasError());
-    ABSL_CHECK_OK(graph.CloseAllInputStreams());
+    CHECK_OK(graph.CloseAllInputStreams());
-    ABSL_CHECK_OK(graph.WaitUntilIdle());
+    CHECK_OK(graph.WaitUntilIdle());
  }
 }
 BENCHMARK(BM_TimeSeriesFramerCalculator);
@@ -19,7 +19,6 @@
 #include <vector>
 #include "Eigen/Core"
 #include "absl/log/absl_log.h"
 #include "audio/dsp/window_functions.h"
 #include "mediapipe/calculators/audio/time_series_framer_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
@@ -187,12 +186,11 @@ class TimeSeriesFramerCalculatorTest
    const int num_unique_output_samples =
        round((output().packets.size() - 1) * frame_step_samples) +
        frame_duration_samples;
-    ABSL_LOG(INFO) << "packets.size()=" << output().packets.size()
+    LOG(INFO) << "packets.size()=" << output().packets.size()
-                   << " frame_duration_samples=" << frame_duration_samples
+              << " frame_duration_samples=" << frame_duration_samples
-                   << " frame_step_samples=" << frame_step_samples
+              << " frame_step_samples=" << frame_step_samples
-                   << " num_input_samples_=" << num_input_samples_
+              << " num_input_samples_=" << num_input_samples_
-                   << " num_unique_output_samples="
+              << " num_unique_output_samples=" << num_unique_output_samples;
                   << num_unique_output_samples;
    const int num_padding_samples =
        num_unique_output_samples - num_input_samples_;
    if (options_.pad_final_packet()) {
@@ -381,6 +381,17 @@ cc_library(
    alwayslink = 1,
 )
 cc_library(
    name = "clip_detection_vector_size_calculator",
    srcs = ["clip_detection_vector_size_calculator.cc"],
    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"],
@@ -582,7 +593,6 @@ cc_library(
        "//mediapipe/framework/port:logging",
        "//mediapipe/framework/port:status",
        "//mediapipe/framework/tool:options_util",
        "@com_google_absl//absl/log:absl_check",
    ],
    alwayslink = 1,
 )
@@ -598,7 +608,6 @@ cc_test(
        "//mediapipe/framework/formats:video_stream_header",
        "//mediapipe/framework/port:gtest_main",
        "//mediapipe/framework/port:integral_types",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/strings",
    ],
 )
@@ -631,7 +640,6 @@ cc_library(
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_log",
    ],
    alwayslink = 1,
 )
@@ -779,11 +787,10 @@ cc_library(
        "//mediapipe/framework/deps:random",
        "//mediapipe/framework/formats:video_stream_header",
        "//mediapipe/framework/port:integral_types",
        "//mediapipe/framework/port:logging",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "//mediapipe/framework/tool:options_util",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_absl//absl/strings",
    ],
    alwayslink = 1,
@@ -839,7 +846,6 @@ cc_test(
        "//mediapipe/framework/port:gtest_main",
        "//mediapipe/framework/port:logging",
        "//mediapipe/framework/tool:validate_type",
        "@com_google_absl//absl/log:absl_check",
        "@eigen_archive//:eigen3",
    ],
 )
@@ -1027,7 +1033,6 @@ cc_library(
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/api2:node",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_log",
    ],
    alwayslink = 1,
 )
@@ -1066,7 +1071,6 @@ cc_test(
        "//mediapipe/framework:calculator_runner",
        "//mediapipe/framework/port:gtest_main",
        "//mediapipe/framework/port:parse_text_proto",
        "@com_google_absl//absl/log:absl_log",
    ],
 )
@@ -1113,7 +1117,6 @@ cc_library(
        "//mediapipe/framework/api2:node",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_log",
    ],
    alwayslink = 1,
 )
@@ -1,4 +1,4 @@
-// Copyright 2023 The MediaPipe Authors.
+// 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.
@@ -11,15 +11,16 @@
 // 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.
 //
 // Forked from mediapipe/framework/tool/source.proto.
 // The forked proto must remain identical to the original proto and should be
 // ONLY used by mediapipe open source project.
-syntax = "proto3";
+#include <vector>
-package mediapipe;
+#include "mediapipe/calculators/core/clip_vector_size_calculator.h"
 #include "mediapipe/framework/formats/detection.pb.h"
-message Proto3Options {
+namespace mediapipe {
-  double test_value = 1;
+
-}
+typedef ClipVectorSizeCalculator<::mediapipe::Detection>
    ClipDetectionVectorSizeCalculator;
 REGISTER_CALCULATOR(ClipDetectionVectorSizeCalculator);
 }  // namespace mediapipe
@@ -14,8 +14,6 @@
 #include "mediapipe/calculators/core/end_loop_calculator.h"
 #include <array>
 #include <utility>
 #include <vector>
 #include "mediapipe/framework/formats/classification.pb.h"
@@ -86,8 +84,4 @@ typedef EndLoopCalculator<std::vector<std::array<float, 16>>>
    EndLoopAffineMatrixCalculator;
 REGISTER_CALCULATOR(EndLoopAffineMatrixCalculator);
 typedef EndLoopCalculator<std::vector<std::pair<int, int>>>
    EndLoopImageSizeCalculator;
 REGISTER_CALCULATOR(EndLoopImageSizeCalculator);
 }  // namespace mediapipe
@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "absl/log/absl_log.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/calculator_runner.h"
 #include "mediapipe/framework/port/gtest.h"
@@ -357,18 +356,18 @@ TEST_F(GateCalculatorTest, AllowWithStateChangeNoDataStreams) {
  RunTimeStepWithoutDataStream(kTimestampValue2, "ALLOW", true);
  constexpr int64_t kTimestampValue3 = 45;
  RunTimeStepWithoutDataStream(kTimestampValue3, "ALLOW", false);
-  ABSL_LOG(INFO) << "a";
+  LOG(INFO) << "a";
  const std::vector<Packet>& output =
      runner()->Outputs().Get("STATE_CHANGE", 0).packets;
-  ABSL_LOG(INFO) << "s";
+  LOG(INFO) << "s";
  ASSERT_EQ(2, output.size());
-  ABSL_LOG(INFO) << "d";
+  LOG(INFO) << "d";
  EXPECT_EQ(kTimestampValue1, output[0].Timestamp().Value());
  EXPECT_EQ(kTimestampValue3, output[1].Timestamp().Value());
-  ABSL_LOG(INFO) << "f";
+  LOG(INFO) << "f";
  EXPECT_EQ(true, output[0].Get<bool>());   // Allow.
  EXPECT_EQ(false, output[1].Get<bool>());  // Disallow.
-  ABSL_LOG(INFO) << "g";
+  LOG(INFO) << "g";
 }
 TEST_F(GateCalculatorTest, DisallowWithStateChange) {
@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "absl/log/absl_log.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/port/ret_check.h"
 #include "mediapipe/framework/port/status.h"
@@ -79,7 +78,7 @@ absl::Status ImmediateMuxCalculator::Process(CalculatorContext* cc) {
      if (packet.Timestamp() >= cc->Outputs().Index(0).NextTimestampBound()) {
        cc->Outputs().Index(0).AddPacket(packet);
      } else {
-        ABSL_LOG_FIRST_N(WARNING, 5)
+        LOG_FIRST_N(WARNING, 5)
            << "Dropping a packet with timestamp " << packet.Timestamp();
      }
      if (cc->Outputs().NumEntries() >= 2) {
@@ -16,7 +16,6 @@
 #include <vector>
 #include "Eigen/Core"
 #include "absl/log/absl_check.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/calculator_runner.h"
 #include "mediapipe/framework/formats/matrix.h"
@@ -210,7 +209,7 @@ TEST(MatrixMultiplyCalculatorTest, Multiply) {
  MatrixFromTextProto(kSamplesText, &samples);
  Matrix expected;
  MatrixFromTextProto(kExpectedText, &expected);
-  ABSL_CHECK_EQ(samples.cols(), expected.cols());
+  CHECK_EQ(samples.cols(), expected.cols());
  for (int i = 0; i < samples.cols(); ++i) {
    // Take a column from samples and produce a packet with just that
@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "absl/log/absl_log.h"
 #include "mediapipe/framework/api2/node.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/port/ret_check.h"
@@ -54,7 +53,7 @@ class MergeCalculator : public Node {
  static absl::Status UpdateContract(CalculatorContract* cc) {
    RET_CHECK_GT(kIn(cc).Count(), 0) << "Needs at least one input stream";
    if (kIn(cc).Count() == 1) {
-      ABSL_LOG(WARNING)
+      LOG(WARNING)
          << "MergeCalculator expects multiple input streams to merge but is "
             "receiving only one. Make sure the calculator is configured "
             "correctly or consider removing this calculator to reduce "
@@ -73,8 +72,8 @@ class MergeCalculator : public Node {
      }
    }
-    ABSL_LOG(WARNING) << "Empty input packets at timestamp "
+    LOG(WARNING) << "Empty input packets at timestamp "
-                      << cc->InputTimestamp().Value();
+                 << cc->InputTimestamp().Value();
    return absl::OkStatus();
  }
@@ -16,9 +16,6 @@
 #include <memory>
 #include "absl/log/absl_check.h"
 #include "absl/log/absl_log.h"
 namespace {
 // Reflect an integer against the lower and upper bound of an interval.
 int64_t ReflectBetween(int64_t ts, int64_t ts_min, int64_t ts_max) {
@@ -180,7 +177,7 @@ PacketResamplerCalculator::GetSamplingStrategy(
    const PacketResamplerCalculatorOptions& options) {
  if (options.reproducible_sampling()) {
    if (!options.jitter_with_reflection()) {
-      ABSL_LOG(WARNING)
+      LOG(WARNING)
          << "reproducible_sampling enabled w/ jitter_with_reflection "
             "disabled. "
          << "reproducible_sampling always uses jitter with reflection, "
@@ -203,15 +200,15 @@ PacketResamplerCalculator::GetSamplingStrategy(
 Timestamp PacketResamplerCalculator::PeriodIndexToTimestamp(
    int64_t index) const {
-  ABSL_CHECK_EQ(jitter_, 0.0);
+  CHECK_EQ(jitter_, 0.0);
-  ABSL_CHECK_NE(first_timestamp_, Timestamp::Unset());
+  CHECK_NE(first_timestamp_, Timestamp::Unset());
  return first_timestamp_ + TimestampDiffFromSeconds(index / frame_rate_);
 }
 int64_t PacketResamplerCalculator::TimestampToPeriodIndex(
    Timestamp timestamp) const {
-  ABSL_CHECK_EQ(jitter_, 0.0);
+  CHECK_EQ(jitter_, 0.0);
-  ABSL_CHECK_NE(first_timestamp_, Timestamp::Unset());
+  CHECK_NE(first_timestamp_, Timestamp::Unset());
  return MathUtil::SafeRound<int64_t, double>(
      (timestamp - first_timestamp_).Seconds() * frame_rate_);
 }
@@ -232,15 +229,13 @@ absl::Status LegacyJitterWithReflectionStrategy::Open(CalculatorContext* cc) {
  if (resampler_options.output_header() !=
      PacketResamplerCalculatorOptions::NONE) {
-    ABSL_LOG(WARNING)
+    LOG(WARNING) << "VideoHeader::frame_rate holds the target value and not "
-        << "VideoHeader::frame_rate holds the target value and not "
+                    "the actual value.";
           "the actual value.";
  }
  if (calculator_->flush_last_packet_) {
-    ABSL_LOG(WARNING)
+    LOG(WARNING) << "PacketResamplerCalculatorOptions.flush_last_packet is "
-        << "PacketResamplerCalculatorOptions.flush_last_packet is "
+                    "ignored, because we are adding jitter.";
           "ignored, because we are adding jitter.";
  }
  const auto& seed = cc->InputSidePackets().Tag(kSeedTag).Get<std::string>();
@@ -259,7 +254,7 @@ absl::Status LegacyJitterWithReflectionStrategy::Open(CalculatorContext* cc) {
 }
 absl::Status LegacyJitterWithReflectionStrategy::Close(CalculatorContext* cc) {
  if (!packet_reservoir_->IsEmpty()) {
-    ABSL_LOG(INFO) << "Emitting pack from reservoir.";
+    LOG(INFO) << "Emitting pack from reservoir.";
    calculator_->OutputWithinLimits(cc, packet_reservoir_->GetSample());
  }
  return absl::OkStatus();
@@ -290,7 +285,7 @@ absl::Status LegacyJitterWithReflectionStrategy::Process(
  if (calculator_->frame_time_usec_ <
      (cc->InputTimestamp() - calculator_->last_packet_.Timestamp()).Value()) {
-    ABSL_LOG_FIRST_N(WARNING, 2)
+    LOG_FIRST_N(WARNING, 2)
        << "Adding jitter is not very useful when upsampling.";
  }
@@ -345,8 +340,8 @@ void LegacyJitterWithReflectionStrategy::UpdateNextOutputTimestampWithJitter() {
  next_output_timestamp_ = Timestamp(ReflectBetween(
      next_output_timestamp_.Value(), next_output_timestamp_min_.Value(),
      next_output_timestamp_max_.Value()));
-  ABSL_CHECK_GE(next_output_timestamp_, next_output_timestamp_min_);
+  CHECK_GE(next_output_timestamp_, next_output_timestamp_min_);
-  ABSL_CHECK_LT(next_output_timestamp_, next_output_timestamp_max_);
+  CHECK_LT(next_output_timestamp_, next_output_timestamp_max_);
 }
 absl::Status ReproducibleJitterWithReflectionStrategy::Open(
@@ -357,15 +352,13 @@ absl::Status ReproducibleJitterWithReflectionStrategy::Open(
  if (resampler_options.output_header() !=
      PacketResamplerCalculatorOptions::NONE) {
-    ABSL_LOG(WARNING)
+    LOG(WARNING) << "VideoHeader::frame_rate holds the target value and not "
-        << "VideoHeader::frame_rate holds the target value and not "
+                    "the actual value.";
           "the actual value.";
  }
  if (calculator_->flush_last_packet_) {
-    ABSL_LOG(WARNING)
+    LOG(WARNING) << "PacketResamplerCalculatorOptions.flush_last_packet is "
-        << "PacketResamplerCalculatorOptions.flush_last_packet is "
+                    "ignored, because we are adding jitter.";
           "ignored, because we are adding jitter.";
  }
  const auto& seed = cc->InputSidePackets().Tag(kSeedTag).Get<std::string>();
@@ -418,7 +411,7 @@ absl::Status ReproducibleJitterWithReflectionStrategy::Process(
    // Note, if the stream is upsampling, this could lead to the same packet
    // being emitted twice.  Upsampling and jitter doesn't make much sense
    // but does technically work.
-    ABSL_LOG_FIRST_N(WARNING, 2)
+    LOG_FIRST_N(WARNING, 2)
        << "Adding jitter is not very useful when upsampling.";
  }
@@ -506,15 +499,13 @@ absl::Status JitterWithoutReflectionStrategy::Open(CalculatorContext* cc) {
  if (resampler_options.output_header() !=
      PacketResamplerCalculatorOptions::NONE) {
-    ABSL_LOG(WARNING)
+    LOG(WARNING) << "VideoHeader::frame_rate holds the target value and not "
-        << "VideoHeader::frame_rate holds the target value and not "
+                    "the actual value.";
           "the actual value.";
  }
  if (calculator_->flush_last_packet_) {
-    ABSL_LOG(WARNING)
+    LOG(WARNING) << "PacketResamplerCalculatorOptions.flush_last_packet is "
-        << "PacketResamplerCalculatorOptions.flush_last_packet is "
+                    "ignored, because we are adding jitter.";
           "ignored, because we are adding jitter.";
  }
  const auto& seed = cc->InputSidePackets().Tag(kSeedTag).Get<std::string>();
@@ -564,7 +555,7 @@ absl::Status JitterWithoutReflectionStrategy::Process(CalculatorContext* cc) {
  if (calculator_->frame_time_usec_ <
      (cc->InputTimestamp() - calculator_->last_packet_.Timestamp()).Value()) {
-    ABSL_LOG_FIRST_N(WARNING, 2)
+    LOG_FIRST_N(WARNING, 2)
        << "Adding jitter is not very useful when upsampling.";
  }
@@ -13,6 +13,7 @@
 #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"
@@ -17,7 +17,6 @@
 #include <cmath>  // for ceil
 #include <memory>
 #include "absl/log/absl_check.h"
 #include "mediapipe/calculators/core/packet_thinner_calculator.pb.h"
 #include "mediapipe/framework/calculator_context.h"
 #include "mediapipe/framework/calculator_framework.h"
@@ -161,8 +160,8 @@ absl::Status PacketThinnerCalculator::Open(CalculatorContext* cc) {
  thinner_type_ = options.thinner_type();
  // This check enables us to assume only two thinner types exist in Process()
-  ABSL_CHECK(thinner_type_ == PacketThinnerCalculatorOptions::ASYNC ||
+  CHECK(thinner_type_ == PacketThinnerCalculatorOptions::ASYNC ||
-             thinner_type_ == PacketThinnerCalculatorOptions::SYNC)
+        thinner_type_ == PacketThinnerCalculatorOptions::SYNC)
      << "Unsupported thinner type.";
  if (thinner_type_ == PacketThinnerCalculatorOptions::ASYNC) {
@@ -178,8 +177,7 @@ absl::Status PacketThinnerCalculator::Open(CalculatorContext* cc) {
  } else {
    period_ = TimestampDiff(options.period());
  }
-  ABSL_CHECK_LT(TimestampDiff(0), period_)
+  CHECK_LT(TimestampDiff(0), period_) << "Specified period must be positive.";
      << "Specified period must be positive.";
  if (options.has_start_time()) {
    start_time_ = Timestamp(options.start_time());
@@ -191,7 +189,7 @@ absl::Status PacketThinnerCalculator::Open(CalculatorContext* cc) {
  end_time_ =
      options.has_end_time() ? Timestamp(options.end_time()) : Timestamp::Max();
-  ABSL_CHECK_LT(start_time_, end_time_)
+  CHECK_LT(start_time_, end_time_)
      << "Invalid PacketThinner: start_time must be earlier than end_time";
  sync_output_timestamps_ = options.sync_output_timestamps();
@@ -234,7 +232,7 @@ absl::Status PacketThinnerCalculator::Close(CalculatorContext* cc) {
  // Emit any saved packets before quitting.
  if (!saved_packet_.IsEmpty()) {
    // Only sync thinner should have saved packets.
-    ABSL_CHECK_EQ(PacketThinnerCalculatorOptions::SYNC, thinner_type_);
+    CHECK_EQ(PacketThinnerCalculatorOptions::SYNC, thinner_type_);
    if (sync_output_timestamps_) {
      cc->Outputs().Index(0).AddPacket(
          saved_packet_.At(NearestSyncTimestamp(saved_packet_.Timestamp())));
@@ -271,7 +269,7 @@ absl::Status PacketThinnerCalculator::SyncThinnerProcess(
    const Timestamp saved_sync = NearestSyncTimestamp(saved);
    const Timestamp now = cc->InputTimestamp();
    const Timestamp now_sync = NearestSyncTimestamp(now);
-    ABSL_CHECK_LE(saved_sync, now_sync);
+    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
@@ -297,7 +295,7 @@ absl::Status PacketThinnerCalculator::SyncThinnerProcess(
 }
 Timestamp PacketThinnerCalculator::NearestSyncTimestamp(Timestamp now) const {
-  ABSL_CHECK_NE(start_time_, Timestamp::Unset())
+  CHECK_NE(start_time_, Timestamp::Unset())
      << "Method only valid for sync thinner calculator.";
  // Computation is done using int64 arithmetic.  No easy way to avoid
@@ -305,12 +303,12 @@ Timestamp PacketThinnerCalculator::NearestSyncTimestamp(Timestamp now) const {
  const int64_t now64 = now.Value();
  const int64_t start64 = start_time_.Value();
  const int64_t period64 = period_.Value();
-  ABSL_CHECK_LE(0, period64);
+  CHECK_LE(0, period64);
  // Round now64 to its closest interval (units of period64).
  int64_t sync64 =
      (now64 - start64 + period64 / 2) / period64 * period64 + start64;
-  ABSL_CHECK_LE(abs(now64 - sync64), period64 / 2)
+  CHECK_LE(abs(now64 - sync64), period64 / 2)
      << "start64: " << start64 << "; now64: " << now64
      << "; sync64: " << sync64;
@@ -16,7 +16,6 @@
 #include <string>
 #include <vector>
 #include "absl/log/absl_check.h"
 #include "absl/strings/str_cat.h"
 #include "mediapipe/calculators/core/packet_thinner_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
@@ -71,7 +70,7 @@ class SimpleRunner : public CalculatorRunner {
  }
  double GetFrameRate() const {
-    ABSL_CHECK(!Outputs().Index(0).header.IsEmpty());
+    CHECK(!Outputs().Index(0).header.IsEmpty());
    return Outputs().Index(0).header.Get<VideoHeader>().frame_rate;
  }
 };
@@ -14,7 +14,6 @@
 #include <deque>
 #include "absl/log/absl_log.h"
 #include "mediapipe/calculators/core/sequence_shift_calculator.pb.h"
 #include "mediapipe/framework/api2/node.h"
 #include "mediapipe/framework/calculator_framework.h"
@@ -102,7 +101,7 @@ void SequenceShiftCalculator::ProcessPositiveOffset(CalculatorContext* cc) {
    kOut(cc).Send(packet_cache_.front().At(cc->InputTimestamp()));
    packet_cache_.pop_front();
  } else if (emit_empty_packets_before_first_packet_) {
-    ABSL_LOG(FATAL) << "Not supported yet";
+    LOG(FATAL) << "Not supported yet";
  }
  // Store current packet for later output.
  packet_cache_.push_back(kIn(cc).packet());
@@ -97,7 +97,6 @@ cc_library(
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:source_location",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_check",
    ],
    alwayslink = 1,
 )
@@ -126,7 +125,6 @@ cc_library(
        "//mediapipe/framework/port:opencv_imgcodecs",
        "//mediapipe/framework/port:opencv_imgproc",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_check",
    ],
    alwayslink = 1,
 )
@@ -153,11 +151,11 @@ cc_library(
        "//mediapipe/framework/formats:image_format_cc_proto",
        "//mediapipe/framework/formats:image_frame",
        "//mediapipe/framework/formats:image_frame_opencv",
        "//mediapipe/framework/port:logging",
        "//mediapipe/framework/port:opencv_core",
        "//mediapipe/framework/port:opencv_imgproc",
        "//mediapipe/framework/port:status",
        "//mediapipe/framework/port:vector",
        "@com_google_absl//absl/log:absl_log",
    ] + select({
        "//mediapipe/gpu:disable_gpu": [],
        "//conditions:default": [
@@ -204,7 +202,6 @@ cc_library(
        "//mediapipe/framework/port:opencv_imgproc",
        "//mediapipe/framework/port:status",
        "//mediapipe/framework/port:vector",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/strings",
    ] + select({
        "//mediapipe/gpu:disable_gpu": [],
@@ -264,12 +261,9 @@ cc_library(
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "//mediapipe/gpu:scale_mode_cc_proto",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/strings",
    ] + select({
        "//mediapipe/gpu:disable_gpu": [],
        "//conditions:default": [
            "//mediapipe/gpu:gl_base_hdr",
            "//mediapipe/gpu:gl_calculator_helper",
            "//mediapipe/gpu:gl_quad_renderer",
            "//mediapipe/gpu:gl_simple_shaders",
@@ -279,36 +273,6 @@ cc_library(
    alwayslink = 1,
 )
 cc_test(
    name = "image_transformation_calculator_test",
    srcs = ["image_transformation_calculator_test.cc"],
    data = ["//mediapipe/calculators/image/testdata:test_images"],
    tags = [
        "desktop_only_test",
    ],
    deps = [
        ":image_transformation_calculator",
        "//mediapipe/framework:calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:calculator_runner",
        "//mediapipe/framework/deps:file_path",
        "//mediapipe/framework/formats:image_format_cc_proto",
        "//mediapipe/framework/formats:image_frame",
        "//mediapipe/framework/formats:image_frame_opencv",
        "//mediapipe/framework/port:gtest",
        "//mediapipe/framework/port:opencv_imgcodecs",
        "//mediapipe/framework/port:opencv_imgproc",
        "//mediapipe/framework/port:parse_text_proto",
        "//mediapipe/gpu:gpu_buffer_to_image_frame_calculator",
        "//mediapipe/gpu:image_frame_to_gpu_buffer_calculator",
        "//third_party:opencv",
        "@com_google_absl//absl/container:flat_hash_set",
        "@com_google_absl//absl/flags:flag",
        "@com_google_absl//absl/strings",
        "@com_google_googletest//:gtest_main",
    ],
 )
 cc_library(
    name = "image_cropping_calculator",
    srcs = ["image_cropping_calculator.cc"],
@@ -336,7 +300,6 @@ cc_library(
        "//mediapipe/framework/port:opencv_imgproc",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_log",
    ] + select({
        "//mediapipe/gpu:disable_gpu": [],
        "//conditions:default": [
@@ -433,7 +396,6 @@ cc_library(
        "//mediapipe/framework/port:logging",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/strings",
    ],
 )
@@ -458,8 +420,6 @@ cc_library(
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "//mediapipe/util:image_frame_util",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_absl//absl/strings",
        "@libyuv",
    ],
@@ -665,9 +625,9 @@ cc_library(
        "//mediapipe/framework/formats:image",
        "//mediapipe/framework/formats:image_format_cc_proto",
        "//mediapipe/framework/formats:image_frame",
        "//mediapipe/framework/port:logging",
        "//mediapipe/framework/port:status",
        "//mediapipe/framework/port:vector",
        "@com_google_absl//absl/log:absl_log",
    ] + select({
        "//mediapipe/gpu:disable_gpu": [],
        "//conditions:default": [
@@ -705,7 +665,6 @@ cc_test(
        "//mediapipe/framework/port:opencv_imgcodecs",
        "//mediapipe/framework/port:opencv_imgproc",
        "//mediapipe/framework/port:parse_text_proto",
        "@com_google_absl//absl/log:absl_log",
    ],
 )
@@ -728,7 +687,6 @@ cc_library(
        "//mediapipe/gpu:gpu_buffer",
        "//mediapipe/gpu:gpu_origin_cc_proto",
        "//mediapipe/gpu:shader_util",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_absl//absl/memory",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/status:statusor",
@@ -20,7 +20,6 @@
 #include "Eigen/Core"
 #include "Eigen/Geometry"
 #include "Eigen/LU"
 #include "absl/log/absl_log.h"
 #include "absl/memory/memory.h"
 #include "absl/status/status.h"
 #include "absl/status/statusor.h"
@@ -54,10 +53,6 @@ bool IsMatrixVerticalFlipNeeded(GpuOrigin::Mode gpu_origin) {
 #endif  //  __APPLE__
    case GpuOrigin::TOP_LEFT:
      return false;
    default:
      ABSL_LOG(ERROR) << "Incorrect GpuOrigin: "
                      << static_cast<int>(gpu_origin);
      return true;
  }
 }
@@ -389,8 +384,6 @@ class GlTextureWarpAffineRunner
    glActiveTexture(GL_TEXTURE0);
    glBindTexture(GL_TEXTURE_2D, 0);
    glFlush();
    return absl::OkStatus();
  }
@@ -15,7 +15,6 @@
 #include <memory>
 #include <string>
 #include "absl/log/absl_check.h"
 #include "absl/strings/str_replace.h"
 #include "mediapipe/calculators/image/bilateral_filter_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
@@ -113,7 +112,7 @@ class BilateralFilterCalculator : public CalculatorBase {
 REGISTER_CALCULATOR(BilateralFilterCalculator);
 absl::Status BilateralFilterCalculator::GetContract(CalculatorContract* cc) {
-  RET_CHECK_GE(cc->Inputs().NumEntries(), 1);
+  CHECK_GE(cc->Inputs().NumEntries(), 1);
  if (cc->Inputs().HasTag(kInputFrameTag) &&
      cc->Inputs().HasTag(kInputFrameTagGpu)) {
@@ -184,8 +183,8 @@ absl::Status BilateralFilterCalculator::Open(CalculatorContext* cc) {
  sigma_color_ = options_.sigma_color();
  sigma_space_ = options_.sigma_space();
-  ABSL_CHECK_GE(sigma_color_, 0.0);
+  CHECK_GE(sigma_color_, 0.0);
-  ABSL_CHECK_GE(sigma_space_, 0.0);
+  CHECK_GE(sigma_space_, 0.0);
  if (!use_gpu_) sigma_color_ *= 255.0;
  if (use_gpu_) {
@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "absl/log/absl_check.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/formats/image_frame.h"
 #include "mediapipe/framework/formats/image_frame_opencv.h"
@@ -26,8 +25,8 @@
 namespace mediapipe {
 namespace {
 void SetColorChannel(int channel, uint8 value, cv::Mat* mat) {
-  ABSL_CHECK(mat->depth() == CV_8U);
+  CHECK(mat->depth() == CV_8U);
-  ABSL_CHECK(channel < mat->channels());
+  CHECK(channel < mat->channels());
  const int step = mat->channels();
  for (int r = 0; r < mat->rows; ++r) {
    uint8* row_ptr = mat->ptr<uint8>(r);
@@ -16,7 +16,6 @@
 #include <cmath>
 #include "absl/log/absl_log.h"
 #include "mediapipe/framework/formats/image_frame.h"
 #include "mediapipe/framework/formats/image_frame_opencv.h"
 #include "mediapipe/framework/formats/rect.pb.h"
@@ -203,9 +202,8 @@ absl::Status ImageCroppingCalculator::ValidateBorderModeForGPU(
  switch (options.border_mode()) {
    case mediapipe::ImageCroppingCalculatorOptions::BORDER_ZERO:
-      ABSL_LOG(WARNING)
+      LOG(WARNING) << "BORDER_ZERO mode is not supported by GPU "
-          << "BORDER_ZERO mode is not supported by GPU "
+                   << "implementation and will fall back into BORDER_REPLICATE";
          << "implementation and will fall back into BORDER_REPLICATE";
      break;
    case mediapipe::ImageCroppingCalculatorOptions::BORDER_REPLICATE:
      break;
@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "absl/status/status.h"
 #include "mediapipe/calculators/image/image_transformation_calculator.pb.h"
 #include "mediapipe/calculators/image/rotation_mode.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
@@ -28,7 +27,6 @@
 #include "mediapipe/gpu/scale_mode.pb.h"
 #if !MEDIAPIPE_DISABLE_GPU
 #include "mediapipe/gpu/gl_base.h"
 #include "mediapipe/gpu/gl_calculator_helper.h"
 #include "mediapipe/gpu/gl_quad_renderer.h"
 #include "mediapipe/gpu/gl_simple_shaders.h"
@@ -62,42 +60,42 @@ constexpr char kVideoPrestreamTag[] = "VIDEO_PRESTREAM";
 int RotationModeToDegrees(mediapipe::RotationMode_Mode rotation) {
  switch (rotation) {
-    case mediapipe::RotationMode::UNKNOWN:
+    case mediapipe::RotationMode_Mode_UNKNOWN:
-    case mediapipe::RotationMode::ROTATION_0:
+    case mediapipe::RotationMode_Mode_ROTATION_0:
      return 0;
-    case mediapipe::RotationMode::ROTATION_90:
+    case mediapipe::RotationMode_Mode_ROTATION_90:
      return 90;
-    case mediapipe::RotationMode::ROTATION_180:
+    case mediapipe::RotationMode_Mode_ROTATION_180:
      return 180;
-    case mediapipe::RotationMode::ROTATION_270:
+    case mediapipe::RotationMode_Mode_ROTATION_270:
      return 270;
  }
 }
 mediapipe::RotationMode_Mode DegreesToRotationMode(int degrees) {
  switch (degrees) {
    case 0:
-      return mediapipe::RotationMode::ROTATION_0;
+      return mediapipe::RotationMode_Mode_ROTATION_0;
    case 90:
-      return mediapipe::RotationMode::ROTATION_90;
+      return mediapipe::RotationMode_Mode_ROTATION_90;
    case 180:
-      return mediapipe::RotationMode::ROTATION_180;
+      return mediapipe::RotationMode_Mode_ROTATION_180;
    case 270:
-      return mediapipe::RotationMode::ROTATION_270;
+      return mediapipe::RotationMode_Mode_ROTATION_270;
    default:
-      return mediapipe::RotationMode::UNKNOWN;
+      return mediapipe::RotationMode_Mode_UNKNOWN;
  }
 }
 mediapipe::ScaleMode_Mode ParseScaleMode(
    mediapipe::ScaleMode_Mode scale_mode,
    mediapipe::ScaleMode_Mode default_mode) {
  switch (scale_mode) {
-    case mediapipe::ScaleMode::DEFAULT:
+    case mediapipe::ScaleMode_Mode_DEFAULT:
      return default_mode;
-    case mediapipe::ScaleMode::STRETCH:
+    case mediapipe::ScaleMode_Mode_STRETCH:
      return scale_mode;
-    case mediapipe::ScaleMode::FIT:
+    case mediapipe::ScaleMode_Mode_FIT:
      return scale_mode;
-    case mediapipe::ScaleMode::FILL_AND_CROP:
+    case mediapipe::ScaleMode_Mode_FILL_AND_CROP:
      return scale_mode;
    default:
      return default_mode;
@@ -210,8 +208,6 @@ class ImageTransformationCalculator : public CalculatorBase {
  bool use_gpu_ = false;
  cv::Scalar padding_color_;
  ImageTransformationCalculatorOptions::InterpolationMode interpolation_mode_;
 #if !MEDIAPIPE_DISABLE_GPU
  GlCalculatorHelper gpu_helper_;
  std::unique_ptr<QuadRenderer> rgb_renderer_;
@@ -347,11 +343,6 @@ absl::Status ImageTransformationCalculator::Open(CalculatorContext* cc) {
                              options_.padding_color().green(),
                              options_.padding_color().blue());
  interpolation_mode_ = options_.interpolation_mode();
  if (options_.interpolation_mode() ==
      ImageTransformationCalculatorOptions::DEFAULT) {
    interpolation_mode_ = ImageTransformationCalculatorOptions::LINEAR;
  }
  if (use_gpu_) {
 #if !MEDIAPIPE_DISABLE_GPU
    // Let the helper access the GL context information.
@@ -466,48 +457,26 @@ absl::Status ImageTransformationCalculator::RenderCpu(CalculatorContext* cc) {
  ComputeOutputDimensions(input_width, input_height, &output_width,
                          &output_height);
  int opencv_interpolation_mode = cv::INTER_LINEAR;
  if (output_width_ > 0 && output_height_ > 0) {
    cv::Mat scaled_mat;
-    if (scale_mode_ == mediapipe::ScaleMode::STRETCH) {
+    if (scale_mode_ == mediapipe::ScaleMode_Mode_STRETCH) {
-      if (interpolation_mode_ == ImageTransformationCalculatorOptions::LINEAR) {
+      int scale_flag =
-        // Use INTER_AREA for downscaling if interpolation mode is set to
+          input_mat.cols > output_width_ && input_mat.rows > output_height_
-        // LINEAR.
+              ? cv::INTER_AREA
-        if (input_mat.cols > output_width_ && input_mat.rows > output_height_) {
+              : cv::INTER_LINEAR;
          opencv_interpolation_mode = cv::INTER_AREA;
        } else {
          opencv_interpolation_mode = cv::INTER_LINEAR;
        }
      } else {
        opencv_interpolation_mode = cv::INTER_NEAREST;
      }
      cv::resize(input_mat, scaled_mat, cv::Size(output_width_, output_height_),
-                 0, 0, opencv_interpolation_mode);
+                 0, 0, scale_flag);
    } else {
      const float scale =
          std::min(static_cast<float>(output_width_) / input_width,
                   static_cast<float>(output_height_) / input_height);
      const int target_width = std::round(input_width * scale);
      const int target_height = std::round(input_height * scale);
-
+      int scale_flag = scale < 1.0f ? cv::INTER_AREA : cv::INTER_LINEAR;
-      if (interpolation_mode_ == ImageTransformationCalculatorOptions::LINEAR) {
+      if (scale_mode_ == mediapipe::ScaleMode_Mode_FIT) {
        // Use INTER_AREA for downscaling if interpolation mode is set to
        // LINEAR.
        if (scale < 1.0f) {
          opencv_interpolation_mode = cv::INTER_AREA;
        } else {
          opencv_interpolation_mode = cv::INTER_LINEAR;
        }
      } else {
        opencv_interpolation_mode = cv::INTER_NEAREST;
      }
      if (scale_mode_ == mediapipe::ScaleMode::FIT) {
        cv::Mat intermediate_mat;
        cv::resize(input_mat, intermediate_mat,
-                   cv::Size(target_width, target_height), 0, 0,
+                   cv::Size(target_width, target_height), 0, 0, scale_flag);
                   opencv_interpolation_mode);
        const int top = (output_height_ - target_height) / 2;
        const int bottom = output_height_ - target_height - top;
        const int left = (output_width_ - target_width) / 2;
@@ -519,7 +488,7 @@ absl::Status ImageTransformationCalculator::RenderCpu(CalculatorContext* cc) {
                           padding_color_);
      } else {
        cv::resize(input_mat, scaled_mat, cv::Size(target_width, target_height),
-                   0, 0, opencv_interpolation_mode);
+                   0, 0, scale_flag);
        output_width = target_width;
        output_height = target_height;
      }
@@ -545,17 +514,17 @@ absl::Status ImageTransformationCalculator::RenderCpu(CalculatorContext* cc) {
    cv::warpAffine(input_mat, rotated_mat, rotation_mat, rotated_size);
  } else {
    switch (rotation_) {
-      case mediapipe::RotationMode::UNKNOWN:
+      case mediapipe::RotationMode_Mode_UNKNOWN:
-      case mediapipe::RotationMode::ROTATION_0:
+      case mediapipe::RotationMode_Mode_ROTATION_0:
        rotated_mat = input_mat;
        break;
-      case mediapipe::RotationMode::ROTATION_90:
+      case mediapipe::RotationMode_Mode_ROTATION_90:
        cv::rotate(input_mat, rotated_mat, cv::ROTATE_90_COUNTERCLOCKWISE);
        break;
-      case mediapipe::RotationMode::ROTATION_180:
+      case mediapipe::RotationMode_Mode_ROTATION_180:
        cv::rotate(input_mat, rotated_mat, cv::ROTATE_180);
        break;
-      case mediapipe::RotationMode::ROTATION_270:
+      case mediapipe::RotationMode_Mode_ROTATION_270:
        cv::rotate(input_mat, rotated_mat, cv::ROTATE_90_CLOCKWISE);
        break;
    }
@@ -592,7 +561,7 @@ absl::Status ImageTransformationCalculator::RenderGpu(CalculatorContext* cc) {
  ComputeOutputDimensions(input_width, input_height, &output_width,
                          &output_height);
-  if (scale_mode_ == mediapipe::ScaleMode::FILL_AND_CROP) {
+  if (scale_mode_ == mediapipe::ScaleMode_Mode_FILL_AND_CROP) {
    const float scale =
        std::min(static_cast<float>(output_width_) / input_width,
                 static_cast<float>(output_height_) / input_height);
@@ -659,12 +628,6 @@ absl::Status ImageTransformationCalculator::RenderGpu(CalculatorContext* cc) {
  glActiveTexture(GL_TEXTURE1);
  glBindTexture(src1.target(), src1.name());
  if (interpolation_mode_ == ImageTransformationCalculatorOptions::NEAREST) {
    // TODO: revert texture params.
    glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_NEAREST);
    glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST);
  }
  MP_RETURN_IF_ERROR(renderer->GlRender(
      src1.width(), src1.height(), dst.width(), dst.height(), scale_mode,
      rotation, flip_horizontally_, flip_vertically_,
@@ -689,8 +652,8 @@ void ImageTransformationCalculator::ComputeOutputDimensions(
  if (output_width_ > 0 && output_height_ > 0) {
    *output_width = output_width_;
    *output_height = output_height_;
-  } else if (rotation_ == mediapipe::RotationMode::ROTATION_90 ||
+  } else if (rotation_ == mediapipe::RotationMode_Mode_ROTATION_90 ||
-             rotation_ == mediapipe::RotationMode::ROTATION_270) {
+             rotation_ == mediapipe::RotationMode_Mode_ROTATION_270) {
    *output_width = input_height;
    *output_height = input_width;
  } else {
@@ -703,9 +666,9 @@ void ImageTransformationCalculator::ComputeOutputLetterboxPadding(
    int input_width, int input_height, int output_width, int output_height,
    std::array<float, 4>* padding) {
  padding->fill(0.f);
-  if (scale_mode_ == mediapipe::ScaleMode::FIT) {
+  if (scale_mode_ == mediapipe::ScaleMode_Mode_FIT) {
-    if (rotation_ == mediapipe::RotationMode::ROTATION_90 ||
+    if (rotation_ == mediapipe::RotationMode_Mode_ROTATION_90 ||
-        rotation_ == mediapipe::RotationMode::ROTATION_270) {
+        rotation_ == mediapipe::RotationMode_Mode_ROTATION_270) {
      std::swap(input_width, input_height);
    }
    const float input_aspect_ratio =
@@ -54,15 +54,4 @@ message ImageTransformationCalculatorOptions {
  // The color for the padding. This option is only used when the scale mode is
  // FIT. Default is black. This is for CPU only.
  optional Color padding_color = 8;
  // Interpolation method to use. Note that on CPU when LINEAR is specified,
  // INTER_LINEAR is used for upscaling and INTER_AREA is used for downscaling.
  enum InterpolationMode {
    DEFAULT = 0;
    LINEAR = 1;
    NEAREST = 2;
  }
  // Mode DEFAULT will use LINEAR interpolation.
  optional InterpolationMode interpolation_mode = 9;
 }
@@ -1,315 +0,0 @@
 #include <string>
 #include <utility>
 #include <vector>
 #include "absl/container/flat_hash_set.h"
 #include "absl/flags/flag.h"
 #include "absl/strings/substitute.h"
 #include "mediapipe/framework/calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/calculator_runner.h"
 #include "mediapipe/framework/deps/file_path.h"
 #include "mediapipe/framework/formats/image_format.pb.h"
 #include "mediapipe/framework/formats/image_frame.h"
 #include "mediapipe/framework/formats/image_frame_opencv.h"
 #include "mediapipe/framework/port/gtest.h"
 #include "mediapipe/framework/port/opencv_imgcodecs_inc.h"
 #include "mediapipe/framework/port/opencv_imgproc_inc.h"
 #include "mediapipe/framework/port/parse_text_proto.h"
 #include "testing/base/public/gmock.h"
 #include "testing/base/public/googletest.h"
 #include "third_party/OpenCV/core.hpp"  // IWYU pragma: keep
 #include "third_party/OpenCV/core/mat.hpp"
 namespace mediapipe {
 namespace {
 absl::flat_hash_set<int> computeUniqueValues(const cv::Mat& mat) {
  // Compute the unique values in cv::Mat
  absl::flat_hash_set<int> unique_values;
  for (int i = 0; i < mat.rows; i++) {
    for (int j = 0; j < mat.cols; j++) {
      unique_values.insert(mat.at<unsigned char>(i, j));
    }
  }
  return unique_values;
 }
 TEST(ImageTransformationCalculatorTest, NearestNeighborResizing) {
  cv::Mat input_mat;
  cv::cvtColor(cv::imread(file::JoinPath("./",
                                         "/mediapipe/calculators/"
                                         "image/testdata/binary_mask.png")),
               input_mat, cv::COLOR_BGR2GRAY);
  Packet input_image_packet = MakePacket<ImageFrame>(
      ImageFormat::GRAY8, input_mat.size().width, input_mat.size().height);
  input_mat.copyTo(formats::MatView(&(input_image_packet.Get<ImageFrame>())));
  std::vector<std::pair<int, int>> output_dims{
      {256, 333}, {512, 512}, {1024, 1024}};
  for (auto& output_dim : output_dims) {
    Packet input_output_dim_packet =
        MakePacket<std::pair<int, int>>(output_dim);
    std::vector<std::string> scale_modes{"FIT", "STRETCH"};
    for (const auto& scale_mode : scale_modes) {
      CalculatorGraphConfig::Node node_config =
          ParseTextProtoOrDie<CalculatorGraphConfig::Node>(
              absl::Substitute(R"(
          calculator: "ImageTransformationCalculator"
          input_stream: "IMAGE:input_image"
          input_stream: "OUTPUT_DIMENSIONS:image_size"
          output_stream: "IMAGE:output_image"
          options: {
            [mediapipe.ImageTransformationCalculatorOptions.ext]: {
              scale_mode: $0
              interpolation_mode: NEAREST
            }
          })",
                               scale_mode));
      CalculatorRunner runner(node_config);
      runner.MutableInputs()->Tag("IMAGE").packets.push_back(
          input_image_packet.At(Timestamp(0)));
      runner.MutableInputs()
          ->Tag("OUTPUT_DIMENSIONS")
          .packets.push_back(input_output_dim_packet.At(Timestamp(0)));
      MP_ASSERT_OK(runner.Run());
      const auto& outputs = runner.Outputs();
      ASSERT_EQ(outputs.NumEntries(), 1);
      const std::vector<Packet>& packets = outputs.Tag("IMAGE").packets;
      ASSERT_EQ(packets.size(), 1);
      const auto& result = packets[0].Get<ImageFrame>();
      ASSERT_EQ(output_dim.first, result.Width());
      ASSERT_EQ(output_dim.second, result.Height());
      auto unique_input_values = computeUniqueValues(input_mat);
      auto unique_output_values =
          computeUniqueValues(formats::MatView(&result));
      EXPECT_THAT(unique_input_values,
                  ::testing::ContainerEq(unique_output_values));
    }
  }
 }
 TEST(ImageTransformationCalculatorTest,
     NearestNeighborResizingWorksForFloatInput) {
  cv::Mat input_mat;
  cv::cvtColor(cv::imread(file::JoinPath("./",
                                         "/mediapipe/calculators/"
                                         "image/testdata/binary_mask.png")),
               input_mat, cv::COLOR_BGR2GRAY);
  Packet input_image_packet = MakePacket<ImageFrame>(
      ImageFormat::VEC32F1, input_mat.size().width, input_mat.size().height);
  cv::Mat packet_mat_view =
      formats::MatView(&(input_image_packet.Get<ImageFrame>()));
  input_mat.convertTo(packet_mat_view, CV_32FC1, 1 / 255.f);
  std::vector<std::pair<int, int>> output_dims{
      {256, 333}, {512, 512}, {1024, 1024}};
  for (auto& output_dim : output_dims) {
    Packet input_output_dim_packet =
        MakePacket<std::pair<int, int>>(output_dim);
    std::vector<std::string> scale_modes{"FIT", "STRETCH"};
    for (const auto& scale_mode : scale_modes) {
      CalculatorGraphConfig::Node node_config =
          ParseTextProtoOrDie<CalculatorGraphConfig::Node>(
              absl::Substitute(R"(
          calculator: "ImageTransformationCalculator"
          input_stream: "IMAGE:input_image"
          input_stream: "OUTPUT_DIMENSIONS:image_size"
          output_stream: "IMAGE:output_image"
          options: {
            [mediapipe.ImageTransformationCalculatorOptions.ext]: {
              scale_mode: $0
              interpolation_mode: NEAREST
            }
          })",
                               scale_mode));
      CalculatorRunner runner(node_config);
      runner.MutableInputs()->Tag("IMAGE").packets.push_back(
          input_image_packet.At(Timestamp(0)));
      runner.MutableInputs()
          ->Tag("OUTPUT_DIMENSIONS")
          .packets.push_back(input_output_dim_packet.At(Timestamp(0)));
      MP_ASSERT_OK(runner.Run());
      const auto& outputs = runner.Outputs();
      ASSERT_EQ(outputs.NumEntries(), 1);
      const std::vector<Packet>& packets = outputs.Tag("IMAGE").packets;
      ASSERT_EQ(packets.size(), 1);
      const auto& result = packets[0].Get<ImageFrame>();
      ASSERT_EQ(output_dim.first, result.Width());
      ASSERT_EQ(output_dim.second, result.Height());
      auto unique_input_values = computeUniqueValues(packet_mat_view);
      auto unique_output_values =
          computeUniqueValues(formats::MatView(&result));
      EXPECT_THAT(unique_input_values,
                  ::testing::ContainerEq(unique_output_values));
    }
  }
 }
 TEST(ImageTransformationCalculatorTest, NearestNeighborResizingGpu) {
  cv::Mat input_mat;
  cv::cvtColor(cv::imread(file::JoinPath("./",
                                         "/mediapipe/calculators/"
                                         "image/testdata/binary_mask.png")),
               input_mat, cv::COLOR_BGR2RGBA);
  std::vector<std::pair<int, int>> output_dims{
      {256, 333}, {512, 512}, {1024, 1024}};
  for (auto& output_dim : output_dims) {
    std::vector<std::string> scale_modes{"FIT"};  //, "STRETCH"};
    for (const auto& scale_mode : scale_modes) {
      CalculatorGraphConfig graph_config =
          ParseTextProtoOrDie<CalculatorGraphConfig>(
              absl::Substitute(R"(
          input_stream: "input_image"
          input_stream: "image_size"
          output_stream: "output_image"
          node {
            calculator: "ImageFrameToGpuBufferCalculator"
            input_stream: "input_image"
            output_stream: "input_image_gpu"
          }
          node {
            calculator: "ImageTransformationCalculator"
            input_stream: "IMAGE_GPU:input_image_gpu"
            input_stream: "OUTPUT_DIMENSIONS:image_size"
            output_stream: "IMAGE_GPU:output_image_gpu"
            options: {
              [mediapipe.ImageTransformationCalculatorOptions.ext]: {
                scale_mode: $0
                interpolation_mode: NEAREST
              }
            }
          }
          node {
            calculator: "GpuBufferToImageFrameCalculator"
            input_stream: "output_image_gpu"
            output_stream: "output_image"
          })",
                               scale_mode));
      ImageFrame input_image(ImageFormat::SRGBA, input_mat.size().width,
                             input_mat.size().height);
      input_mat.copyTo(formats::MatView(&input_image));
      std::vector<Packet> output_image_packets;
      tool::AddVectorSink("output_image", &graph_config, &output_image_packets);
      CalculatorGraph graph(graph_config);
      MP_ASSERT_OK(graph.StartRun({}));
      MP_ASSERT_OK(graph.AddPacketToInputStream(
          "input_image",
          MakePacket<ImageFrame>(std::move(input_image)).At(Timestamp(0))));
      MP_ASSERT_OK(graph.AddPacketToInputStream(
          "image_size",
          MakePacket<std::pair<int, int>>(output_dim).At(Timestamp(0))));
      MP_ASSERT_OK(graph.WaitUntilIdle());
      ASSERT_THAT(output_image_packets, testing::SizeIs(1));
      const auto& output_image = output_image_packets[0].Get<ImageFrame>();
      ASSERT_EQ(output_dim.first, output_image.Width());
      ASSERT_EQ(output_dim.second, output_image.Height());
      auto unique_input_values = computeUniqueValues(input_mat);
      auto unique_output_values =
          computeUniqueValues(formats::MatView(&output_image));
      EXPECT_THAT(unique_input_values,
                  ::testing::ContainerEq(unique_output_values));
    }
  }
 }
 TEST(ImageTransformationCalculatorTest,
     NearestNeighborResizingWorksForFloatTexture) {
  cv::Mat input_mat;
  cv::cvtColor(cv::imread(file::JoinPath("./",
                                         "/mediapipe/calculators/"
                                         "image/testdata/binary_mask.png")),
               input_mat, cv::COLOR_BGR2GRAY);
  Packet input_image_packet = MakePacket<ImageFrame>(
      ImageFormat::VEC32F1, input_mat.size().width, input_mat.size().height);
  cv::Mat packet_mat_view =
      formats::MatView(&(input_image_packet.Get<ImageFrame>()));
  input_mat.convertTo(packet_mat_view, CV_32FC1, 1 / 255.f);
  std::vector<std::pair<int, int>> output_dims{
      {256, 333}, {512, 512}, {1024, 1024}};
  for (auto& output_dim : output_dims) {
    std::vector<std::string> scale_modes{"FIT"};  //, "STRETCH"};
    for (const auto& scale_mode : scale_modes) {
      CalculatorGraphConfig graph_config =
          ParseTextProtoOrDie<CalculatorGraphConfig>(
              absl::Substitute(R"(
          input_stream: "input_image"
          input_stream: "image_size"
          output_stream: "output_image"
          node {
            calculator: "ImageFrameToGpuBufferCalculator"
            input_stream: "input_image"
            output_stream: "input_image_gpu"
          }
          node {
            calculator: "ImageTransformationCalculator"
            input_stream: "IMAGE_GPU:input_image_gpu"
            input_stream: "OUTPUT_DIMENSIONS:image_size"
            output_stream: "IMAGE_GPU:output_image_gpu"
            options: {
              [mediapipe.ImageTransformationCalculatorOptions.ext]: {
                scale_mode: $0
                interpolation_mode: NEAREST
              }
            }
          }
          node {
            calculator: "GpuBufferToImageFrameCalculator"
            input_stream: "output_image_gpu"
            output_stream: "output_image"
          })",
                               scale_mode));
      std::vector<Packet> output_image_packets;
      tool::AddVectorSink("output_image", &graph_config, &output_image_packets);
      CalculatorGraph graph(graph_config);
      MP_ASSERT_OK(graph.StartRun({}));
      MP_ASSERT_OK(graph.AddPacketToInputStream(
          "input_image", input_image_packet.At(Timestamp(0))));
      MP_ASSERT_OK(graph.AddPacketToInputStream(
          "image_size",
          MakePacket<std::pair<int, int>>(output_dim).At(Timestamp(0))));
      MP_ASSERT_OK(graph.WaitUntilIdle());
      ASSERT_THAT(output_image_packets, testing::SizeIs(1));
      const auto& output_image = output_image_packets[0].Get<ImageFrame>();
      ASSERT_EQ(output_dim.first, output_image.Width());
      ASSERT_EQ(output_dim.second, output_image.Height());
      auto unique_input_values = computeUniqueValues(packet_mat_view);
      auto unique_output_values =
          computeUniqueValues(formats::MatView(&output_image));
      EXPECT_THAT(unique_input_values,
                  ::testing::ContainerEq(unique_output_values));
    }
  }
 }
 }  // namespace
 }  // namespace mediapipe
@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "absl/log/absl_check.h"
 #include "mediapipe/calculators/image/opencv_image_encoder_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/formats/image_frame_opencv.h"
@@ -62,7 +61,7 @@ absl::Status OpenCvImageEncoderCalculator::Open(CalculatorContext* cc) {
 absl::Status OpenCvImageEncoderCalculator::Process(CalculatorContext* cc) {
  const ImageFrame& image_frame = cc->Inputs().Index(0).Get<ImageFrame>();
-  ABSL_CHECK_EQ(1, image_frame.ByteDepth());
+  CHECK_EQ(1, image_frame.ByteDepth());
  std::unique_ptr<OpenCvImageEncoderCalculatorResults> encoded_result =
      absl::make_unique<OpenCvImageEncoderCalculatorResults>();
@@ -18,8 +18,6 @@
 #include <memory>
 #include <string>
 #include "absl/log/absl_check.h"
 #include "absl/log/absl_log.h"
 #include "absl/strings/str_cat.h"
 #include "absl/strings/substitute.h"
 #include "libyuv/scale.h"
@@ -295,7 +293,7 @@ absl::Status ScaleImageCalculator::InitializeFrameInfo(CalculatorContext* cc) {
    header->width = output_width_;
    header->height = output_height_;
    header->format = output_format_;
-    ABSL_LOG(INFO) << "OUTPUTTING HEADER on stream";
+    LOG(INFO) << "OUTPUTTING HEADER on stream";
    cc->Outputs()
        .Tag("VIDEO_HEADER")
        .Add(header.release(), Timestamp::PreStream());
@@ -395,11 +393,10 @@ absl::Status ScaleImageCalculator::Open(CalculatorContext* cc) {
          .SetHeader(Adopt(output_header.release()));
      has_header_ = true;
    } else {
-      ABSL_LOG(WARNING)
+      LOG(WARNING) << "Stream had a VideoHeader which didn't have sufficient "
-          << "Stream had a VideoHeader which didn't have sufficient "
+                      "information.  "
-             "information.  "
+                      "Dropping VideoHeader and trying to deduce needed "
-             "Dropping VideoHeader and trying to deduce needed "
+                      "information.";
             "information.";
      input_width_ = 0;
      input_height_ = 0;
      if (!options_.has_input_format()) {
@@ -510,7 +507,7 @@ absl::Status ScaleImageCalculator::ValidateImageFrame(
 absl::Status ScaleImageCalculator::ValidateYUVImage(CalculatorContext* cc,
                                                    const YUVImage& yuv_image) {
-  ABSL_CHECK_EQ(input_format_, ImageFormat::YCBCR420P);
+  CHECK_EQ(input_format_, ImageFormat::YCBCR420P);
  if (!has_header_) {
    if (input_width_ != yuv_image.width() ||
        input_height_ != yuv_image.height()) {
@@ -18,7 +18,6 @@
 #include <string>
 #include "absl/log/absl_check.h"
 #include "absl/strings/str_split.h"
 #include "mediapipe/framework/port/logging.h"
 #include "mediapipe/framework/port/ret_check.h"
@@ -41,10 +40,10 @@ absl::Status FindCropDimensions(int input_width, int input_height,    //
                                const std::string& max_aspect_ratio,  //
                                int* crop_width, int* crop_height,    //
                                int* col_start, int* row_start) {
-  ABSL_CHECK(crop_width);
+  CHECK(crop_width);
-  ABSL_CHECK(crop_height);
+  CHECK(crop_height);
-  ABSL_CHECK(col_start);
+  CHECK(col_start);
-  ABSL_CHECK(row_start);
+  CHECK(row_start);
  double min_aspect_ratio_q = 0.0;
  double max_aspect_ratio_q = 0.0;
@@ -84,8 +83,8 @@ absl::Status FindCropDimensions(int input_width, int input_height,    //
    }
  }
-  ABSL_CHECK_LE(*crop_width, input_width);
+  CHECK_LE(*crop_width, input_width);
-  ABSL_CHECK_LE(*crop_height, input_height);
+  CHECK_LE(*crop_height, input_height);
  return absl::OkStatus();
 }
@@ -97,8 +96,8 @@ absl::Status FindOutputDimensions(int input_width,             //
                                  bool preserve_aspect_ratio,  //
                                  int scale_to_multiple_of,    //
                                  int* output_width, int* output_height) {
-  ABSL_CHECK(output_width);
+  CHECK(output_width);
-  ABSL_CHECK(output_height);
+  CHECK(output_height);
  if (target_max_area > 0 && input_width * input_height > target_max_area) {
    preserve_aspect_ratio = true;
@@ -15,13 +15,13 @@
 #include <algorithm>
 #include <memory>
 #include "absl/log/absl_log.h"
 #include "mediapipe/calculators/image/segmentation_smoothing_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/calculator_options.pb.h"
 #include "mediapipe/framework/formats/image.h"
 #include "mediapipe/framework/formats/image_format.pb.h"
 #include "mediapipe/framework/formats/image_frame.h"
 #include "mediapipe/framework/port/logging.h"
 #include "mediapipe/framework/port/status.h"
 #include "mediapipe/framework/port/vector.h"
@@ -110,7 +110,7 @@ REGISTER_CALCULATOR(SegmentationSmoothingCalculator);
 absl::Status SegmentationSmoothingCalculator::GetContract(
    CalculatorContract* cc) {
-  RET_CHECK_GE(cc->Inputs().NumEntries(), 1);
+  CHECK_GE(cc->Inputs().NumEntries(), 1);
  cc->Inputs().Tag(kCurrentMaskTag).Set<Image>();
  cc->Inputs().Tag(kPreviousMaskTag).Set<Image>();
@@ -273,7 +273,7 @@ absl::Status SegmentationSmoothingCalculator::RenderGpu(CalculatorContext* cc) {
  const auto& previous_frame = cc->Inputs().Tag(kPreviousMaskTag).Get<Image>();
  if (previous_frame.format() != current_frame.format()) {
-    ABSL_LOG(ERROR) << "Warning: mixing input format types. ";
+    LOG(ERROR) << "Warning: mixing input format types. ";
  }
  auto previous_texture = gpu_helper_.CreateSourceTexture(previous_frame);
@@ -14,7 +14,6 @@
 #include <memory>
 #include "absl/log/absl_log.h"
 #include "mediapipe/calculators/image/segmentation_smoothing_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/calculator_runner.h"
@@ -170,7 +169,7 @@ void RunTest(bool use_gpu, float mix_ratio, cv::Mat& test_result) {
      }
    }
  } else {
-    ABSL_LOG(ERROR) << "invalid ratio";
+    LOG(ERROR) << "invalid ratio";
  }
 }
@@ -14,13 +14,13 @@
 #include <memory>
 #include "absl/log/absl_log.h"
 #include "mediapipe/calculators/image/set_alpha_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/calculator_options.pb.h"
 #include "mediapipe/framework/formats/image_format.pb.h"
 #include "mediapipe/framework/formats/image_frame.h"
 #include "mediapipe/framework/formats/image_frame_opencv.h"
 #include "mediapipe/framework/port/logging.h"
 #include "mediapipe/framework/port/opencv_core_inc.h"
 #include "mediapipe/framework/port/opencv_imgproc_inc.h"
 #include "mediapipe/framework/port/status.h"
@@ -142,7 +142,7 @@ class SetAlphaCalculator : public CalculatorBase {
 REGISTER_CALCULATOR(SetAlphaCalculator);
 absl::Status SetAlphaCalculator::GetContract(CalculatorContract* cc) {
-  RET_CHECK_GE(cc->Inputs().NumEntries(), 1);
+  CHECK_GE(cc->Inputs().NumEntries(), 1);
  bool use_gpu = false;
@@ -268,7 +268,7 @@ absl::Status SetAlphaCalculator::RenderCpu(CalculatorContext* cc) {
  const auto& input_frame = cc->Inputs().Tag(kInputFrameTag).Get<ImageFrame>();
  const cv::Mat input_mat = formats::MatView(&input_frame);
  if (!(input_mat.type() == CV_8UC3 || input_mat.type() == CV_8UC4)) {
-    ABSL_LOG(ERROR) << "Only 3 or 4 channel 8-bit input image supported";
+    LOG(ERROR) << "Only 3 or 4 channel 8-bit input image supported";
  }
  // Setup destination image
@@ -328,7 +328,7 @@ absl::Status SetAlphaCalculator::RenderGpu(CalculatorContext* cc) {
      cc->Inputs().Tag(kInputFrameTagGpu).Get<mediapipe::GpuBuffer>();
  if (!(input_frame.format() == mediapipe::GpuBufferFormat::kBGRA32 ||
        input_frame.format() == mediapipe::GpuBufferFormat::kRGB24)) {
-    ABSL_LOG(ERROR) << "Only RGB or RGBA input image supported";
+    LOG(ERROR) << "Only RGB or RGBA input image supported";
  }
  auto input_texture = gpu_helper_.CreateSourceTexture(input_frame);
@@ -18,7 +18,6 @@ licenses(["notice"])
 filegroup(
    name = "test_images",
    srcs = [
        "binary_mask.png",
        "dino.jpg",
        "dino_quality_50.jpg",
        "dino_quality_80.jpg",
@@ -31,14 +31,12 @@ mediapipe_proto_library(
 cc_library(
    name = "callback_packet_calculator",
    srcs = ["callback_packet_calculator.cc"],
    hdrs = ["callback_packet_calculator.h"],
    visibility = ["//mediapipe/framework:__subpackages__"],
    deps = [
        ":callback_packet_calculator_cc_proto",
        "//mediapipe/framework:calculator_base",
        "//mediapipe/framework:calculator_registry",
        "//mediapipe/framework:output_side_packet",
        "@com_google_absl//absl/status",
    ],
    alwayslink = 1,
 )
@@ -11,12 +11,10 @@
 // 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/internal/callback_packet_calculator.h"
 #include <functional>
 #include <string>
 #include "absl/status/status.h"
 #include "mediapipe/calculators/internal/callback_packet_calculator.pb.h"  // NOLINT
 #include "mediapipe/framework/calculator_base.h"
 #include "mediapipe/framework/calculator_registry.h"
@@ -41,55 +39,64 @@ void DumpPostStreamPacket(Packet* post_stream_packet, const Packet& packet) {
    *post_stream_packet = packet;
  }
 }
 }  // namespace
-absl::Status CallbackPacketCalculator::GetContract(CalculatorContract* cc) {
+// Creates a callback which takes a packet and stores it either in a
-  const auto& options = cc->Options<CallbackPacketCalculatorOptions>();
+// vector of packets or stores only the packet at PostStream timestamp.
-  switch (options.type()) {
+// The kind of callback is controlled by an option.  The callback is
-    case CallbackPacketCalculatorOptions::VECTOR_PACKET:
+// a std::function and is directly usable by CallbackCalculator.
-    case CallbackPacketCalculatorOptions::POST_STREAM_PACKET:
+// Since the options for the packet generator include a serialized pointer
-      cc->OutputSidePackets()
+// value, the resulting callback is only valid on the original machine
-          .Index(0)
+// while that pointer is still alive.
-          .Set<std::function<void(const Packet&)>>();
+class CallbackPacketCalculator : public CalculatorBase {
-      break;
+ public:
-    default:
+  static absl::Status GetContract(CalculatorContract* cc) {
-      return mediapipe::InvalidArgumentErrorBuilder(MEDIAPIPE_LOC)
+    const auto& options = cc->Options<CallbackPacketCalculatorOptions>();
-             << "Invalid type of callback to produce.";
+    switch (options.type()) {
      case CallbackPacketCalculatorOptions::VECTOR_PACKET:
      case CallbackPacketCalculatorOptions::POST_STREAM_PACKET:
        cc->OutputSidePackets()
            .Index(0)
            .Set<std::function<void(const Packet&)>>();
        break;
      default:
        return mediapipe::InvalidArgumentErrorBuilder(MEDIAPIPE_LOC)
               << "Invalid type of callback to produce.";
    }
    return absl::OkStatus();
  }
  return absl::OkStatus();
 }
-absl::Status CallbackPacketCalculator::Open(CalculatorContext* cc) {
+  absl::Status Open(CalculatorContext* cc) override {
-  const auto& options = cc->Options<CallbackPacketCalculatorOptions>();
+    const auto& options = cc->Options<CallbackPacketCalculatorOptions>();
-  void* ptr;
+    void* ptr;
-  if (sscanf(options.pointer().c_str(), "%p", &ptr) != 1) {
+    if (sscanf(options.pointer().c_str(), "%p", &ptr) != 1) {
    return mediapipe::InvalidArgumentErrorBuilder(MEDIAPIPE_LOC)
           << "Stored pointer value in options is invalid.";
  }
  switch (options.type()) {
    case CallbackPacketCalculatorOptions::VECTOR_PACKET:
      cc->OutputSidePackets().Index(0).Set(
          MakePacket<std::function<void(const Packet&)>>(std::bind(
              &DumpToVector, reinterpret_cast<std::vector<Packet>*>(ptr),
              std::placeholders::_1)));
      break;
    case CallbackPacketCalculatorOptions::POST_STREAM_PACKET:
      cc->OutputSidePackets().Index(0).Set(
          MakePacket<std::function<void(const Packet&)>>(
              std::bind(&DumpPostStreamPacket, reinterpret_cast<Packet*>(ptr),
                        std::placeholders::_1)));
      break;
    default:
      return mediapipe::InvalidArgumentErrorBuilder(MEDIAPIPE_LOC)
-             << "Invalid type to dump into.";
+             << "Stored pointer value in options is invalid.";
    }
    switch (options.type()) {
      case CallbackPacketCalculatorOptions::VECTOR_PACKET:
        cc->OutputSidePackets().Index(0).Set(
            MakePacket<std::function<void(const Packet&)>>(std::bind(
                &DumpToVector, reinterpret_cast<std::vector<Packet>*>(ptr),
                std::placeholders::_1)));
        break;
      case CallbackPacketCalculatorOptions::POST_STREAM_PACKET:
        cc->OutputSidePackets().Index(0).Set(
            MakePacket<std::function<void(const Packet&)>>(
                std::bind(&DumpPostStreamPacket, reinterpret_cast<Packet*>(ptr),
                          std::placeholders::_1)));
        break;
      default:
        return mediapipe::InvalidArgumentErrorBuilder(MEDIAPIPE_LOC)
               << "Invalid type to dump into.";
    }
    return absl::OkStatus();
  }
  return absl::OkStatus();
 }
-absl::Status CallbackPacketCalculator::Process(CalculatorContext* cc) {
+  absl::Status Process(CalculatorContext* cc) override {
-  return absl::OkStatus();
+    return absl::OkStatus();
-}
+  }
 };
 REGISTER_CALCULATOR(CallbackPacketCalculator);
@@ -1,39 +0,0 @@
 // Copyright 2023 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_INTERNAL_CALLBACK_PACKET_CALCULATOR_H_
 #define MEDIAPIPE_CALCULATORS_INTERNAL_CALLBACK_PACKET_CALCULATOR_H_
 #include "absl/status/status.h"
 #include "mediapipe/framework/calculator_base.h"
 namespace mediapipe {
 // Creates a callback which takes a packet and stores it either in a
 // vector of packets or stores only the packet at PostStream timestamp.
 // The kind of callback is controlled by an option.  The callback is
 // a std::function and is directly usable by CallbackCalculator.
 // Since the options for the packet generator include a serialized pointer
 // value, the resulting callback is only valid on the original machine
 // while that pointer is still alive.
 class CallbackPacketCalculator : public CalculatorBase {
 public:
  static absl::Status GetContract(CalculatorContract* cc);
  absl::Status Open(CalculatorContext* cc) override;
  absl::Status Process(CalculatorContext* cc) override;
 };
 }  // namespace mediapipe
 #endif  // MEDIAPIPE_CALCULATORS_INTERNAL_CALLBACK_PACKET_CALCULATOR_H_
@@ -87,7 +87,6 @@ cc_library(
        "//mediapipe/framework/formats:time_series_header_cc_proto",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/util:time_series_util",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/memory",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/status:statusor",
@@ -182,7 +181,6 @@ cc_library(
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/api2:node",
        "//mediapipe/framework/formats:tensor",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/status",
    ],
    alwayslink = 1,
@@ -200,7 +198,6 @@ cc_test(
        "//mediapipe/framework/formats:tensor",
        "//mediapipe/framework/port:gtest_main",
        "//mediapipe/framework/port:parse_text_proto",
        "@com_google_absl//absl/log:absl_check",
        "@org_tensorflow//tensorflow/lite/c:common",
    ],
 )
@@ -448,7 +445,6 @@ cc_library(
        "//mediapipe/framework/deps:file_path",
        "//mediapipe/gpu:gl_calculator_helper",
        "//mediapipe/util/tflite:tflite_gpu_runner",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_absl//absl/memory",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/status:statusor",
@@ -478,7 +474,6 @@ cc_library(
        "//mediapipe/gpu:gpu_buffer",
        "//mediapipe/objc:mediapipe_framework_ios",
        "//mediapipe/util/tflite:config",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_absl//absl/memory",
        "@com_google_absl//absl/strings:str_format",
        "@org_tensorflow//tensorflow/lite/delegates/gpu:metal_delegate",
@@ -625,7 +620,6 @@ mediapipe_proto_library(
    deps = [
        "//mediapipe/framework:calculator_options_proto",
        "//mediapipe/framework:calculator_proto",
        "//mediapipe/gpu:gpu_origin_proto",
    ],
 )
@@ -655,18 +649,7 @@ cc_library(
        "//mediapipe/framework/formats:matrix",
        "//mediapipe/framework/formats:tensor",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "//mediapipe/framework/port:statusor",
        "//mediapipe/gpu:gpu_buffer_format",
        "//mediapipe/gpu:gpu_origin_cc_proto",
        "//mediapipe/util:resource_util",
        "@com_google_absl//absl/log",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_absl//absl/log:check",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/status:statusor",
        "@com_google_absl//absl/strings:str_format",
    ] + select({
        "//mediapipe/gpu:disable_gpu": [],
        "//conditions:default": ["tensor_converter_calculator_gpu_deps"],
@@ -716,11 +699,9 @@ cc_test(
        "//mediapipe/framework/formats:tensor",
        "//mediapipe/framework/port:gtest_main",
        "//mediapipe/framework/port:integral_types",
        "//mediapipe/framework/port:opencv_core",
        "//mediapipe/framework/port:parse_text_proto",
        "//mediapipe/framework/tool:validate_type",
        "@com_google_absl//absl/memory",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/strings",
    ],
 )
@@ -756,8 +737,6 @@ cc_library(
        "//mediapipe/framework/formats:tensor",
        "//mediapipe/framework/formats/object_detection:anchor_cc_proto",
        "//mediapipe/framework/port:ret_check",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_absl//absl/strings:str_format",
        "@com_google_absl//absl/types:span",
    ] + selects.with_or({
@@ -814,7 +793,6 @@ cc_library(
        "//mediapipe/framework/formats:landmark_cc_proto",
        "//mediapipe/framework/formats:tensor",
        "//mediapipe/framework/port:ret_check",
        "@com_google_absl//absl/log:absl_check",
    ],
    alwayslink = 1,
 )
@@ -1007,8 +985,6 @@ cc_library(
        "//mediapipe/framework/port:status",
        "//mediapipe/framework/port:statusor",
        "//mediapipe/gpu:gpu_origin_cc_proto",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/log:absl_log",
    ] + select({
        "//mediapipe/gpu:disable_gpu": [],
        "//conditions:default": [":image_to_tensor_calculator_gpu_deps"],
@@ -1101,7 +1077,6 @@ cc_test(
        "//mediapipe/framework/port:parse_text_proto",
        "//mediapipe/util:image_test_utils",
        "@com_google_absl//absl/flags:flag",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/memory",
        "@com_google_absl//absl/strings",
        "@com_google_absl//absl/strings:str_format",
@@ -1229,7 +1204,6 @@ cc_library(
            "//mediapipe/gpu:gl_calculator_helper",
            "//mediapipe/gpu:gl_simple_shaders",
            "//mediapipe/gpu:shader_util",
            "@com_google_absl//absl/log:absl_log",
            "@com_google_absl//absl/strings",
        ],
    }),
@@ -20,7 +20,6 @@
 #include <utility>
 #include <vector>
 #include "absl/log/absl_check.h"
 #include "absl/memory/memory.h"
 #include "absl/status/status.h"
 #include "absl/status/statusor.h"
@@ -349,7 +348,7 @@ absl::Status AudioToTensorCalculator::Process(CalculatorContext* cc) {
    return absl::InvalidArgumentError(
        "The audio data should be stored in column-major.");
  }
-  ABSL_CHECK(channels_match || mono_output);
+  CHECK(channels_match || mono_output);
  const Matrix& input = channels_match ? input_frame
                                       // Mono mixdown.
                                       : input_frame.colwise().mean();
@@ -458,7 +457,7 @@ absl::Status AudioToTensorCalculator::SetupStreamingResampler(
 }
 void AudioToTensorCalculator::AppendZerosToSampleBuffer(int num_samples) {
-  ABSL_CHECK_GE(num_samples, 0);  // Ensured by `UpdateContract`.
+  CHECK_GE(num_samples, 0);  // Ensured by `UpdateContract`.
  if (num_samples == 0) {
    return;
  }
@@ -18,7 +18,6 @@
 #include <utility>
 #include <vector>
 #include "absl/log/absl_check.h"
 #include "mediapipe/calculators/tensor/feedback_tensors_calculator.pb.h"
 #include "mediapipe/framework/calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
@@ -66,7 +65,7 @@ template <typename T>
 Tensor MakeTensor(std::initializer_list<int> shape,
                  std::initializer_list<T> values) {
  Tensor tensor(TensorElementType<T>::value, shape);
-  ABSL_CHECK_EQ(values.size(), tensor.shape().num_elements())
+  CHECK_EQ(values.size(), tensor.shape().num_elements())
      << "The size of `values` is incompatible with `shape`";
  absl::c_copy(values, tensor.GetCpuWriteView().buffer<T>());
  return tensor;
@@ -16,7 +16,6 @@
 #include <memory>
 #include <vector>
 #include "absl/log/absl_log.h"
 #include "mediapipe/calculators/tensor/image_to_tensor_calculator.pb.h"
 #include "mediapipe/calculators/tensor/image_to_tensor_converter.h"
 #include "mediapipe/calculators/tensor/image_to_tensor_utils.h"
@@ -285,9 +284,9 @@ class ImageToTensorCalculator : public Node {
                             cc, GetBorderMode(options_.border_mode()),
                             GetOutputTensorType(/*uses_gpu=*/false, params_)));
 #else
-        ABSL_LOG(FATAL) << "Cannot create image to tensor CPU converter since "
+        LOG(FATAL) << "Cannot create image to tensor CPU converter since "
-                           "MEDIAPIPE_DISABLE_OPENCV is defined and "
+                      "MEDIAPIPE_DISABLE_OPENCV is defined and "
-                           "MEDIAPIPE_ENABLE_HALIDE is not defined.";
+                      "MEDIAPIPE_ENABLE_HALIDE is not defined.";
 #endif  // !MEDIAPIPE_DISABLE_HALIDE
      }
    }
@@ -18,7 +18,6 @@
 #include <vector>
 #include "absl/flags/flag.h"
 #include "absl/log/absl_check.h"
 #include "absl/memory/memory.h"
 #include "absl/strings/str_format.h"
 #include "absl/strings/substitute.h"
@@ -206,7 +205,7 @@ mediapipe::ImageFormat::Format GetImageFormat(int image_channels) {
  } else if (image_channels == 1) {
    return ImageFormat::GRAY8;
  }
-  ABSL_CHECK(false) << "Unsupported input image channles: " << image_channels;
+  CHECK(false) << "Unsupported input image channles: " << image_channels;
 }
 Packet MakeImageFramePacket(cv::Mat input) {
@@ -22,7 +22,6 @@
 #include <memory>
 #include <vector>
 #include "absl/log/absl_log.h"
 #include "absl/strings/str_cat.h"
 #include "mediapipe/calculators/tensor/image_to_tensor_converter.h"
 #include "mediapipe/calculators/tensor/image_to_tensor_converter_gl_utils.h"
@@ -260,7 +259,7 @@ class GlProcessor : public ImageToTensorConverter {
    // error. So in that case, we'll grab the transpose of our original matrix
    // and send that instead.
    const auto gl_context = mediapipe::GlContext::GetCurrent();
-    ABSL_LOG_IF(FATAL, !gl_context) << "GlContext is not bound to the thread.";
+    LOG_IF(FATAL, !gl_context) << "GlContext is not bound to the thread.";
    if (gl_context->GetGlVersion() == mediapipe::GlVersion::kGLES2) {
      GetTransposedRotatedSubRectToRectTransformMatrix(
          sub_rect, texture.width(), texture.height(), flip_horizontaly,
@@ -88,20 +88,6 @@ message InferenceCalculatorOptions {
      // serialized model is invalid or missing.
      optional string serialized_model_dir = 7;
      enum CacheWritingBehavior {
        // Do not write any caches.
        NO_WRITE = 0;
        // Try to write caches, log on failure.
        TRY_WRITE = 1;
        // Write caches or return an error if write fails.
        WRITE_OR_ERROR = 2;
      }
      // Specifies how GPU caches are written to disk.
      optional CacheWritingBehavior cache_writing_behavior = 10
          [default = WRITE_OR_ERROR];
      // Unique token identifying the model. Used in conjunction with
      // "serialized_model_dir". It is the caller's responsibility to ensure
      // there is no clash of the tokens.
@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include <cstdint>
 #include <cstring>
 #include <memory>
 #include <string>
@@ -27,7 +26,6 @@
 #include "mediapipe/util/tflite/tflite_gpu_runner.h"
 #if defined(MEDIAPIPE_ANDROID) || defined(MEDIAPIPE_CHROMIUMOS)
 #include "absl/log/absl_log.h"
 #include "mediapipe/framework/deps/file_path.h"
 #include "mediapipe/util/android/file/base/file.h"
 #include "mediapipe/util/android/file/base/filesystem.h"
@@ -70,21 +68,13 @@ class InferenceCalculatorGlAdvancedImpl
        const mediapipe::InferenceCalculatorOptions::Delegate::Gpu&
            gpu_delegate_options);
    absl::Status ReadGpuCaches(tflite::gpu::TFLiteGPURunner* gpu_runner) const;
    // Writes caches to disk based on |cache_writing_behavior_|.
    absl::Status SaveGpuCachesBasedOnBehavior(
        tflite::gpu::TFLiteGPURunner* gpu_runner) const;
    bool UseSerializedModel() const { return use_serialized_model_; }
   private:
    // Writes caches to disk, returns error on failure.
    absl::Status SaveGpuCaches(tflite::gpu::TFLiteGPURunner* gpu_runner) const;
   private:
    bool use_kernel_caching_ = false;
    std::string cached_kernel_filename_;
    bool use_serialized_model_ = false;
    std::string serialized_model_path_;
    mediapipe::InferenceCalculatorOptions::Delegate::Gpu::CacheWritingBehavior
        cache_writing_behavior_;
  };
  // Helper class that wraps everything related to GPU inference acceleration.
@@ -160,6 +150,8 @@ InferenceCalculatorGlAdvancedImpl::GpuInferenceRunner::Process(
 }
 absl::Status InferenceCalculatorGlAdvancedImpl::GpuInferenceRunner::Close() {
  MP_RETURN_IF_ERROR(
      on_disk_cache_helper_.SaveGpuCaches(tflite_gpu_runner_.get()));
  return gpu_helper_.RunInGlContext([this]() -> absl::Status {
    tflite_gpu_runner_.reset();
    return absl::OkStatus();
@@ -234,15 +226,9 @@ InferenceCalculatorGlAdvancedImpl::GpuInferenceRunner::InitTFLiteGPURunner(
                         tflite_gpu_runner_->GetOutputShapes()[i].c};
  }
  if (on_disk_cache_helper_.UseSerializedModel()) {
    tflite_gpu_runner_->ForceOpenCLInitFromSerializedModel();
  }
  MP_RETURN_IF_ERROR(
      on_disk_cache_helper_.ReadGpuCaches(tflite_gpu_runner_.get()));
-  MP_RETURN_IF_ERROR(tflite_gpu_runner_->Build());
+  return tflite_gpu_runner_->Build();
  return on_disk_cache_helper_.SaveGpuCachesBasedOnBehavior(
      tflite_gpu_runner_.get());
 }
 #if defined(MEDIAPIPE_ANDROID) || defined(MEDIAPIPE_CHROMIUMOS)
@@ -271,36 +257,9 @@ absl::Status InferenceCalculatorGlAdvancedImpl::OnDiskCacheHelper::Init(
        mediapipe::file::JoinPath(gpu_delegate_options.serialized_model_dir(),
                                  gpu_delegate_options.model_token());
  }
  cache_writing_behavior_ = gpu_delegate_options.has_cache_writing_behavior()
                                ? gpu_delegate_options.cache_writing_behavior()
                                : mediapipe::InferenceCalculatorOptions::
                                      Delegate::Gpu::WRITE_OR_ERROR;
  return absl::OkStatus();
 }
 absl::Status InferenceCalculatorGlAdvancedImpl::OnDiskCacheHelper::
    SaveGpuCachesBasedOnBehavior(
        tflite::gpu::TFLiteGPURunner* gpu_runner) const {
  switch (cache_writing_behavior_) {
    case mediapipe::InferenceCalculatorOptions::Delegate::Gpu::NO_WRITE:
      return absl::OkStatus();
    case mediapipe::InferenceCalculatorOptions::Delegate::Gpu::TRY_WRITE: {
      auto status = SaveGpuCaches(gpu_runner);
      if (!status.ok()) {
        ABSL_LOG_FIRST_N(WARNING, 1) << "Failed to save gpu caches: " << status;
      }
      return absl::OkStatus();
    }
    case mediapipe::InferenceCalculatorOptions::Delegate::Gpu::WRITE_OR_ERROR:
      return SaveGpuCaches(gpu_runner);
    default:
      ABSL_LOG_FIRST_N(ERROR, 1)
          << "Unknown cache writing behavior: "
          << static_cast<uint32_t>(cache_writing_behavior_);
      return absl::InvalidArgumentError("Unknown cache writing behavior.");
  }
 }
 absl::Status
 InferenceCalculatorGlAdvancedImpl::OnDiskCacheHelper::SaveGpuCaches(
    tflite::gpu::TFLiteGPURunner* gpu_runner) const {
@@ -355,12 +314,6 @@ absl::Status InferenceCalculatorGlAdvancedImpl::OnDiskCacheHelper::Init(
  return absl::OkStatus();
 }
 absl::Status InferenceCalculatorGlAdvancedImpl::OnDiskCacheHelper::
    SaveGpuCachesBasedOnBehavior(
        tflite::gpu::TFLiteGPURunner* gpu_runner) const {
  return absl::OkStatus();
 }
 absl::Status
 InferenceCalculatorGlAdvancedImpl::OnDiskCacheHelper::ReadGpuCaches(
    tflite::gpu::TFLiteGPURunner* gpu_runner) const {
@@ -21,7 +21,6 @@
 #include <string>
 #include <vector>
 #include "absl/log/absl_log.h"
 #include "absl/memory/memory.h"
 #include "absl/strings/str_format.h"
 #include "mediapipe/calculators/tensor/inference_calculator.h"
@@ -75,7 +74,7 @@ tflite::gpu::BHWC BhwcFromTensorShape(const Tensor::Shape& shape) {
      break;
    default:
      // Handles 0 and >4.
-      ABSL_LOG(FATAL)
+      LOG(FATAL)
          << "Dimensions size must be in range [1,4] for GPU inference, but "
          << shape.dims.size() << " is provided";
  }
@@ -16,7 +16,7 @@
 #include <string>
 #include <vector>
-#include "absl/log/absl_check.h"
+#include "absl/log/check.h"
 #include "absl/strings/str_cat.h"
 #include "absl/strings/str_replace.h"
 #include "absl/strings/string_view.h"
@@ -12,15 +12,9 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include <cstdint>
 #include <string>
 #include <vector>
 #include "absl/log/absl_check.h"
 #include "absl/log/absl_log.h"
 #include "absl/status/status.h"
 #include "absl/status/statusor.h"
 #include "absl/strings/str_format.h"
 #include "mediapipe/calculators/tensor/tensor_converter_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/formats/image_frame.h"
@@ -28,8 +22,7 @@
 #include "mediapipe/framework/formats/tensor.h"
 #include "mediapipe/framework/port.h"
 #include "mediapipe/framework/port/ret_check.h"
-#include "mediapipe/gpu/gpu_buffer_format.h"
+#include "mediapipe/util/resource_util.h"
 #include "mediapipe/gpu/gpu_origin.pb.h"
 #if !MEDIAPIPE_DISABLE_GPU
 #include "mediapipe/gpu/gpu_buffer.h"
@@ -50,50 +43,12 @@
 #endif  // !MEDIAPIPE_DISABLE_GPU
 namespace {
 constexpr int kWorkgroupSize = 8;  // Block size for GPU shader.
 // 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;
 }
 absl::StatusOr<bool> ShouldFlipVertically(
    const mediapipe::TensorConverterCalculatorOptions& options, bool use_gpu) {
  if (options.has_flip_vertically() && options.has_gpu_origin()) {
    return absl::FailedPreconditionError(absl::StrFormat(
        "Cannot specify both flip_vertically and gpu_origin options"));
  }
  if (!options.has_gpu_origin()) {
    // Fall back to flip_vertically.
    return options.flip_vertically();
  }
  // Warn if gpu_origin is specified with a CPU input image.
  // Those are always TOP_LEFT, so no flipping is necessary.
  if (!use_gpu) {
    ABSL_LOG(WARNING)
        << "Ignoring gpu_origin option since IMAGE_GPU input is not specified";
    return false;
  }
  switch (options.gpu_origin()) {
    case mediapipe::GpuOrigin::TOP_LEFT:
      return false;
    case mediapipe::GpuOrigin::DEFAULT:
    case mediapipe::GpuOrigin::CONVENTIONAL:
      // TOP_LEFT on Metal, BOTTOM_LEFT on OpenGL.
 #ifdef __APPLE__
      return false;
 #else
      return true;
 #endif
    default:
      return absl::InvalidArgumentError(
          absl::StrFormat("Unhandled GPU origin %i", options.gpu_origin()));
  }
 }
 typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>
    RowMajorMatrixXf;
 typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::ColMajor>
@@ -103,7 +58,6 @@ constexpr char kImageFrameTag[] = "IMAGE";
 constexpr char kGpuBufferTag[] = "IMAGE_GPU";
 constexpr char kTensorsTag[] = "TENSORS";
 constexpr char kMatrixTag[] = "MATRIX";
 }  // namespace
 namespace mediapipe {
@@ -155,7 +109,7 @@ class TensorConverterCalculator : public CalculatorBase {
 private:
  absl::Status InitGpu(CalculatorContext* cc);
-  absl::Status LoadOptions(CalculatorContext* cc, bool use_gpu);
+  absl::Status LoadOptions(CalculatorContext* cc);
  template <class T>
  absl::Status NormalizeImage(const ImageFrame& image_frame,
                              bool flip_vertically, float* tensor_ptr);
@@ -191,8 +145,7 @@ absl::Status TensorConverterCalculator::GetContract(CalculatorContract* cc) {
  RET_CHECK(static_cast<int>(cc->Inputs().HasTag(kImageFrameTag)) +
                static_cast<int>(cc->Inputs().HasTag(kGpuBufferTag)) +
                static_cast<int>(cc->Inputs().HasTag(kMatrixTag)) ==
-            1)
+            1);
      << "Only one input tag of {IMAGE, IMAGE_GPU, MATRIX} may be specified";
  if (cc->Inputs().HasTag(kImageFrameTag)) {
    cc->Inputs().Tag(kImageFrameTag).Set<ImageFrame>();
@@ -220,6 +173,8 @@ absl::Status TensorConverterCalculator::GetContract(CalculatorContract* cc) {
 absl::Status TensorConverterCalculator::Open(CalculatorContext* cc) {
  cc->SetOffset(TimestampDiff(0));
  MP_RETURN_IF_ERROR(LoadOptions(cc));
 #if !MEDIAPIPE_DISABLE_GPU
  if (cc->Inputs().HasTag(kGpuBufferTag)) {
    use_gpu_ = true;
@@ -232,8 +187,6 @@ absl::Status TensorConverterCalculator::Open(CalculatorContext* cc) {
  }
 #endif  // !MEDIAPIPE_DISABLE_GPU
  MP_RETURN_IF_ERROR(LoadOptions(cc, use_gpu_));
  return absl::OkStatus();
 }
@@ -425,34 +378,23 @@ absl::Status TensorConverterCalculator::InitGpu(CalculatorContext* cc) {
  // Get input image sizes.
  const auto& input =
      cc->Inputs().Tag(kGpuBufferTag).Get<mediapipe::GpuBuffer>();
-  mediapipe::GpuBufferFormat format = input.format();
+  mediapipe::ImageFormat::Format format =
      mediapipe::ImageFormatForGpuBufferFormat(input.format());
  const bool include_alpha = (max_num_channels_ == 4);
  const bool single_channel = (max_num_channels_ == 1);
-
+  if (!(format == mediapipe::ImageFormat::GRAY8 ||
-  RET_CHECK(format == mediapipe::GpuBufferFormat::kBGRA32 ||
+        format == mediapipe::ImageFormat::SRGB ||
-            format == mediapipe::GpuBufferFormat::kRGB24 ||
+        format == mediapipe::ImageFormat::SRGBA))
-            format == mediapipe::GpuBufferFormat::kRGBA32 ||
+    RET_CHECK_FAIL() << "Unsupported GPU input format.";
-            format == mediapipe::GpuBufferFormat::kRGBAFloat128 ||
+  if (include_alpha && (format != mediapipe::ImageFormat::SRGBA))
-            format == mediapipe::GpuBufferFormat::kRGBAHalf64 ||
+    RET_CHECK_FAIL() << "Num input channels is less than desired output.";
            format == mediapipe::GpuBufferFormat::kGrayFloat32 ||
            format == mediapipe::GpuBufferFormat::kGrayHalf16 ||
            format == mediapipe::GpuBufferFormat::kOneComponent8)
      << "Unsupported GPU input format: " << static_cast<uint32_t>(format);
  if (include_alpha) {
    RET_CHECK(format == mediapipe::GpuBufferFormat::kBGRA32 ||
              format == mediapipe::GpuBufferFormat::kRGBA32 ||
              format == mediapipe::GpuBufferFormat::kRGBAFloat128 ||
              format == mediapipe::GpuBufferFormat::kRGBAHalf64)
        << "Num input channels is less than desired output, input format: "
        << static_cast<uint32_t>(format);
  }
 #if MEDIAPIPE_METAL_ENABLED
  id<MTLDevice> device = gpu_helper_.mtlDevice;
  // Shader to convert GL Texture to Metal Buffer,
  // with normalization to either: [0,1] or [-1,1].
  const std::string shader_source = absl::Substitute(
-      R"glsl(
+      R"(
  #include <metal_stdlib>
  using namespace metal;
@@ -471,7 +413,7 @@ absl::Status TensorConverterCalculator::InitGpu(CalculatorContext* cc) {
    $3  // g & b channels
    $4  // alpha channel
  }
-      )glsl",
+      )",
      /*$0=*/
      output_range_.has_value()
          ? absl::Substitute("pixel = pixel * half($0) + half($1);",
@@ -481,8 +423,8 @@ absl::Status TensorConverterCalculator::InitGpu(CalculatorContext* cc) {
      /*$1=*/max_num_channels_,
      /*$2=*/flip_vertically_ ? "(in_tex.get_height() - 1 - gid.y)" : "gid.y",
      /*$3=*/
-      single_channel ? "" : R"glsl(out_buf[linear_index + 1] = pixel.y;
+      single_channel ? "" : R"(out_buf[linear_index + 1] = pixel.y;
-                                   out_buf[linear_index + 2] = pixel.z;)glsl",
+               out_buf[linear_index + 2] = pixel.z;)",
      /*$4=*/include_alpha ? "out_buf[linear_index + 3] = pixel.w;" : "");
  NSString* library_source =
@@ -500,17 +442,17 @@ absl::Status TensorConverterCalculator::InitGpu(CalculatorContext* cc) {
  RET_CHECK(to_buffer_program_ != nil) << "Couldn't create pipeline state " <<
      [[error localizedDescription] UTF8String];
 #elif MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_30
-  MP_RETURN_IF_ERROR(
+  MP_RETURN_IF_ERROR(gpu_helper_.RunInGlContext([this, &include_alpha,
      gpu_helper_.RunInGlContext([this, &include_alpha,
 #if MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
-                                  &input,
+                                                 &input,
 #endif  // MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
-                                  &single_channel]() -> absl::Status {
+                                                 &single_channel]()
                                                    -> absl::Status {
 #if MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
-        // Shader to convert GL Texture to Shader Storage Buffer Object (SSBO),
+    // Shader to convert GL Texture to Shader Storage Buffer Object (SSBO),
-        // with normalization to either: [0,1] or [-1,1].
+    // with normalization to either: [0,1] or [-1,1].
-        const std::string shader_source = absl::Substitute(
+    const std::string shader_source = absl::Substitute(
-            R"glsl( #version 310 es
+        R"( #version 310 es
          layout(local_size_x = $0, local_size_y = $0) in;
          layout(binding = 0) uniform sampler2D input_texture;
          layout(std430, binding = 1) buffer Output {float elements[];} output_data;
@@ -524,40 +466,38 @@ absl::Status TensorConverterCalculator::InitGpu(CalculatorContext* cc) {
            output_data.elements[linear_index + 0] = pixel.x;  // r channel
            $5  // g & b channels
            $6  // alpha channel
-          })glsl",
+          })",
-            /*$0=*/kWorkgroupSize, /*$1=*/input.width(), /*$2=*/input.height(),
+        /*$0=*/kWorkgroupSize, /*$1=*/input.width(), /*$2=*/input.height(),
-            /*$3=*/
+        /*$3=*/
-            output_range_.has_value()
+        output_range_.has_value()
-                ? absl::Substitute(
+            ? absl::Substitute("pixel = pixel * float($0) + float($1);",
-                      "pixel = pixel * float($0) + float($1);",
+                               (output_range_->second - output_range_->first),
-                      (output_range_->second - output_range_->first),
+                               output_range_->first)
-                      output_range_->first)
+            : "",
-                : "",
+        /*$4=*/flip_vertically_ ? "(width_height.y - 1 - gid.y)" : "gid.y",
-            /*$4=*/flip_vertically_ ? "(width_height.y - 1 - gid.y)" : "gid.y",
+        /*$5=*/
-            /*$5=*/
+        single_channel ? ""
-            single_channel
+                       : R"(output_data.elements[linear_index + 1] = pixel.y;
-                ? ""
+                            output_data.elements[linear_index + 2] = pixel.z;)",
-                : R"glsl(output_data.elements[linear_index + 1] = pixel.y;
+        /*$6=*/
-                     output_data.elements[linear_index + 2] = pixel.z;)glsl",
+        include_alpha ? "output_data.elements[linear_index + 3] = pixel.w;"
-            /*$6=*/
+                      : "",
-            include_alpha ? "output_data.elements[linear_index + 3] = pixel.w;"
+        /*$7=*/max_num_channels_);
-                          : "",
+    GLuint shader = glCreateShader(GL_COMPUTE_SHADER);
-            /*$7=*/max_num_channels_);
+    const GLchar* sources[] = {shader_source.c_str()};
-        GLuint shader = glCreateShader(GL_COMPUTE_SHADER);
+    glShaderSource(shader, 1, sources, NULL);
-        const GLchar* sources[] = {shader_source.c_str()};
+    glCompileShader(shader);
-        glShaderSource(shader, 1, sources, NULL);
+    GLint compiled = GL_FALSE;
-        glCompileShader(shader);
+    glGetShaderiv(shader, GL_COMPILE_STATUS, &compiled);
-        GLint compiled = GL_FALSE;
+    RET_CHECK(compiled == GL_TRUE);
-        glGetShaderiv(shader, GL_COMPILE_STATUS, &compiled);
+    to_buffer_program_ = glCreateProgram();
-        RET_CHECK(compiled == GL_TRUE);
+    glAttachShader(to_buffer_program_, shader);
-        to_buffer_program_ = glCreateProgram();
+    glDeleteShader(shader);
-        glAttachShader(to_buffer_program_, shader);
+    glLinkProgram(to_buffer_program_);
        glDeleteShader(shader);
        glLinkProgram(to_buffer_program_);
 #else
-        // OpenGL ES 3.0 fragment shader Texture2d -> Texture2d conversion.
+    // OpenGL ES 3.0 fragment shader Texture2d -> Texture2d conversion.
-        const std::string shader_source = absl::Substitute(
+    const std::string shader_source = absl::Substitute(
-            R"glsl(
+        R"(
        #if __VERSION__ < 130
          #define in varying
        #endif  // __VERSION__ < 130
@@ -583,51 +523,49 @@ absl::Status TensorConverterCalculator::InitGpu(CalculatorContext* cc) {
            fragColor.r = pixel.r;  // r channel
            $3  // g & b channels
            $4  // alpha channel
-          })glsl",
+          })",
-            /*$0=*/single_channel ? "vec1" : "vec4",
+        /*$0=*/single_channel ? "vec1" : "vec4",
-            /*$1=*/
+        /*$1=*/
-            flip_vertically_
+        flip_vertically_
-                ? "vec2(sample_coordinate.x, 1.0 - sample_coordinate.y);"
+            ? "vec2(sample_coordinate.x, 1.0 - sample_coordinate.y);"
-                : "sample_coordinate;",
+            : "sample_coordinate;",
-            /*$2=*/output_range_.has_value()
+        /*$2=*/output_range_.has_value()
-                ? absl::Substitute(
+            ? absl::Substitute("pixel = pixel * float($0) + float($1);",
-                      "pixel = pixel * float($0) + float($1);",
+                               (output_range_->second - output_range_->first),
-                      (output_range_->second - output_range_->first),
+                               output_range_->first)
-                      output_range_->first)
+            : "",
-                : "",
+        /*$3=*/single_channel ? "" : R"(fragColor.g = pixel.g;
-            /*$3=*/single_channel ? "" : R"glsl(fragColor.g = pixel.g;
+                            fragColor.b = pixel.b;)",
-                                            fragColor.b = pixel.b;)glsl",
+        /*$4=*/
-            /*$4=*/
+        include_alpha ? "fragColor.a = pixel.a;"
-            include_alpha ? "fragColor.a = pixel.a;"
+                      : (single_channel ? "" : "fragColor.a = 1.0;"));
                          : (single_channel ? "" : "fragColor.a = 1.0;"));
-        const GLint attr_location[NUM_ATTRIBUTES] = {
+    const GLint attr_location[NUM_ATTRIBUTES] = {
-            ATTRIB_VERTEX,
+        ATTRIB_VERTEX,
-            ATTRIB_TEXTURE_POSITION,
+        ATTRIB_TEXTURE_POSITION,
-        };
+    };
-        const GLchar* attr_name[NUM_ATTRIBUTES] = {
+    const GLchar* attr_name[NUM_ATTRIBUTES] = {
-            "position",
+        "position",
-            "texture_coordinate",
+        "texture_coordinate",
-        };
+    };
-        // shader program and params
+    // shader program and params
-        mediapipe::GlhCreateProgram(
+    mediapipe::GlhCreateProgram(
-            mediapipe::kBasicVertexShader, shader_source.c_str(),
+        mediapipe::kBasicVertexShader, shader_source.c_str(), NUM_ATTRIBUTES,
-            NUM_ATTRIBUTES, &attr_name[0], attr_location, &to_tex2d_program_);
+        &attr_name[0], attr_location, &to_tex2d_program_);
-        RET_CHECK(to_tex2d_program_) << "Problem initializing the program.";
+    RET_CHECK(to_tex2d_program_) << "Problem initializing the program.";
-        glUseProgram(to_tex2d_program_);
+    glUseProgram(to_tex2d_program_);
-        glUniform1i(glGetUniformLocation(to_tex2d_program_, "frame"), 1);
+    glUniform1i(glGetUniformLocation(to_tex2d_program_, "frame"), 1);
-        glGenFramebuffers(1, &framebuffer_);
+    glGenFramebuffers(1, &framebuffer_);
 #endif  // MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
-        return absl::OkStatus();
+    return absl::OkStatus();
-      }));
+  }));
 #endif  // MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_30
 #endif  // !MEDIAPIPE_DISABLE_GPU
  return absl::OkStatus();
 }
-absl::Status TensorConverterCalculator::LoadOptions(CalculatorContext* cc,
+absl::Status TensorConverterCalculator::LoadOptions(CalculatorContext* cc) {
                                                    bool use_gpu) {
  // Get calculator options specified in the graph.
  const auto& options =
      cc->Options<::mediapipe::TensorConverterCalculatorOptions>();
@@ -644,7 +582,7 @@ absl::Status TensorConverterCalculator::LoadOptions(CalculatorContext* cc,
  if (options.has_output_tensor_float_range()) {
    output_range_.emplace(options.output_tensor_float_range().min(),
                          options.output_tensor_float_range().max());
-    ABSL_CHECK_GT(output_range_->second, output_range_->first);
+    CHECK_GT(output_range_->second, output_range_->first);
  }
  // Custom div and sub values.
@@ -655,16 +593,16 @@ absl::Status TensorConverterCalculator::LoadOptions(CalculatorContext* cc,
  }
  // Get y-flip mode.
-  ASSIGN_OR_RETURN(flip_vertically_, ShouldFlipVertically(options, use_gpu));
+  flip_vertically_ = options.flip_vertically();
  // Get row_major_matrix mode.
  row_major_matrix_ = options.row_major_matrix();
  // Get desired way to handle input channels.
  max_num_channels_ = options.max_num_channels();
-  ABSL_CHECK_GE(max_num_channels_, 1);
+  CHECK_GE(max_num_channels_, 1);
-  ABSL_CHECK_LE(max_num_channels_, 4);
+  CHECK_LE(max_num_channels_, 4);
-  ABSL_CHECK_NE(max_num_channels_, 2);
+  CHECK_NE(max_num_channels_, 2);
  return absl::OkStatus();
 }
@@ -3,7 +3,6 @@ syntax = "proto2";
 package mediapipe;
 import "mediapipe/framework/calculator.proto";
 import "mediapipe/gpu/gpu_origin.proto";
 // Full Example:
 //
@@ -44,16 +43,8 @@ message TensorConverterCalculatorOptions {
  // with a coordinate system where the origin is at the bottom-left corner
  // (e.g., in OpenGL) whereas the ML model expects an image with a top-left
  // origin.
  // Prefer gpu_origin over this field when using GPU input images.
  optional bool flip_vertically = 2 [default = false];
  // Determines when the input GPU image should be flipped vertically.
  // See GpuOrigin.Mode for more information.
  // Affects only IMAGE_GPU inputs.
  // If unset, falls back to flip_vertically for backwards compatibility.
  // Cannot set both gpu_origin and flip_vertically.
  optional GpuOrigin.Mode gpu_origin = 10;
  // Controls how many channels of the input image get passed through to the
  // tensor. Valid values are 1,3,4 only. Ignored for iOS GPU.
  optional int32 max_num_channels = 3 [default = 3];
@@ -12,15 +12,10 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include <cmath>
 #include <cstdint>
 #include <memory>
 #include <random>
 #include <utility>
 #include <vector>
 #include "absl/memory/memory.h"
 #include "absl/status/status.h"
 #include "absl/strings/substitute.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/calculator_runner.h"
@@ -29,10 +24,8 @@
 #include "mediapipe/framework/formats/image_frame_opencv.h"
 #include "mediapipe/framework/formats/matrix.h"
 #include "mediapipe/framework/formats/tensor.h"
 #include "mediapipe/framework/port/gmock.h"
 #include "mediapipe/framework/port/gtest.h"
 #include "mediapipe/framework/port/integral_types.h"
 #include "mediapipe/framework/port/opencv_core_inc.h"
 #include "mediapipe/framework/port/parse_text_proto.h"
 #include "mediapipe/framework/port/status_matchers.h"  // NOLINT
 #include "mediapipe/framework/tool/validate_type.h"
@@ -47,7 +40,7 @@ constexpr char kTransposeOptionsString[] =
 }  // namespace
 using RandomEngine = std::mt19937_64;
-using ::testing::HasSubstr;
+using testing::Eq;
 const uint32_t kSeed = 1234;
 const int kNumSizes = 8;
 const int sizes[kNumSizes][2] = {{1, 1}, {12, 1}, {1, 9},   {2, 2},
@@ -60,7 +53,7 @@ class TensorConverterCalculatorTest : public ::testing::Test {
                       bool row_major_matrix = false) {
    RandomEngine random(kSeed);
    std::uniform_real_distribution<> uniform_dist(0, 1.0);
-    auto matrix = std::make_unique<Matrix>();
+    auto matrix = ::absl::make_unique<Matrix>();
    matrix->resize(num_rows, num_columns);
    if (row_major_matrix) {
      for (int y = 0; y < num_rows; ++y) {
@@ -108,7 +101,7 @@ TEST_F(TensorConverterCalculatorTest, RandomMatrixColMajor) {
    tool::AddVectorSink("tensor", &graph_config, &output_packets);
    // Run the graph.
-    graph_ = std::make_unique<CalculatorGraph>();
+    graph_ = absl::make_unique<CalculatorGraph>();
    MP_ASSERT_OK(graph_->Initialize(graph_config));
    MP_ASSERT_OK(graph_->StartRun({}));
@@ -117,12 +110,12 @@ TEST_F(TensorConverterCalculatorTest, RandomMatrixColMajor) {
    // Wait until the calculator done processing.
    MP_ASSERT_OK(graph_->WaitUntilIdle());
-    ASSERT_EQ(output_packets.size(), 1);
+    EXPECT_EQ(1, output_packets.size());
    // Get and process results.
    const std::vector<Tensor>& tensor_vec =
        output_packets[0].Get<std::vector<Tensor>>();
-    ASSERT_EQ(tensor_vec.size(), 1);
+    EXPECT_EQ(1, tensor_vec.size());
    const Tensor* tensor = &tensor_vec[0];
    EXPECT_EQ(Tensor::ElementType::kFloat32, tensor->element_type());
@@ -134,7 +127,7 @@ TEST_F(TensorConverterCalculatorTest, RandomMatrixColMajor) {
    auto tensor_buffer = view.buffer<float>();
    for (int i = 0; i < num_rows * num_columns; ++i) {
      const float expected = uniform_dist(random);
-      EXPECT_FLOAT_EQ(tensor_buffer[i], expected) << "at i = " << i;
+      EXPECT_EQ(expected, tensor_buffer[i]) << "at i = " << i;
    }
    // Fully close graph at end, otherwise calculator+tensors are destroyed
@@ -170,7 +163,7 @@ TEST_F(TensorConverterCalculatorTest, RandomMatrixRowMajor) {
    tool::AddVectorSink("tensor", &graph_config, &output_packets);
    // Run the graph.
-    graph_ = std::make_unique<CalculatorGraph>();
+    graph_ = absl::make_unique<CalculatorGraph>();
    MP_ASSERT_OK(graph_->Initialize(graph_config));
    MP_ASSERT_OK(graph_->StartRun({}));
@@ -179,12 +172,12 @@ TEST_F(TensorConverterCalculatorTest, RandomMatrixRowMajor) {
    // Wait until the calculator done processing.
    MP_ASSERT_OK(graph_->WaitUntilIdle());
-    ASSERT_EQ(output_packets.size(), 1);
+    EXPECT_EQ(1, output_packets.size());
    // Get and process results.
    const std::vector<Tensor>& tensor_vec =
        output_packets[0].Get<std::vector<Tensor>>();
-    ASSERT_EQ(tensor_vec.size(), 1);
+    EXPECT_EQ(1, tensor_vec.size());
    const Tensor* tensor = &tensor_vec[0];
    EXPECT_EQ(Tensor::ElementType::kFloat32, tensor->element_type());
@@ -196,7 +189,7 @@ TEST_F(TensorConverterCalculatorTest, RandomMatrixRowMajor) {
    auto tensor_buffer = view.buffer<float>();
    for (int i = 0; i < num_rows * num_columns; ++i) {
      const float expected = uniform_dist(random);
-      EXPECT_EQ(tensor_buffer[i], expected) << "at i = " << i;
+      EXPECT_EQ(expected, tensor_buffer[i]) << "at i = " << i;
    }
    // Fully close graph at end, otherwise calculator+tensors are destroyed
@@ -234,7 +227,7 @@ TEST_F(TensorConverterCalculatorTest, CustomDivAndSub) {
  // Run the graph.
  MP_ASSERT_OK(graph.Initialize(graph_config));
  MP_ASSERT_OK(graph.StartRun({}));
-  auto input_image = std::make_unique<ImageFrame>(ImageFormat::GRAY8, 1, 1);
+  auto input_image = absl::make_unique<ImageFrame>(ImageFormat::GRAY8, 1, 1);
  cv::Mat mat = mediapipe::formats::MatView(input_image.get());
  mat.at<uint8_t>(0, 0) = 200;
  MP_ASSERT_OK(graph.AddPacketToInputStream(
@@ -246,12 +239,12 @@ TEST_F(TensorConverterCalculatorTest, CustomDivAndSub) {
  // Get and process results.
  const std::vector<Tensor>& tensor_vec =
      output_packets[0].Get<std::vector<Tensor>>();
-  ASSERT_EQ(tensor_vec.size(), 1);
+  EXPECT_EQ(1, tensor_vec.size());
  const Tensor* tensor = &tensor_vec[0];
  EXPECT_EQ(Tensor::ElementType::kFloat32, tensor->element_type());
  auto view = tensor->GetCpuReadView();
-  EXPECT_FLOAT_EQ(*view.buffer<float>(), 67.0f);
+  EXPECT_FLOAT_EQ(67.0f, *view.buffer<float>());
  // Fully close graph at end, otherwise calculator+tensors are destroyed
  // after calling WaitUntilDone().
@@ -266,29 +259,32 @@ TEST_F(TensorConverterCalculatorTest, SetOutputRange) {
  for (std::pair<float, float> range : range_values) {
    CalculatorGraph graph;
    CalculatorGraphConfig graph_config =
-        mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(absl::Substitute(
+        mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(
-            R"pb(
+            absl::Substitute(R"(
-              input_stream: "input_image"
+        input_stream: "input_image"
-              node {
+        node {
-                calculator: "TensorConverterCalculator"
+          calculator: "TensorConverterCalculator"
-                input_stream: "IMAGE:input_image"
+          input_stream: "IMAGE:input_image"
-                output_stream: "TENSORS:tensor"
+          output_stream: "TENSORS:tensor"
-                options {
+          options {
-                  [mediapipe.TensorConverterCalculatorOptions.ext] {
+            [mediapipe.TensorConverterCalculatorOptions.ext] {
-                    output_tensor_float_range { min: $0 max: $1 }
+              output_tensor_float_range {
-                  }
+                min: $0
-                }
+                max: $1
              }
-            )pb",
+            }
-            /*$0=*/range.first,
+          }
-            /*$1=*/range.second));
+        }
        )",
                             /*$0=*/range.first,
                             /*$1=*/range.second));
    std::vector<Packet> output_packets;
    tool::AddVectorSink("tensor", &graph_config, &output_packets);
    // Run the graph.
    MP_ASSERT_OK(graph.Initialize(graph_config));
    MP_ASSERT_OK(graph.StartRun({}));
-    auto input_image = std::make_unique<ImageFrame>(ImageFormat::GRAY8, 1, 1);
+    auto input_image = absl::make_unique<ImageFrame>(ImageFormat::GRAY8, 1, 1);
    cv::Mat mat = mediapipe::formats::MatView(input_image.get());
    mat.at<uint8_t>(0, 0) = 200;
    MP_ASSERT_OK(graph.AddPacketToInputStream(
@@ -296,23 +292,26 @@ TEST_F(TensorConverterCalculatorTest, SetOutputRange) {
    // Wait until the calculator finishes processing.
    MP_ASSERT_OK(graph.WaitUntilIdle());
-    ASSERT_EQ(output_packets.size(), 1);
+    EXPECT_THAT(output_packets.size(), Eq(1));
    // Get and process results.
    const std::vector<Tensor>& tensor_vec =
        output_packets[0].Get<std::vector<Tensor>>();
-    ASSERT_EQ(tensor_vec.size(), 1);
+    EXPECT_THAT(tensor_vec.size(), Eq(1));
    const Tensor* tensor = &tensor_vec[0];
    // Calculate the expected normalized value:
-    float expected_value =
+    float normalized_value =
        range.first + (200 * (range.second - range.first)) / 255.0;
-    EXPECT_EQ(tensor->element_type(), Tensor::ElementType::kFloat32);
+    EXPECT_THAT(tensor->element_type(), Eq(Tensor::ElementType::kFloat32));
    auto view = tensor->GetCpuReadView();
-    float actual_value = *view.buffer<float>();
+    float dataf = *view.buffer<float>();
-    EXPECT_FLOAT_EQ(actual_value, expected_value);
+    EXPECT_THAT(
        normalized_value,
        testing::FloatNear(dataf, 2.0f * std::abs(dataf) *
                                      std::numeric_limits<float>::epsilon()));
    // Fully close graph at end, otherwise calculator+tensors are destroyed
    // after calling WaitUntilDone().
@@ -321,153 +320,4 @@ TEST_F(TensorConverterCalculatorTest, SetOutputRange) {
  }
 }
 TEST_F(TensorConverterCalculatorTest, FlipVertically) {
  CalculatorGraph graph;
  CalculatorGraphConfig graph_config =
      mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(R"pb(
        input_stream: "input_image"
        node {
          calculator: "TensorConverterCalculator"
          input_stream: "IMAGE:input_image"
          output_stream: "TENSORS:tensor"
          options {
            [mediapipe.TensorConverterCalculatorOptions.ext] {
              flip_vertically: true
              output_tensor_float_range { min: 0 max: 255 }
            }
          }
        }
      )pb");
  std::vector<Packet> output_packets;
  tool::AddVectorSink("tensor", &graph_config, &output_packets);
  // Run the graph.
  MP_ASSERT_OK(graph.Initialize(graph_config));
  MP_ASSERT_OK(graph.StartRun({}));
  auto input_image = std::make_unique<ImageFrame>(ImageFormat::GRAY8, 1, 2);
  cv::Mat mat = mediapipe::formats::MatView(input_image.get());
  constexpr uint8_t kY0Value = 100;
  constexpr uint8_t kY1Value = 200;
  mat.at<uint8_t>(0, 0) = kY0Value;
  mat.at<uint8_t>(1, 0) = kY1Value;  // Note: y, x!
  MP_ASSERT_OK(graph.AddPacketToInputStream(
      "input_image", Adopt(input_image.release()).At(Timestamp(0))));
  // Wait until the calculator finishes processing.
  MP_ASSERT_OK(graph.WaitUntilIdle());
  ASSERT_EQ(output_packets.size(), 1);
  // Get and process results.
  const std::vector<Tensor>& tensor_vec =
      output_packets[0].Get<std::vector<Tensor>>();
  ASSERT_EQ(tensor_vec.size(), 1);
  const Tensor* tensor = &tensor_vec[0];
  EXPECT_EQ(tensor->element_type(), Tensor::ElementType::kFloat32);
  const float* dataf = tensor->GetCpuReadView().buffer<float>();
  EXPECT_EQ(static_cast<int>(roundf(dataf[0])), kY1Value);  // Y0, Y1 flipped!
  EXPECT_EQ(static_cast<int>(roundf(dataf[1])), kY0Value);
  // Fully close graph at end, otherwise calculator+tensors are destroyed
  // after calling WaitUntilDone().
  MP_ASSERT_OK(graph.CloseInputStream("input_image"));
  MP_ASSERT_OK(graph.WaitUntilDone());
 }
 TEST_F(TensorConverterCalculatorTest,
       CannotSpecifyBothFlipVerticallyAndGpuOrigin) {
  CalculatorGraph graph;
  CalculatorGraphConfig graph_config =
      mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(R"pb(
        input_stream: "input_image"
        node {
          calculator: "TensorConverterCalculator"
          input_stream: "IMAGE:input_image"
          output_stream: "TENSORS:tensor"
          options {
            [mediapipe.TensorConverterCalculatorOptions.ext] {
              flip_vertically: true
              gpu_origin: TOP_LEFT
              output_tensor_float_range { min: 0 max: 255 }
            }
          }
        }
      )pb");
  std::vector<Packet> output_packets;
  tool::AddVectorSink("tensor", &graph_config, &output_packets);
  // Run the graph.
  MP_ASSERT_OK(graph.Initialize(graph_config));
  MP_ASSERT_OK(graph.StartRun({}));
  auto input_image = std::make_unique<ImageFrame>(ImageFormat::GRAY8, 1, 1);
  MP_ASSERT_OK(graph.AddPacketToInputStream(
      "input_image", Adopt(input_image.release()).At(Timestamp(0))));
  // Processing should fail as we specified both flip_vertically and gpu_origin.
  absl::Status status = graph.WaitUntilIdle();
  EXPECT_FALSE(status.ok());
  EXPECT_THAT(status.message(), HasSubstr("flip_vertically and gpu_origin"));
  EXPECT_EQ(output_packets.size(), 0);
  // Fully close graph at end, otherwise calculator+tensors are destroyed
  // after calling WaitUntilDone().
  MP_ASSERT_OK(graph.CloseInputStream("input_image"));
  EXPECT_FALSE(graph.WaitUntilDone().ok());
 }
 TEST_F(TensorConverterCalculatorTest, GpuOriginIsIgnoredWithCpuImage) {
  CalculatorGraph graph;
  CalculatorGraphConfig graph_config =
      mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(R"pb(
        input_stream: "input_image"
        node {
          calculator: "TensorConverterCalculator"
          input_stream: "IMAGE:input_image"
          output_stream: "TENSORS:tensor"
          options {
            [mediapipe.TensorConverterCalculatorOptions.ext] {
              gpu_origin: CONVENTIONAL
              output_tensor_float_range { min: 0 max: 255 }
            }
          }
        }
      )pb");
  std::vector<Packet> output_packets;
  tool::AddVectorSink("tensor", &graph_config, &output_packets);
  // Run the graph.
  MP_ASSERT_OK(graph.Initialize(graph_config));
  MP_ASSERT_OK(graph.StartRun({}));
  auto input_image = std::make_unique<ImageFrame>(ImageFormat::GRAY8, 1, 2);
  cv::Mat mat = mediapipe::formats::MatView(input_image.get());
  constexpr uint8_t kY0Value = 100;
  constexpr uint8_t kY1Value = 200;
  mat.at<uint8_t>(0, 0) = kY0Value;
  mat.at<uint8_t>(1, 0) = kY1Value;  // Note: y, x!
  MP_ASSERT_OK(graph.AddPacketToInputStream(
      "input_image", Adopt(input_image.release()).At(Timestamp(0))));
  // Wait until the calculator finishes processing.
  MP_ASSERT_OK(graph.WaitUntilIdle());
  ASSERT_EQ(output_packets.size(), 1);
  // Get and process results.
  const std::vector<Tensor>& tensor_vec =
      output_packets[0].Get<std::vector<Tensor>>();
  ASSERT_EQ(tensor_vec.size(), 1);
  const Tensor* tensor = &tensor_vec[0];
  EXPECT_EQ(tensor->element_type(), Tensor::ElementType::kFloat32);
  const float* dataf = tensor->GetCpuReadView().buffer<float>();
  EXPECT_EQ(static_cast<int>(roundf(dataf[0])), kY0Value);  // Not flipped!
  EXPECT_EQ(static_cast<int>(roundf(dataf[1])), kY1Value);
  // Fully close graph at end, otherwise calculator+tensors are destroyed
  // after calling WaitUntilDone().
  MP_ASSERT_OK(graph.CloseInputStream("input_image"));
  MP_ASSERT_OK(graph.WaitUntilDone());
 }
 }  // namespace mediapipe
@@ -15,7 +15,6 @@
 #include <unordered_map>
 #include <vector>
 #include "absl/log/absl_log.h"
 #include "absl/strings/str_format.h"
 #include "absl/types/span.h"
 #include "mediapipe/calculators/tensor/tensors_to_detections_calculator.pb.h"
@@ -84,7 +83,7 @@ void ConvertRawValuesToAnchors(const float* raw_anchors, int num_boxes,
 void ConvertAnchorsToRawValues(const std::vector<Anchor>& anchors,
                               int num_boxes, float* raw_anchors) {
-  ABSL_CHECK_EQ(anchors.size(), num_boxes);
+  CHECK_EQ(anchors.size(), num_boxes);
  int box = 0;
  for (const auto& anchor : anchors) {
    raw_anchors[box * kNumCoordsPerBox + 0] = anchor.y_center();
@@ -330,7 +329,7 @@ absl::Status TensorsToDetectionsCalculator::Process(CalculatorContext* cc) {
    } else if (status.code() == absl::StatusCode::kFailedPrecondition) {
      // For initialization error because of hardware limitation, fallback to
      // CPU processing.
-      ABSL_LOG(WARNING) << status.message();
+      LOG(WARNING) << status.message();
    } else {
      // For other error, let the error propagates.
      return status;
@@ -669,7 +668,7 @@ absl::Status TensorsToDetectionsCalculator::ProcessGPU(
                                         output_detections));
 #else
-  ABSL_LOG(ERROR) << "GPU input on non-Android not supported yet.";
+  LOG(ERROR) << "GPU input on non-Android not supported yet.";
 #endif  // !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
  return absl::OkStatus();
 }
@@ -704,18 +703,18 @@ absl::Status TensorsToDetectionsCalculator::LoadOptions(CalculatorContext* cc) {
  num_boxes_ = options_.num_boxes();
  num_coords_ = options_.num_coords();
  box_output_format_ = GetBoxFormat(options_);
-  ABSL_CHECK_NE(options_.max_results(), 0)
+  CHECK_NE(options_.max_results(), 0)
      << "The maximum number of the top-scored detection results must be "
         "non-zero.";
  max_results_ = options_.max_results();
  // Currently only support 2D when num_values_per_keypoint equals to 2.
-  ABSL_CHECK_EQ(options_.num_values_per_keypoint(), 2);
+  CHECK_EQ(options_.num_values_per_keypoint(), 2);
  // Check if the output size is equal to the requested boxes and keypoints.
-  ABSL_CHECK_EQ(options_.num_keypoints() * options_.num_values_per_keypoint() +
+  CHECK_EQ(options_.num_keypoints() * options_.num_values_per_keypoint() +
-                    kNumCoordsPerBox,
+               kNumCoordsPerBox,
-                num_coords_);
+           num_coords_);
  if (kSideInIgnoreClasses(cc).IsConnected()) {
    RET_CHECK(!kSideInIgnoreClasses(cc).IsEmpty());
@@ -1155,12 +1154,11 @@ void main() {
    }
    // TODO support better filtering.
    if (class_index_set_.is_allowlist) {
-      ABSL_CHECK_EQ(class_index_set_.values.size(),
+      CHECK_EQ(class_index_set_.values.size(),
-                    IsClassIndexAllowed(0) ? num_classes_ : num_classes_ - 1)
+               IsClassIndexAllowed(0) ? num_classes_ : num_classes_ - 1)
          << "Only all classes  >= class 0  or  >= class 1";
    } else {
-      ABSL_CHECK_EQ(class_index_set_.values.size(),
+      CHECK_EQ(class_index_set_.values.size(), IsClassIndexAllowed(0) ? 0 : 1)
                    IsClassIndexAllowed(0) ? 0 : 1)
          << "Only ignore class 0 is allowed";
    }
@@ -1381,12 +1379,11 @@ kernel void scoreKernel(
  // TODO support better filtering.
  if (class_index_set_.is_allowlist) {
-    ABSL_CHECK_EQ(class_index_set_.values.size(),
+    CHECK_EQ(class_index_set_.values.size(),
-                  IsClassIndexAllowed(0) ? num_classes_ : num_classes_ - 1)
+             IsClassIndexAllowed(0) ? num_classes_ : num_classes_ - 1)
        << "Only all classes  >= class 0  or  >= class 1";
  } else {
-    ABSL_CHECK_EQ(class_index_set_.values.size(),
+    CHECK_EQ(class_index_set_.values.size(), IsClassIndexAllowed(0) ? 0 : 1)
                  IsClassIndexAllowed(0) ? 0 : 1)
        << "Only ignore class 0 is allowed";
  }
@@ -142,7 +142,7 @@ absl::Status TensorsToLandmarksCalculator::Process(CalculatorContext* cc) {
  RET_CHECK(input_tensors[0].element_type() == Tensor::ElementType::kFloat32);
  int num_values = input_tensors[0].shape().num_elements();
  const int num_dimensions = num_values / num_landmarks_;
-  ABSL_CHECK_GT(num_dimensions, 0);
+  CHECK_GT(num_dimensions, 0);
  auto view = input_tensors[0].GetCpuReadView();
  auto raw_landmarks = view.buffer<float>();
@@ -13,7 +13,6 @@
 # limitations under the License.
 #
 # Placeholder: load py_proto_library
 load("//mediapipe/framework/port:build_config.bzl", "mediapipe_cc_proto_library", "mediapipe_proto_library")
 licenses(["notice"])
@@ -315,7 +314,6 @@ cc_library(
        "//mediapipe/framework/formats:time_series_header_cc_proto",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_check",
    ] + select({
        "//conditions:default": [
            "@org_tensorflow//tensorflow/core:framework",
@@ -368,18 +366,18 @@ cc_library(
    name = "pack_media_sequence_calculator",
    srcs = ["pack_media_sequence_calculator.cc"],
    deps = [
        ":pack_media_sequence_calculator_cc_proto",
        "//mediapipe/calculators/image:opencv_image_encoder_calculator_cc_proto",
        "//mediapipe/calculators/tensorflow:pack_media_sequence_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/formats:detection_cc_proto",
        "//mediapipe/framework/formats:location",
        "//mediapipe/framework/formats:location_opencv",
        "//mediapipe/framework/port:opencv_imgcodecs",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "//mediapipe/util/sequence:media_sequence",
        "//mediapipe/util/sequence:media_sequence_util",
        "@com_google_absl//absl/container:flat_hash_map",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/strings",
        "@org_tensorflow//tensorflow/core:protos_all_cc",
    ],
@@ -408,13 +406,8 @@ cc_library(
    alwayslink = 1,
 )
-# This dependency removed the following 3 targets because they failed Boq conformance test:
+# This dependency removed tensorflow_jellyfish_deps and xprofilez_with_server because they failed
-#
+# Boq conformance test. Weigh your use case to see if this will work for you.
 # tensorflow_jellyfish_deps
 # jfprof_lib
 # xprofilez_with_server
 #
 # If you need them plz consider tensorflow_inference_calculator_no_envelope_loader.
 cc_library(
    name = "tensorflow_inference_calculator_for_boq",
    srcs = ["tensorflow_inference_calculator.cc"],
@@ -431,7 +424,7 @@ cc_library(
        "//mediapipe/framework/port:status",
        "//mediapipe/framework/tool:status_util",
        "@com_google_absl//absl/base:core_headers",
-        "@com_google_absl//absl/log:absl_check",
+        "@com_google_absl//absl/log:check",
        "@com_google_absl//absl/memory",
        "@com_google_absl//absl/strings",
        "@com_google_absl//absl/synchronization",
@@ -490,10 +483,10 @@ cc_library(
        "//mediapipe/calculators/tensorflow:tensorflow_session_from_frozen_graph_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/deps:clock",
        "//mediapipe/framework/port:logging",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "//mediapipe/framework/tool:status_util",
        "@com_google_absl//absl/log:absl_log",
        "@org_tensorflow//tensorflow/core:protos_all_cc",
    ] + select({
        "//conditions:default": [
@@ -521,10 +514,10 @@ cc_library(
        ":tensorflow_session_from_frozen_graph_generator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/deps:clock",
        "//mediapipe/framework/port:logging",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "//mediapipe/framework/tool:status_util",
        "@com_google_absl//absl/log:absl_log",
        "@org_tensorflow//tensorflow/core:protos_all_cc",
    ] + select({
        "//conditions:default": [
@@ -557,7 +550,6 @@ cc_library(
        "//mediapipe/framework/deps:file_path",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_absl//absl/strings",
        "@org_tensorflow//tensorflow/cc/saved_model:constants",
        "@org_tensorflow//tensorflow/cc/saved_model:loader_lite",
@@ -635,7 +627,6 @@ cc_library(
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "//mediapipe/framework/tool:status_util",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/strings",
        "@org_tensorflow//tensorflow/cc/saved_model:constants",
@@ -657,7 +648,6 @@ cc_library(
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_log",
        "@org_tensorflow//tensorflow/core:framework",
    ],
    alwayslink = 1,
@@ -672,7 +662,6 @@ cc_library(
        "//mediapipe/framework/formats:image_frame",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_check",
        "@org_tensorflow//tensorflow/core:framework",
    ],
    alwayslink = 1,
@@ -688,7 +677,6 @@ cc_library(
        "//mediapipe/framework/formats:time_series_header_cc_proto",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_check",
    ] + select({
        "//conditions:default": [
            "@org_tensorflow//tensorflow/core:framework",
@@ -723,7 +711,6 @@ cc_library(
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "@org_tensorflow//tensorflow/core/platform:bfloat16",
    ] + select({
        "//conditions:default": [
            "@org_tensorflow//tensorflow/core:framework",
@@ -786,7 +773,6 @@ cc_library(
        "//mediapipe/framework/port:status",
        "//mediapipe/util:audio_decoder_cc_proto",
        "//mediapipe/util/sequence:media_sequence",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_absl//absl/strings",
        "@org_tensorflow//tensorflow/core:protos_all_cc",
    ],
@@ -801,8 +787,6 @@ cc_library(
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/log:absl_log",
        "@org_tensorflow//tensorflow/core:framework",
    ],
    alwayslink = 1,
@@ -816,7 +800,6 @@ cc_library(
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_log",
        "@org_tensorflow//tensorflow/core:framework",
    ],
    alwayslink = 1,
@@ -830,7 +813,6 @@ cc_library(
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_log",
        "@org_tensorflow//tensorflow/core:framework",
    ],
    alwayslink = 1,
@@ -844,8 +826,6 @@ cc_library(
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:packet",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/log:absl_log",
        "@org_tensorflow//tensorflow/core:protos_all_cc",
    ],
    alwayslink = 1,
@@ -940,24 +920,22 @@ cc_test(
    srcs = ["pack_media_sequence_calculator_test.cc"],
    deps = [
        ":pack_media_sequence_calculator",
        ":pack_media_sequence_calculator_cc_proto",
        "//mediapipe/calculators/image:opencv_image_encoder_calculator_cc_proto",
        "//mediapipe/calculators/tensorflow:pack_media_sequence_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:calculator_runner",
        "//mediapipe/framework:packet",
        "//mediapipe/framework:timestamp",
        "//mediapipe/framework/formats:detection_cc_proto",
        "//mediapipe/framework/formats:image_frame",
        "//mediapipe/framework/formats:image_frame_opencv",
        "//mediapipe/framework/formats:location",
        "//mediapipe/framework/formats:location_opencv",
        "//mediapipe/framework/port:gtest_main",
        "//mediapipe/framework/port:opencv_imgcodecs",
        "//mediapipe/util/sequence:media_sequence",
-        "//mediapipe/util/sequence:media_sequence_util",
+        "@com_google_absl//absl/container:flat_hash_map",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/memory",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/strings",
        "@com_google_googletest//:gtest_main",
        "@org_tensorflow//tensorflow/core:protos_all_cc",
    ],
 )
@@ -1140,7 +1118,6 @@ cc_test(
        "//mediapipe/util:packet_test_util",
        "@org_tensorflow//tensorflow/core:framework",
        "@org_tensorflow//tensorflow/core:protos_all_cc",
        "@org_tensorflow//tensorflow/core/platform:bfloat16",
    ],
 )
@@ -1186,7 +1163,6 @@ cc_test(
        "//mediapipe/framework/port:rectangle",
        "//mediapipe/util:audio_decoder_cc_proto",
        "//mediapipe/util/sequence:media_sequence",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_absl//absl/memory",
        "@com_google_absl//absl/strings",
        "@org_tensorflow//tensorflow/core:protos_all_cc",
@@ -1268,8 +1244,6 @@ cc_test(
        "//mediapipe/framework/tool:sink",
        "//mediapipe/framework/tool:validate_type",
        "@com_google_absl//absl/flags:flag",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/log:absl_log",
    ] + select({
        "//conditions:default": [
            "@org_tensorflow//tensorflow/core:direct_session",
@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "absl/log/absl_check.h"
 #include "mediapipe/calculators/tensorflow/matrix_to_tensor_calculator_options.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/formats/matrix.h"
@@ -29,7 +28,7 @@ namespace mediapipe {
 namespace {
 absl::Status FillTimeSeriesHeaderIfValid(const Packet& header_packet,
                                         TimeSeriesHeader* header) {
-  ABSL_CHECK(header);
+  CHECK(header);
  if (header_packet.IsEmpty()) {
    return absl::UnknownError("No header found.");
  }
@@ -12,23 +12,21 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include <cstdint>
 #include <optional>
 #include <string>
 #include <vector>
 #include "absl/container/flat_hash_map.h"
 #include "absl/status/status.h"
 #include "absl/strings/match.h"
 #include "absl/strings/strip.h"
 #include "mediapipe/calculators/image/opencv_image_encoder_calculator.pb.h"
 #include "mediapipe/calculators/tensorflow/pack_media_sequence_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/formats/detection.pb.h"
 #include "mediapipe/framework/formats/location.h"
 #include "mediapipe/framework/formats/location_opencv.h"
 #include "mediapipe/framework/port/canonical_errors.h"
 #include "mediapipe/framework/port/opencv_imgcodecs_inc.h"
 #include "mediapipe/framework/port/ret_check.h"
 #include "mediapipe/framework/port/status.h"
 #include "mediapipe/util/sequence/media_sequence.h"
 #include "mediapipe/util/sequence/media_sequence_util.h"
 #include "tensorflow/core/example/example.pb.h"
@@ -38,11 +36,7 @@ namespace mediapipe {
 const char kSequenceExampleTag[] = "SEQUENCE_EXAMPLE";
 const char kImageTag[] = "IMAGE";
 const char kImageLabelPrefixTag[] = "IMAGE_LABEL_";
 const char kClipLabelPrefixTag[] = "CLIP_LABEL_";
 const char kFloatContextFeaturePrefixTag[] = "FLOAT_CONTEXT_FEATURE_";
 const char kIntsContextFeaturePrefixTag[] = "INTS_CONTEXT_FEATURE_";
 const char kBytesContextFeaturePrefixTag[] = "BYTES_CONTEXT_FEATURE_";
 const char kFloatFeaturePrefixTag[] = "FLOAT_FEATURE_";
 const char kIntFeaturePrefixTag[] = "INT_FEATURE_";
 const char kBytesFeaturePrefixTag[] = "BYTES_FEATURE_";
@@ -50,7 +44,6 @@ const char kForwardFlowEncodedTag[] = "FORWARD_FLOW_ENCODED";
 const char kBBoxTag[] = "BBOX";
 const char kKeypointsTag[] = "KEYPOINTS";
 const char kSegmentationMaskTag[] = "CLASS_SEGMENTATION";
 const char kClipMediaIdTag[] = "CLIP_MEDIA_ID";
 namespace tf = ::tensorflow;
 namespace mpms = mediapipe::mediasequence;
@@ -62,23 +55,16 @@ namespace mpms = mediapipe::mediasequence;
 // context features can be supplied verbatim in the calculator's options. The
 // SequenceExample will conform to the description in media_sequence.h.
 //
-// The supported input stream tags are:
+// The supported input stream tags are "IMAGE", which stores the encoded
-// * "IMAGE", which stores the encoded images from the
+// images from the OpenCVImageEncoderCalculator, "FORWARD_FLOW_ENCODED", which
-//   OpenCVImageEncoderCalculator,
+// stores the encoded optical flow from the same calculator, "BBOX" which stores
-// * "IMAGE_LABEL", which stores whole image labels from Detection,
+// bounding boxes from vector<Detections>, and streams with the
-// * "FORWARD_FLOW_ENCODED", which stores the encoded optical flow from the same
+// "FLOAT_FEATURE_${NAME}" pattern, which stores the values from vector<float>'s
-//   calculator,
+// associated with the name ${NAME}. "KEYPOINTS" stores a map of 2D keypoints
-// * "BBOX" which stores bounding boxes from vector<Detections>,
+// from flat_hash_map<string, vector<pair<float, float>>>. "IMAGE_${NAME}",
-// * streams with the "FLOAT_FEATURE_${NAME}" pattern, which stores the values
+// "BBOX_${NAME}", and "KEYPOINTS_${NAME}" will also store prefixed versions of
-//   from vector<float>'s associated with the name ${NAME},
+// each stream, which allows for multiple image streams to be included. However,
-// * "KEYPOINTS" stores a map of 2D keypoints from flat_hash_map<string,
+// the default names are suppored by more tools.
 //   vector<pair<float, float>>>,
 // * "CLIP_MEDIA_ID", which stores the clip's media ID as a string.
 // * "CLIP_LABEL_${NAME}" which stores sparse feature labels, ID and scores in
 //   mediapipe::Detection.
 // "IMAGE_${NAME}", "BBOX_${NAME}", and "KEYPOINTS_${NAME}" will also store
 // prefixed versions of each stream, which allows for multiple image streams to
 // be included. However, the default names are suppored by more tools.
 //
 // Example config:
 // node {
@@ -114,9 +100,6 @@ class PackMediaSequenceCalculator : public CalculatorBase {
  static absl::Status GetContract(CalculatorContract* cc) {
    RET_CHECK(cc->InputSidePackets().HasTag(kSequenceExampleTag));
    cc->InputSidePackets().Tag(kSequenceExampleTag).Set<tf::SequenceExample>();
    if (cc->InputSidePackets().HasTag(kClipMediaIdTag)) {
      cc->InputSidePackets().Tag(kClipMediaIdTag).Set<std::string>();
    }
    if (cc->Inputs().HasTag(kForwardFlowEncodedTag)) {
      cc->Inputs()
@@ -129,10 +112,6 @@ class PackMediaSequenceCalculator : public CalculatorBase {
    for (const auto& tag : cc->Inputs().GetTags()) {
      if (absl::StartsWith(tag, kImageTag)) {
        if (absl::StartsWith(tag, kImageLabelPrefixTag)) {
          cc->Inputs().Tag(tag).Set<Detection>();
          continue;
        }
        std::string key = "";
        if (tag != kImageTag) {
          int tag_length = sizeof(kImageTag) / sizeof(*kImageTag) - 1;
@@ -171,18 +150,9 @@ class PackMediaSequenceCalculator : public CalculatorBase {
        }
        cc->Inputs().Tag(tag).Set<std::vector<Detection>>();
      }
      if (absl::StartsWith(tag, kClipLabelPrefixTag)) {
        cc->Inputs().Tag(tag).Set<Detection>();
      }
      if (absl::StartsWith(tag, kFloatContextFeaturePrefixTag)) {
        cc->Inputs().Tag(tag).Set<std::vector<float>>();
      }
      if (absl::StartsWith(tag, kIntsContextFeaturePrefixTag)) {
        cc->Inputs().Tag(tag).Set<std::vector<int64_t>>();
      }
      if (absl::StartsWith(tag, kBytesContextFeaturePrefixTag)) {
        cc->Inputs().Tag(tag).Set<std::vector<std::string>>();
      }
      if (absl::StartsWith(tag, kFloatFeaturePrefixTag)) {
        cc->Inputs().Tag(tag).Set<std::vector<float>>();
      }
@@ -194,8 +164,8 @@ class PackMediaSequenceCalculator : public CalculatorBase {
      }
    }
-    RET_CHECK(cc->Outputs().HasTag(kSequenceExampleTag) ||
+    CHECK(cc->Outputs().HasTag(kSequenceExampleTag) ||
-              cc->OutputSidePackets().HasTag(kSequenceExampleTag))
+          cc->OutputSidePackets().HasTag(kSequenceExampleTag))
        << "Neither the output stream nor the output side packet is set to "
           "output the sequence example.";
    if (cc->Outputs().HasTag(kSequenceExampleTag)) {
@@ -214,11 +184,6 @@ class PackMediaSequenceCalculator : public CalculatorBase {
        cc->InputSidePackets()
            .Tag(kSequenceExampleTag)
            .Get<tf::SequenceExample>());
    if (cc->InputSidePackets().HasTag(kClipMediaIdTag) &&
        !cc->InputSidePackets().Tag(kClipMediaIdTag).IsEmpty()) {
      clip_media_id_ =
          cc->InputSidePackets().Tag(kClipMediaIdTag).Get<std::string>();
    }
    const auto& context_features =
        cc->Options<PackMediaSequenceCalculatorOptions>().context_feature_map();
@@ -232,19 +197,8 @@ class PackMediaSequenceCalculator : public CalculatorBase {
    replace_keypoints_ = false;
    if (cc->Options<PackMediaSequenceCalculatorOptions>()
            .replace_data_instead_of_append()) {
      // Clear the existing values under the same key.
      for (const auto& tag : cc->Inputs().GetTags()) {
        if (absl::StartsWith(tag, kImageTag)) {
          if (absl::StartsWith(tag, kImageLabelPrefixTag)) {
            std::string key =
                std::string(absl::StripPrefix(tag, kImageLabelPrefixTag));
            mpms::ClearImageLabelString(key, sequence_.get());
            mpms::ClearImageLabelConfidence(key, sequence_.get());
            if (!key.empty() || mpms::HasImageEncoded(*sequence_)) {
              mpms::ClearImageTimestamp(key, sequence_.get());
            }
            continue;
          }
          std::string key = "";
          if (tag != kImageTag) {
            int tag_length = sizeof(kImageTag) / sizeof(*kImageTag) - 1;
@@ -273,41 +227,12 @@ class PackMediaSequenceCalculator : public CalculatorBase {
          mpms::ClearBBoxNumRegions(key, sequence_.get());
          mpms::ClearBBoxLabelString(key, sequence_.get());
          mpms::ClearBBoxLabelIndex(key, sequence_.get());
          mpms::ClearBBoxLabelConfidence(key, sequence_.get());
          mpms::ClearBBoxClassString(key, sequence_.get());
          mpms::ClearBBoxClassIndex(key, sequence_.get());
          mpms::ClearBBoxTrackString(key, sequence_.get());
          mpms::ClearBBoxTrackIndex(key, sequence_.get());
          mpms::ClearUnmodifiedBBoxTimestamp(key, sequence_.get());
        }
        if (absl::StartsWith(tag, kClipLabelPrefixTag)) {
          const std::string& key = tag.substr(
              sizeof(kClipLabelPrefixTag) / sizeof(*kClipLabelPrefixTag) - 1);
          mpms::ClearClipLabelIndex(key, sequence_.get());
          mpms::ClearClipLabelString(key, sequence_.get());
          mpms::ClearClipLabelConfidence(key, sequence_.get());
        }
        if (absl::StartsWith(tag, kFloatContextFeaturePrefixTag)) {
          const std::string& key =
              tag.substr(sizeof(kFloatContextFeaturePrefixTag) /
                             sizeof(*kFloatContextFeaturePrefixTag) -
                         1);
          mpms::ClearContextFeatureFloats(key, sequence_.get());
        }
        if (absl::StartsWith(tag, kIntsContextFeaturePrefixTag)) {
          const std::string& key =
              tag.substr(sizeof(kIntsContextFeaturePrefixTag) /
                             sizeof(*kIntsContextFeaturePrefixTag) -
                         1);
          mpms::ClearContextFeatureInts(key, sequence_.get());
        }
        if (absl::StartsWith(tag, kBytesContextFeaturePrefixTag)) {
          const std::string& key =
              tag.substr(sizeof(kBytesContextFeaturePrefixTag) /
                             sizeof(*kBytesContextFeaturePrefixTag) -
                         1);
          mpms::ClearContextFeatureBytes(key, sequence_.get());
        }
        if (absl::StartsWith(tag, kFloatFeaturePrefixTag)) {
          std::string key = tag.substr(sizeof(kFloatFeaturePrefixTag) /
                                           sizeof(*kFloatFeaturePrefixTag) -
@@ -418,34 +343,6 @@ class PackMediaSequenceCalculator : public CalculatorBase {
      if (absl::StartsWith(tag, kImageTag) &&
          !cc->Inputs().Tag(tag).IsEmpty()) {
        std::string key = "";
        if (absl::StartsWith(tag, kImageLabelPrefixTag)) {
          std::string key =
              std::string(absl::StripPrefix(tag, kImageLabelPrefixTag));
          const auto& detection = cc->Inputs().Tag(tag).Get<Detection>();
          if (detection.label().empty()) continue;
          RET_CHECK(detection.label_size() == detection.score_size())
              << "Wrong image label data format: " << detection.label_size()
              << " vs " << detection.score_size();
          if (!detection.label_id().empty()) {
            RET_CHECK(detection.label_id_size() == detection.label_size())
                << "Wrong image label ID format: " << detection.label_id_size()
                << " vs " << detection.label_size();
          }
          std::vector<std::string> labels(detection.label().begin(),
                                          detection.label().end());
          std::vector<float> confidences(detection.score().begin(),
                                         detection.score().end());
          std::vector<int32_t> ids(detection.label_id().begin(),
                                   detection.label_id().end());
          if (!key.empty() || mpms::HasImageEncoded(*sequence_)) {
            mpms::AddImageTimestamp(key, cc->InputTimestamp().Value(),
                                    sequence_.get());
          }
          mpms::AddImageLabelString(key, labels, sequence_.get());
          mpms::AddImageLabelConfidence(key, confidences, sequence_.get());
          if (!ids.empty()) mpms::AddImageLabelIndex(key, ids, sequence_.get());
          continue;
        }
        if (tag != kImageTag) {
          int tag_length = sizeof(kImageTag) / sizeof(*kImageTag) - 1;
          if (tag[tag_length] == '_') {
@@ -496,7 +393,6 @@ class PackMediaSequenceCalculator : public CalculatorBase {
            mpms::ClearBBoxNumRegions(prefix, sequence_.get());
            mpms::ClearBBoxLabelString(prefix, sequence_.get());
            mpms::ClearBBoxLabelIndex(prefix, sequence_.get());
            mpms::ClearBBoxLabelConfidence(prefix, sequence_.get());
            mpms::ClearBBoxClassString(prefix, sequence_.get());
            mpms::ClearBBoxClassIndex(prefix, sequence_.get());
            mpms::ClearBBoxTrackString(prefix, sequence_.get());
@@ -509,33 +405,6 @@ class PackMediaSequenceCalculator : public CalculatorBase {
        }
        replace_keypoints_ = false;
      }
      if (absl::StartsWith(tag, kClipLabelPrefixTag) &&
          !cc->Inputs().Tag(tag).IsEmpty()) {
        const std::string& key = tag.substr(
            sizeof(kClipLabelPrefixTag) / sizeof(*kClipLabelPrefixTag) - 1);
        const Detection& detection = cc->Inputs().Tag(tag).Get<Detection>();
        if (detection.label().size() != detection.score().size()) {
          return absl::InvalidArgumentError(
              "Different size of detection.label and detection.score");
        }
        // Allow empty label_ids, but if label_ids is not empty, it should have
        // the same size as the label and score fields.
        if (!detection.label_id().empty()) {
          if (detection.label_id().size() != detection.label().size()) {
            return absl::InvalidArgumentError(
                "Different size of detection.label_id and detection.label");
          }
        }
        for (int i = 0; i < detection.label().size(); ++i) {
          if (!detection.label_id().empty()) {
            mpms::AddClipLabelIndex(key, detection.label_id(i),
                                    sequence_.get());
          }
          mpms::AddClipLabelString(key, detection.label(i), sequence_.get());
          mpms::AddClipLabelConfidence(key, detection.score(i),
                                       sequence_.get());
        }
      }
      if (absl::StartsWith(tag, kFloatContextFeaturePrefixTag) &&
          !cc->Inputs().Tag(tag).IsEmpty()) {
        std::string key =
@@ -543,36 +412,9 @@ class PackMediaSequenceCalculator : public CalculatorBase {
                           sizeof(*kFloatContextFeaturePrefixTag) -
                       1);
        RET_CHECK_EQ(cc->InputTimestamp(), Timestamp::PostStream());
-        for (const auto& value :
+        mpms::SetContextFeatureFloats(
-             cc->Inputs().Tag(tag).Get<std::vector<float>>()) {
+            key, cc->Inputs().Tag(tag).Get<std::vector<float>>(),
-          mpms::AddContextFeatureFloats(key, value, sequence_.get());
+            sequence_.get());
        }
      }
      if (absl::StartsWith(tag, kIntsContextFeaturePrefixTag) &&
          !cc->Inputs().Tag(tag).IsEmpty()) {
        const std::string& key =
            tag.substr(sizeof(kIntsContextFeaturePrefixTag) /
                           sizeof(*kIntsContextFeaturePrefixTag) -
                       1);
        // To ensure only one packet is provided for this tag.
        RET_CHECK_EQ(cc->InputTimestamp(), Timestamp::PostStream());
        for (const auto& value :
             cc->Inputs().Tag(tag).Get<std::vector<int64_t>>()) {
          mpms::AddContextFeatureInts(key, value, sequence_.get());
        }
      }
      if (absl::StartsWith(tag, kBytesContextFeaturePrefixTag) &&
          !cc->Inputs().Tag(tag).IsEmpty()) {
        const std::string& key =
            tag.substr(sizeof(kBytesContextFeaturePrefixTag) /
                           sizeof(*kBytesContextFeaturePrefixTag) -
                       1);
        // To ensure only one packet is provided for this tag.
        RET_CHECK_EQ(cc->InputTimestamp(), Timestamp::PostStream());
        for (const auto& value :
             cc->Inputs().Tag(tag).Get<std::vector<std::string>>()) {
          mpms::AddContextFeatureBytes(key, value, sequence_.get());
        }
      }
      if (absl::StartsWith(tag, kFloatFeaturePrefixTag) &&
          !cc->Inputs().Tag(tag).IsEmpty()) {
@@ -618,7 +460,6 @@ class PackMediaSequenceCalculator : public CalculatorBase {
        }
        std::vector<Location> predicted_locations;
        std::vector<std::string> predicted_class_strings;
        std::vector<float> predicted_class_confidences;
        std::vector<int> predicted_label_ids;
        for (auto& detection :
             cc->Inputs().Tag(tag).Get<std::vector<Detection>>()) {
@@ -647,9 +488,6 @@ class PackMediaSequenceCalculator : public CalculatorBase {
            if (detection.label_id_size() > 0) {
              predicted_label_ids.push_back(detection.label_id(0));
            }
            if (detection.score_size() > 0) {
              predicted_class_confidences.push_back(detection.score(0));
            }
          }
        }
        if (!predicted_locations.empty()) {
@@ -663,10 +501,6 @@ class PackMediaSequenceCalculator : public CalculatorBase {
          if (!predicted_label_ids.empty()) {
            mpms::AddBBoxLabelIndex(key, predicted_label_ids, sequence_.get());
          }
          if (!predicted_class_confidences.empty()) {
            mpms::AddBBoxLabelConfidence(key, predicted_class_confidences,
                                         sequence_.get());
          }
        }
      }
    }
@@ -714,14 +548,10 @@ class PackMediaSequenceCalculator : public CalculatorBase {
        }
      }
    }
    if (clip_media_id_.has_value()) {
      mpms::SetClipMediaId(*clip_media_id_, sequence_.get());
    }
    return absl::OkStatus();
  }
  std::unique_ptr<tf::SequenceExample> sequence_;
  std::optional<std::string> clip_media_id_ = std::nullopt;
  std::map<std::string, bool> features_present_;
  bool replace_keypoints_;
 };
@@ -12,32 +12,28 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
-#include <cstdint>
+#include <algorithm>
 #include <memory>
 #include <string>
 #include <vector>
-#include "absl/log/absl_check.h"
+#include "absl/container/flat_hash_map.h"
 #include "absl/memory/memory.h"
-#include "absl/status/status.h"
+#include "absl/strings/numbers.h"
 #include "absl/strings/str_cat.h"
 #include "mediapipe/calculators/image/opencv_image_encoder_calculator.pb.h"
 #include "mediapipe/calculators/tensorflow/pack_media_sequence_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/calculator_runner.h"
 #include "mediapipe/framework/formats/detection.pb.h"
 #include "mediapipe/framework/formats/image_frame.h"
 #include "mediapipe/framework/formats/image_frame_opencv.h"
 #include "mediapipe/framework/formats/location.h"
 #include "mediapipe/framework/formats/location_opencv.h"
-#include "mediapipe/framework/packet.h"
+#include "mediapipe/framework/port/gmock.h"
 #include "mediapipe/framework/port/gtest.h"
 #include "mediapipe/framework/port/opencv_imgcodecs_inc.h"
 #include "mediapipe/framework/port/status_matchers.h"
 #include "mediapipe/framework/timestamp.h"
 #include "mediapipe/util/sequence/media_sequence.h"
 #include "mediapipe/util/sequence/media_sequence_util.h"
 #include "tensorflow/core/example/example.pb.h"
 #include "tensorflow/core/example/feature.pb.h"
 #include "testing/base/public/gmock.h"
 #include "testing/base/public/gunit.h"
 namespace mediapipe {
 namespace {
@@ -59,22 +55,13 @@ constexpr char kBytesFeatureTestTag[] = "BYTES_FEATURE_TEST";
 constexpr char kForwardFlowEncodedTag[] = "FORWARD_FLOW_ENCODED";
 constexpr char kFloatContextFeatureOtherTag[] = "FLOAT_CONTEXT_FEATURE_OTHER";
 constexpr char kFloatContextFeatureTestTag[] = "FLOAT_CONTEXT_FEATURE_TEST";
 constexpr char kIntsContextFeatureTestTag[] = "INTS_CONTEXT_FEATURE_TEST";
 constexpr char kIntsContextFeatureOtherTag[] = "INTS_CONTEXT_FEATURE_OTHER";
 constexpr char kBytesContextFeatureTestTag[] = "BYTES_CONTEXT_FEATURE_TEST";
 constexpr char kBytesContextFeatureOtherTag[] = "BYTES_CONTEXT_FEATURE_OTHER";
 constexpr char kFloatFeatureOtherTag[] = "FLOAT_FEATURE_OTHER";
 constexpr char kFloatFeatureTestTag[] = "FLOAT_FEATURE_TEST";
 constexpr char kIntFeatureOtherTag[] = "INT_FEATURE_OTHER";
 constexpr char kIntFeatureTestTag[] = "INT_FEATURE_TEST";
 constexpr char kImageLabelTestTag[] = "IMAGE_LABEL_TEST";
 constexpr char kImageLabelOtherTag[] = "IMAGE_LABEL_OTHER";
 constexpr char kImagePrefixTag[] = "IMAGE_PREFIX";
 constexpr char kSequenceExampleTag[] = "SEQUENCE_EXAMPLE";
 constexpr char kImageTag[] = "IMAGE";
 constexpr char kClipMediaIdTag[] = "CLIP_MEDIA_ID";
 constexpr char kClipLabelTestTag[] = "CLIP_LABEL_TEST";
 constexpr char kClipLabelOtherTag[] = "CLIP_LABEL_OTHER";
 class PackMediaSequenceCalculatorTest : public ::testing::Test {
 protected:
@@ -82,14 +69,10 @@ class PackMediaSequenceCalculatorTest : public ::testing::Test {
                       const tf::Features& features,
                       const bool output_only_if_all_present,
                       const bool replace_instead_of_append,
-                       const bool output_as_zero_timestamp = false,
+                       const bool output_as_zero_timestamp = false) {
                       const std::vector<std::string>& input_side_packets = {
                           "SEQUENCE_EXAMPLE:input_sequence"}) {
    CalculatorGraphConfig::Node config;
    config.set_calculator("PackMediaSequenceCalculator");
-    for (const std::string& side_packet : input_side_packets) {
+    config.add_input_side_packet("SEQUENCE_EXAMPLE:input_sequence");
      config.add_input_side_packet(side_packet);
    }
    config.add_output_stream("SEQUENCE_EXAMPLE:output_sequence");
    for (const std::string& stream : input_streams) {
      config.add_input_stream(stream);
@@ -113,8 +96,7 @@ TEST_F(PackMediaSequenceCalculatorTest, PacksTwoImages) {
  mpms::SetClipMediaId(test_video_id, input_sequence.get());
  cv::Mat image(2, 3, CV_8UC3, cv::Scalar(0, 0, 255));
  std::vector<uchar> bytes;
-  ASSERT_TRUE(
+  ASSERT_TRUE(cv::imencode(".jpg", image, bytes, {80}));
      cv::imencode(".jpg", image, bytes, {cv::IMWRITE_HDR_COMPRESSION, 1}));
  OpenCvImageEncoderCalculatorResults encoded_image;
  encoded_image.set_encoded_image(bytes.data(), bytes.size());
  encoded_image.set_width(2);
@@ -157,8 +139,7 @@ TEST_F(PackMediaSequenceCalculatorTest, PacksTwoPrefixedImages) {
  mpms::SetClipMediaId(test_video_id, input_sequence.get());
  cv::Mat image(2, 3, CV_8UC3, cv::Scalar(0, 0, 255));
  std::vector<uchar> bytes;
-  ASSERT_TRUE(
+  ASSERT_TRUE(cv::imencode(".jpg", image, bytes, {80}));
      cv::imencode(".jpg", image, bytes, {cv::IMWRITE_HDR_COMPRESSION, 1}));
  OpenCvImageEncoderCalculatorResults encoded_image;
  encoded_image.set_encoded_image(bytes.data(), bytes.size());
  encoded_image.set_width(2);
@@ -331,76 +312,6 @@ TEST_F(PackMediaSequenceCalculatorTest, PacksTwoBytesLists) {
  }
 }
 TEST_F(PackMediaSequenceCalculatorTest, PacksTwoImageLabels) {
  SetUpCalculator(
      {"IMAGE_LABEL_TEST:test_labels", "IMAGE_LABEL_OTHER:test_labels2"}, {},
      false, true);
  auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
  int num_timesteps = 2;
  for (int i = 0; i < num_timesteps; ++i) {
    Detection detection1;
    detection1.add_label(absl::StrCat("foo", 2 << i));
    detection1.add_label_id(i);
    detection1.add_score(0.1 * i);
    detection1.add_label(absl::StrCat("foo", 2 << i));
    detection1.add_label_id(i);
    detection1.add_score(0.1 * i);
    auto label_ptr1 = ::absl::make_unique<Detection>(detection1);
    runner_->MutableInputs()
        ->Tag(kImageLabelTestTag)
        .packets.push_back(Adopt(label_ptr1.release()).At(Timestamp(i)));
    Detection detection2;
    detection2.add_label(absl::StrCat("bar", 2 << i));
    detection2.add_score(0.2 * i);
    detection2.add_label(absl::StrCat("bar", 2 << i));
    detection2.add_score(0.2 * i);
    auto label_ptr2 = ::absl::make_unique<Detection>(detection2);
    runner_->MutableInputs()
        ->Tag(kImageLabelOtherTag)
        .packets.push_back(Adopt(label_ptr2.release()).At(Timestamp(i)));
  }
  runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
      Adopt(input_sequence.release());
  MP_ASSERT_OK(runner_->Run());
  const std::vector<Packet>& output_packets =
      runner_->Outputs().Tag(kSequenceExampleTag).packets;
  ASSERT_EQ(1, output_packets.size());
  const tf::SequenceExample& output_sequence =
      output_packets[0].Get<tf::SequenceExample>();
  ASSERT_EQ(num_timesteps,
            mpms::GetImageTimestampSize("TEST", output_sequence));
  ASSERT_EQ(num_timesteps,
            mpms::GetImageLabelStringSize("TEST", output_sequence));
  ASSERT_EQ(num_timesteps,
            mpms::GetImageLabelConfidenceSize("TEST", output_sequence));
  ASSERT_EQ(num_timesteps,
            mpms::GetImageTimestampSize("OTHER", output_sequence));
  ASSERT_EQ(num_timesteps,
            mpms::GetImageLabelStringSize("OTHER", output_sequence));
  ASSERT_EQ(num_timesteps,
            mpms::GetImageLabelConfidenceSize("OTHER", output_sequence));
  for (int i = 0; i < num_timesteps; ++i) {
    ASSERT_EQ(i, mpms::GetImageTimestampAt("TEST", output_sequence, i));
    ASSERT_THAT(mpms::GetImageLabelStringAt("TEST", output_sequence, i),
                ::testing::ElementsAreArray(
                    std::vector<std::string>(2, absl::StrCat("foo", 2 << i))));
    ASSERT_THAT(mpms::GetImageLabelIndexAt("TEST", output_sequence, i),
                ::testing::ElementsAreArray(std::vector<int32_t>(2, i)));
    ASSERT_THAT(mpms::GetImageLabelConfidenceAt("TEST", output_sequence, i),
                ::testing::ElementsAreArray(std::vector<float>(2, 0.1 * i)));
    ASSERT_EQ(i, mpms::GetImageTimestampAt("OTHER", output_sequence, i));
    ASSERT_THAT(mpms::GetImageLabelStringAt("OTHER", output_sequence, i),
                ::testing::ElementsAreArray(
                    std::vector<std::string>(2, absl::StrCat("bar", 2 << i))));
    ASSERT_THAT(mpms::GetImageLabelConfidenceAt("OTHER", output_sequence, i),
                ::testing::ElementsAreArray(std::vector<float>(2, 0.2 * i)));
  }
 }
 TEST_F(PackMediaSequenceCalculatorTest, OutputAsZeroTimestamp) {
  SetUpCalculator({"FLOAT_FEATURE_TEST:test"}, {}, false, true, true);
  auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
@@ -456,315 +367,6 @@ TEST_F(PackMediaSequenceCalculatorTest, PacksTwoContextFloatLists) {
              testing::ElementsAre(4, 4));
 }
 TEST_F(PackMediaSequenceCalculatorTest, ReplaceTwoContextFloatLists) {
  SetUpCalculator(
      /*input_streams=*/{"FLOAT_CONTEXT_FEATURE_TEST:test",
                         "FLOAT_CONTEXT_FEATURE_OTHER:test2"},
      /*features=*/{},
      /*output_only_if_all_present=*/false, /*replace_instead_of_append=*/true);
  auto input_sequence = std::make_unique<tf::SequenceExample>();
  mpms::SetContextFeatureFloats("TEST", {2, 3}, input_sequence.get());
  mpms::SetContextFeatureFloats("OTHER", {2, 4}, input_sequence.get());
  const std::vector<float> vf_1 = {5, 6};
  runner_->MutableInputs()
      ->Tag(kFloatContextFeatureTestTag)
      .packets.push_back(
          MakePacket<std::vector<float>>(vf_1).At(Timestamp::PostStream()));
  const std::vector<float> vf_2 = {7, 8};
  runner_->MutableInputs()
      ->Tag(kFloatContextFeatureOtherTag)
      .packets.push_back(
          MakePacket<std::vector<float>>(vf_2).At(Timestamp::PostStream()));
  runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
      Adopt(input_sequence.release());
  MP_ASSERT_OK(runner_->Run());
  const std::vector<Packet>& output_packets =
      runner_->Outputs().Tag(kSequenceExampleTag).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(5, 6));
  ASSERT_THAT(mpms::GetContextFeatureFloats("OTHER", output_sequence),
              testing::ElementsAre(7, 8));
 }
 TEST_F(PackMediaSequenceCalculatorTest, AppendTwoContextFloatLists) {
  SetUpCalculator(
      /*input_streams=*/{"FLOAT_CONTEXT_FEATURE_TEST:test",
                         "FLOAT_CONTEXT_FEATURE_OTHER:test2"},
      /*features=*/{},
      /*output_only_if_all_present=*/false,
      /*replace_instead_of_append=*/false);
  auto input_sequence = std::make_unique<tf::SequenceExample>();
  mpms::SetContextFeatureFloats("TEST", {2, 3}, input_sequence.get());
  mpms::SetContextFeatureFloats("OTHER", {2, 4}, input_sequence.get());
  const std::vector<float> vf_1 = {5, 6};
  runner_->MutableInputs()
      ->Tag(kFloatContextFeatureTestTag)
      .packets.push_back(
          MakePacket<std::vector<float>>(vf_1).At(Timestamp::PostStream()));
  const std::vector<float> vf_2 = {7, 8};
  runner_->MutableInputs()
      ->Tag(kFloatContextFeatureOtherTag)
      .packets.push_back(
          MakePacket<std::vector<float>>(vf_2).At(Timestamp::PostStream()));
  runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
      Adopt(input_sequence.release());
  MP_ASSERT_OK(runner_->Run());
  const std::vector<Packet>& output_packets =
      runner_->Outputs().Tag(kSequenceExampleTag).packets;
  ASSERT_EQ(1, output_packets.size());
  const tf::SequenceExample& output_sequence =
      output_packets[0].Get<tf::SequenceExample>();
  EXPECT_THAT(mpms::GetContextFeatureFloats("TEST", output_sequence),
              testing::ElementsAre(2, 3, 5, 6));
  EXPECT_THAT(mpms::GetContextFeatureFloats("OTHER", output_sequence),
              testing::ElementsAre(2, 4, 7, 8));
 }
 TEST_F(PackMediaSequenceCalculatorTest, PackTwoContextIntLists) {
  SetUpCalculator(
      /*input_streams=*/{"INTS_CONTEXT_FEATURE_TEST:test",
                         "INTS_CONTEXT_FEATURE_OTHER:test2"},
      /*features=*/{},
      /*output_only_if_all_present=*/false, /*replace_instead_of_append=*/true);
  auto input_sequence = absl::make_unique<tf::SequenceExample>();
  const std::vector<int64_t> vi_1 = {2, 3};
  runner_->MutableInputs()
      ->Tag(kIntsContextFeatureTestTag)
      .packets.push_back(
          MakePacket<std::vector<int64_t>>(vi_1).At(Timestamp::PostStream()));
  const std::vector<int64_t> vi_2 = {2, 4};
  runner_->MutableInputs()
      ->Tag(kIntsContextFeatureOtherTag)
      .packets.push_back(
          MakePacket<std::vector<int64_t>>(vi_2).At(Timestamp::PostStream()));
  runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
      Adopt(input_sequence.release());
  MP_ASSERT_OK(runner_->Run());
  const std::vector<Packet>& output_packets =
      runner_->Outputs().Tag(kSequenceExampleTag).packets;
  ASSERT_EQ(1, output_packets.size());
  const tf::SequenceExample& output_sequence =
      output_packets[0].Get<tf::SequenceExample>();
  ASSERT_THAT(mpms::GetContextFeatureInts("TEST", output_sequence),
              testing::ElementsAre(2, 3));
  ASSERT_THAT(mpms::GetContextFeatureInts("OTHER", output_sequence),
              testing::ElementsAre(2, 4));
 }
 TEST_F(PackMediaSequenceCalculatorTest, ReplaceTwoContextIntLists) {
  SetUpCalculator(
      /*input_streams=*/{"INTS_CONTEXT_FEATURE_TEST:test",
                         "INTS_CONTEXT_FEATURE_OTHER:test2"},
      /*features=*/{},
      /*output_only_if_all_present=*/false, /*replace_instead_of_append=*/true);
  auto input_sequence = absl::make_unique<tf::SequenceExample>();
  mpms::SetContextFeatureInts("TEST", {2, 3}, input_sequence.get());
  mpms::SetContextFeatureInts("OTHER", {2, 4}, input_sequence.get());
  const std::vector<int64_t> vi_1 = {5, 6};
  runner_->MutableInputs()
      ->Tag(kIntsContextFeatureTestTag)
      .packets.push_back(
          MakePacket<std::vector<int64_t>>(vi_1).At(Timestamp::PostStream()));
  const std::vector<int64_t> vi_2 = {7, 8};
  runner_->MutableInputs()
      ->Tag(kIntsContextFeatureOtherTag)
      .packets.push_back(
          MakePacket<std::vector<int64_t>>(vi_2).At(Timestamp::PostStream()));
  runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
      Adopt(input_sequence.release());
  MP_ASSERT_OK(runner_->Run());
  const std::vector<Packet>& output_packets =
      runner_->Outputs().Tag(kSequenceExampleTag).packets;
  ASSERT_EQ(1, output_packets.size());
  const tf::SequenceExample& output_sequence =
      output_packets[0].Get<tf::SequenceExample>();
  ASSERT_THAT(mpms::GetContextFeatureInts("TEST", output_sequence),
              testing::ElementsAre(5, 6));
  ASSERT_THAT(mpms::GetContextFeatureInts("OTHER", output_sequence),
              testing::ElementsAre(7, 8));
 }
 TEST_F(PackMediaSequenceCalculatorTest, AppendTwoContextIntLists) {
  SetUpCalculator(
      /*input_streams=*/{"INTS_CONTEXT_FEATURE_TEST:test",
                         "INTS_CONTEXT_FEATURE_OTHER:test2"},
      /*features=*/{},
      /*output_only_if_all_present=*/false,
      /*replace_instead_of_append=*/false);
  auto input_sequence = absl::make_unique<tf::SequenceExample>();
  mpms::SetContextFeatureInts("TEST", {2, 3}, input_sequence.get());
  mpms::SetContextFeatureInts("OTHER", {2, 4}, input_sequence.get());
  const std::vector<int64_t> vi_1 = {5, 6};
  runner_->MutableInputs()
      ->Tag(kIntsContextFeatureTestTag)
      .packets.push_back(
          MakePacket<std::vector<int64_t>>(vi_1).At(Timestamp::PostStream()));
  const std::vector<int64_t> vi_2 = {7, 8};
  runner_->MutableInputs()
      ->Tag(kIntsContextFeatureOtherTag)
      .packets.push_back(
          MakePacket<std::vector<int64_t>>(vi_2).At(Timestamp::PostStream()));
  runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
      Adopt(input_sequence.release());
  MP_ASSERT_OK(runner_->Run());
  const std::vector<Packet>& output_packets =
      runner_->Outputs().Tag(kSequenceExampleTag).packets;
  ASSERT_EQ(1, output_packets.size());
  const tf::SequenceExample& output_sequence =
      output_packets[0].Get<tf::SequenceExample>();
  ASSERT_THAT(mpms::GetContextFeatureInts("TEST", output_sequence),
              testing::ElementsAre(2, 3, 5, 6));
  ASSERT_THAT(mpms::GetContextFeatureInts("OTHER", output_sequence),
              testing::ElementsAre(2, 4, 7, 8));
 }
 TEST_F(PackMediaSequenceCalculatorTest, PackTwoContextByteLists) {
  SetUpCalculator(
      /*input_streams=*/{"BYTES_CONTEXT_FEATURE_TEST:test",
                         "BYTES_CONTEXT_FEATURE_OTHER:test2"},
      /*features=*/{},
      /*output_only_if_all_present=*/false, /*replace_instead_of_append=*/true);
  auto input_sequence = absl::make_unique<tf::SequenceExample>();
  const std::vector<std::string> vb_1 = {"value_1", "value_2"};
  runner_->MutableInputs()
      ->Tag(kBytesContextFeatureTestTag)
      .packets.push_back(MakePacket<std::vector<std::string>>(vb_1).At(
          Timestamp::PostStream()));
  const std::vector<std::string> vb_2 = {"value_3", "value_4"};
  runner_->MutableInputs()
      ->Tag(kBytesContextFeatureOtherTag)
      .packets.push_back(MakePacket<std::vector<std::string>>(vb_2).At(
          Timestamp::PostStream()));
  runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
      Adopt(input_sequence.release());
  MP_ASSERT_OK(runner_->Run());
  const std::vector<Packet>& output_packets =
      runner_->Outputs().Tag(kSequenceExampleTag).packets;
  ASSERT_EQ(1, output_packets.size());
  const tf::SequenceExample& output_sequence =
      output_packets[0].Get<tf::SequenceExample>();
  ASSERT_THAT(mpms::GetContextFeatureBytes("TEST", output_sequence),
              testing::ElementsAre("value_1", "value_2"));
  ASSERT_THAT(mpms::GetContextFeatureBytes("OTHER", output_sequence),
              testing::ElementsAre("value_3", "value_4"));
 }
 TEST_F(PackMediaSequenceCalculatorTest, ReplaceTwoContextByteLists) {
  SetUpCalculator(
      /*input_streams=*/{"BYTES_CONTEXT_FEATURE_TEST:test",
                         "BYTES_CONTEXT_FEATURE_OTHER:test2"},
      /*features=*/{},
      /*output_only_if_all_present=*/false, /*replace_instead_of_append=*/true);
  auto input_sequence = absl::make_unique<tf::SequenceExample>();
  mpms::SetContextFeatureBytes("TEST", {"existing_value_1", "existing_value_2"},
                               input_sequence.get());
  mpms::SetContextFeatureBytes(
      "OTHER", {"existing_value_3", "existing_value_4"}, input_sequence.get());
  const std::vector<std::string> vb_1 = {"value_1", "value_2"};
  runner_->MutableInputs()
      ->Tag(kBytesContextFeatureTestTag)
      .packets.push_back(MakePacket<std::vector<std::string>>(vb_1).At(
          Timestamp::PostStream()));
  const std::vector<std::string> vb_2 = {"value_3", "value_4"};
  runner_->MutableInputs()
      ->Tag(kBytesContextFeatureOtherTag)
      .packets.push_back(MakePacket<std::vector<std::string>>(vb_2).At(
          Timestamp::PostStream()));
  runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
      Adopt(input_sequence.release());
  MP_ASSERT_OK(runner_->Run());
  const std::vector<Packet>& output_packets =
      runner_->Outputs().Tag(kSequenceExampleTag).packets;
  ASSERT_EQ(1, output_packets.size());
  const tf::SequenceExample& output_sequence =
      output_packets[0].Get<tf::SequenceExample>();
  ASSERT_THAT(mpms::GetContextFeatureBytes("TEST", output_sequence),
              testing::ElementsAre("value_1", "value_2"));
  ASSERT_THAT(mpms::GetContextFeatureBytes("OTHER", output_sequence),
              testing::ElementsAre("value_3", "value_4"));
 }
 TEST_F(PackMediaSequenceCalculatorTest, AppendTwoContextByteLists) {
  SetUpCalculator(
      /*input_streams=*/{"BYTES_CONTEXT_FEATURE_TEST:test",
                         "BYTES_CONTEXT_FEATURE_OTHER:test2"},
      /*features=*/{},
      /*output_only_if_all_present=*/false,
      /*replace_instead_of_append=*/false);
  auto input_sequence = absl::make_unique<tf::SequenceExample>();
  mpms::SetContextFeatureBytes("TEST", {"existing_value_1", "existing_value_2"},
                               input_sequence.get());
  mpms::SetContextFeatureBytes(
      "OTHER", {"existing_value_3", "existing_value_4"}, input_sequence.get());
  const std::vector<std::string> vb_1 = {"value_1", "value_2"};
  runner_->MutableInputs()
      ->Tag(kBytesContextFeatureTestTag)
      .packets.push_back(MakePacket<std::vector<std::string>>(vb_1).At(
          Timestamp::PostStream()));
  const std::vector<std::string> vb_2 = {"value_3", "value_4"};
  runner_->MutableInputs()
      ->Tag(kBytesContextFeatureOtherTag)
      .packets.push_back(MakePacket<std::vector<std::string>>(vb_2).At(
          Timestamp::PostStream()));
  runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
      Adopt(input_sequence.release());
  MP_ASSERT_OK(runner_->Run());
  const std::vector<Packet>& output_packets =
      runner_->Outputs().Tag(kSequenceExampleTag).packets;
  ASSERT_EQ(1, output_packets.size());
  const tf::SequenceExample& output_sequence =
      output_packets[0].Get<tf::SequenceExample>();
  ASSERT_THAT(mpms::GetContextFeatureBytes("TEST", output_sequence),
              testing::ElementsAre("existing_value_1", "existing_value_2",
                                   "value_1", "value_2"));
  ASSERT_THAT(mpms::GetContextFeatureBytes("OTHER", output_sequence),
              testing::ElementsAre("existing_value_3", "existing_value_4",
                                   "value_3", "value_4"));
 }
 TEST_F(PackMediaSequenceCalculatorTest, PacksAdditionalContext) {
  tf::Features context;
  (*context.mutable_feature())["TEST"].mutable_bytes_list()->add_value("YES");
@@ -776,8 +378,7 @@ TEST_F(PackMediaSequenceCalculatorTest, PacksAdditionalContext) {
      Adopt(input_sequence.release());
  cv::Mat image(2, 3, CV_8UC3, cv::Scalar(0, 0, 255));
  std::vector<uchar> bytes;
-  ASSERT_TRUE(
+  ASSERT_TRUE(cv::imencode(".jpg", image, bytes, {80}));
      cv::imencode(".jpg", image, bytes, {cv::IMWRITE_HDR_COMPRESSION, 1}));
  OpenCvImageEncoderCalculatorResults encoded_image;
  encoded_image.set_encoded_image(bytes.data(), bytes.size());
  auto image_ptr =
@@ -809,8 +410,7 @@ TEST_F(PackMediaSequenceCalculatorTest, PacksTwoForwardFlowEncodeds) {
  cv::Mat image(2, 3, CV_8UC3, cv::Scalar(0, 0, 255));
  std::vector<uchar> bytes;
-  ASSERT_TRUE(
+  ASSERT_TRUE(cv::imencode(".jpg", image, bytes, {80}));
      cv::imencode(".jpg", image, bytes, {cv::IMWRITE_HDR_COMPRESSION, 1}));
  std::string test_flow_string(bytes.begin(), bytes.end());
  OpenCvImageEncoderCalculatorResults encoded_flow;
  encoded_flow.set_encoded_image(test_flow_string);
@@ -926,10 +526,6 @@ TEST_F(PackMediaSequenceCalculatorTest, PacksTwoBBoxDetections) {
    auto class_indices = mpms::GetPredictedBBoxLabelIndexAt(output_sequence, i);
    ASSERT_EQ(0, class_indices[0]);
    ASSERT_EQ(1, class_indices[1]);
    auto class_scores =
        mpms::GetPredictedBBoxLabelConfidenceAt(output_sequence, i);
    ASSERT_FLOAT_EQ(0.5, class_scores[0]);
    ASSERT_FLOAT_EQ(0.75, class_scores[1]);
  }
 }
@@ -1022,8 +618,7 @@ TEST_F(PackMediaSequenceCalculatorTest, PacksBBoxWithImages) {
  }
  cv::Mat image(height, width, CV_8UC3, cv::Scalar(0, 0, 255));
  std::vector<uchar> bytes;
-  ASSERT_TRUE(
+  ASSERT_TRUE(cv::imencode(".jpg", image, bytes, {80}));
      cv::imencode(".jpg", image, bytes, {cv::IMWRITE_HDR_COMPRESSION, 1}));
  OpenCvImageEncoderCalculatorResults encoded_image;
  encoded_image.set_encoded_image(bytes.data(), bytes.size());
  encoded_image.set_width(width);
@@ -1072,10 +667,6 @@ TEST_F(PackMediaSequenceCalculatorTest, PacksBBoxWithImages) {
    auto class_indices = mpms::GetPredictedBBoxLabelIndexAt(output_sequence, i);
    ASSERT_EQ(0, class_indices[0]);
    ASSERT_EQ(1, class_indices[1]);
    auto class_scores =
        mpms::GetPredictedBBoxLabelConfidenceAt(output_sequence, i);
    ASSERT_FLOAT_EQ(0.5, class_scores[0]);
    ASSERT_FLOAT_EQ(0.75, class_scores[1]);
  }
 }
@@ -1166,365 +757,6 @@ TEST_F(PackMediaSequenceCalculatorTest, PacksTwoMaskDetections) {
              testing::ElementsAreArray(::std::vector<std::string>({"mask"})));
 }
 TEST_F(PackMediaSequenceCalculatorTest, PackTwoClipLabels) {
  SetUpCalculator(
      /*input_streams=*/{"CLIP_LABEL_TEST:test", "CLIP_LABEL_OTHER:test2"},
      /*features=*/{}, /*output_only_if_all_present=*/false,
      /*replace_instead_of_append=*/true);
  auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
  Detection detection_1;
  detection_1.add_label("label_1");
  detection_1.add_label("label_2");
  detection_1.add_label_id(1);
  detection_1.add_label_id(2);
  detection_1.add_score(0.1);
  detection_1.add_score(0.2);
  runner_->MutableInputs()
      ->Tag(kClipLabelTestTag)
      .packets.push_back(MakePacket<Detection>(detection_1).At(Timestamp(1)));
  // No label ID for detection_2.
  Detection detection_2;
  detection_2.add_label("label_3");
  detection_2.add_label("label_4");
  detection_2.add_score(0.3);
  detection_2.add_score(0.4);
  runner_->MutableInputs()
      ->Tag(kClipLabelOtherTag)
      .packets.push_back(MakePacket<Detection>(detection_2).At(Timestamp(2)));
  runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
      Adopt(input_sequence.release());
  MP_ASSERT_OK(runner_->Run());
  const std::vector<Packet>& output_packets =
      runner_->Outputs().Tag(kSequenceExampleTag).packets;
  ASSERT_EQ(1, output_packets.size());
  const tf::SequenceExample& output_sequence =
      output_packets[0].Get<tf::SequenceExample>();
  ASSERT_THAT(mpms::GetClipLabelString("TEST", output_sequence),
              testing::ElementsAre("label_1", "label_2"));
  ASSERT_THAT(mpms::GetClipLabelIndex("TEST", output_sequence),
              testing::ElementsAre(1, 2));
  ASSERT_THAT(mpms::GetClipLabelConfidence("TEST", output_sequence),
              testing::ElementsAre(0.1, 0.2));
  ASSERT_THAT(mpms::GetClipLabelString("OTHER", output_sequence),
              testing::ElementsAre("label_3", "label_4"));
  ASSERT_FALSE(mpms::HasClipLabelIndex("OTHER", output_sequence));
  ASSERT_THAT(mpms::GetClipLabelConfidence("OTHER", output_sequence),
              testing::ElementsAre(0.3, 0.4));
 }
 TEST_F(PackMediaSequenceCalculatorTest,
       PackTwoClipLabels_DifferentLabelScoreSize) {
  SetUpCalculator(
      /*input_streams=*/{"CLIP_LABEL_TEST:test", "CLIP_LABEL_OTHER:test2"},
      /*features=*/{}, /*output_only_if_all_present=*/false,
      /*replace_instead_of_append=*/true);
  auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
  // 2 labels and 1 score in detection_1.
  Detection detection_1;
  detection_1.add_label("label_1");
  detection_1.add_label("label_2");
  detection_1.add_score(0.1);
  runner_->MutableInputs()
      ->Tag(kClipLabelTestTag)
      .packets.push_back(MakePacket<Detection>(detection_1).At(Timestamp(1)));
  Detection detection_2;
  detection_2.add_label("label_3");
  detection_2.add_label("label_4");
  detection_2.add_score(0.3);
  detection_2.add_score(0.4);
  runner_->MutableInputs()
      ->Tag(kClipLabelOtherTag)
      .packets.push_back(MakePacket<Detection>(detection_2).At(Timestamp(2)));
  runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
      Adopt(input_sequence.release());
  ASSERT_THAT(
      runner_->Run(),
      testing::status::StatusIs(
          absl::StatusCode::kInvalidArgument,
          testing::HasSubstr(
              "Different size of detection.label and detection.score")));
 }
 TEST_F(PackMediaSequenceCalculatorTest,
       PackTwoClipLabels_DifferentLabelIdSize) {
  SetUpCalculator(
      /*input_streams=*/{"CLIP_LABEL_TEST:test", "CLIP_LABEL_OTHER:test2"},
      /*features=*/{}, /*output_only_if_all_present=*/false,
      /*replace_instead_of_append=*/true);
  auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
  // 2 labels and 1 label_id in detection_1.
  Detection detection_1;
  detection_1.add_label("label_1");
  detection_1.add_label("label_2");
  detection_1.add_label_id(1);
  detection_1.add_score(0.1);
  detection_1.add_score(0.2);
  runner_->MutableInputs()
      ->Tag(kClipLabelTestTag)
      .packets.push_back(MakePacket<Detection>(detection_1).At(Timestamp(1)));
  Detection detection_2;
  detection_2.add_label("label_3");
  detection_2.add_label("label_4");
  detection_2.add_score(0.3);
  detection_2.add_score(0.4);
  runner_->MutableInputs()
      ->Tag(kClipLabelOtherTag)
      .packets.push_back(MakePacket<Detection>(detection_2).At(Timestamp(2)));
  runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
      Adopt(input_sequence.release());
  ASSERT_THAT(
      runner_->Run(),
      testing::status::StatusIs(
          absl::StatusCode::kInvalidArgument,
          testing::HasSubstr(
              "Different size of detection.label_id and detection.label")));
 }
 TEST_F(PackMediaSequenceCalculatorTest, ReplaceTwoClipLabels) {
  // Replace existing clip/label/string and clip/label/confidence values for
  // the prefixes.
  SetUpCalculator(
      /*input_streams=*/{"CLIP_LABEL_TEST:test", "CLIP_LABEL_OTHER:test2"},
      /*features=*/{}, /*output_only_if_all_present=*/false,
      /*replace_instead_of_append=*/true);
  auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
  mpms::SetClipLabelString("TEST", {"old_label_1", "old_label_2"},
                           input_sequence.get());
  mpms::SetClipLabelConfidence("TEST", {0.1, 0.2}, input_sequence.get());
  mpms::SetClipLabelString("OTHER", {"old_label_3", "old_label_4"},
                           input_sequence.get());
  mpms::SetClipLabelConfidence("OTHER", {0.3, 0.4}, input_sequence.get());
  Detection detection_1;
  detection_1.add_label("label_1");
  detection_1.add_label("label_2");
  detection_1.add_label_id(1);
  detection_1.add_label_id(2);
  detection_1.add_score(0.9);
  detection_1.add_score(0.8);
  runner_->MutableInputs()
      ->Tag(kClipLabelTestTag)
      .packets.push_back(MakePacket<Detection>(detection_1).At(Timestamp(1)));
  Detection detection_2;
  detection_2.add_label("label_3");
  detection_2.add_label("label_4");
  detection_2.add_label_id(3);
  detection_2.add_label_id(4);
  detection_2.add_score(0.7);
  detection_2.add_score(0.6);
  runner_->MutableInputs()
      ->Tag(kClipLabelOtherTag)
      .packets.push_back(MakePacket<Detection>(detection_2).At(Timestamp(2)));
  runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
      Adopt(input_sequence.release());
  MP_ASSERT_OK(runner_->Run());
  const std::vector<Packet>& output_packets =
      runner_->Outputs().Tag(kSequenceExampleTag).packets;
  ASSERT_EQ(1, output_packets.size());
  const tf::SequenceExample& output_sequence =
      output_packets[0].Get<tf::SequenceExample>();
  ASSERT_THAT(mpms::GetClipLabelString("TEST", output_sequence),
              testing::ElementsAre("label_1", "label_2"));
  ASSERT_THAT(mpms::GetClipLabelIndex("TEST", output_sequence),
              testing::ElementsAre(1, 2));
  ASSERT_THAT(mpms::GetClipLabelConfidence("TEST", output_sequence),
              testing::ElementsAre(0.9, 0.8));
  ASSERT_THAT(mpms::GetClipLabelString("OTHER", output_sequence),
              testing::ElementsAre("label_3", "label_4"));
  ASSERT_THAT(mpms::GetClipLabelIndex("OTHER", output_sequence),
              testing::ElementsAre(3, 4));
  ASSERT_THAT(mpms::GetClipLabelConfidence("OTHER", output_sequence),
              testing::ElementsAre(0.7, 0.6));
 }
 TEST_F(PackMediaSequenceCalculatorTest, AppendTwoClipLabels) {
  // Append to the existing clip/label/string and clip/label/confidence values
  // for the prefixes.
  SetUpCalculator(
      /*input_streams=*/{"CLIP_LABEL_TEST:test", "CLIP_LABEL_OTHER:test2"},
      /*features=*/{}, /*output_only_if_all_present=*/false,
      /*replace_instead_of_append=*/false);
  auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
  mpms::SetClipLabelString("TEST", {"old_label_1", "old_label_2"},
                           input_sequence.get());
  mpms::SetClipLabelIndex("TEST", {1, 2}, input_sequence.get());
  mpms::SetClipLabelConfidence("TEST", {0.1, 0.2}, input_sequence.get());
  mpms::SetClipLabelString("OTHER", {"old_label_3", "old_label_4"},
                           input_sequence.get());
  mpms::SetClipLabelIndex("OTHER", {3, 4}, input_sequence.get());
  mpms::SetClipLabelConfidence("OTHER", {0.3, 0.4}, input_sequence.get());
  Detection detection_1;
  detection_1.add_label("label_1");
  detection_1.add_label("label_2");
  detection_1.add_label_id(9);
  detection_1.add_label_id(8);
  detection_1.add_score(0.9);
  detection_1.add_score(0.8);
  runner_->MutableInputs()
      ->Tag(kClipLabelTestTag)
      .packets.push_back(MakePacket<Detection>(detection_1).At(Timestamp(1)));
  Detection detection_2;
  detection_2.add_label("label_3");
  detection_2.add_label("label_4");
  detection_2.add_label_id(7);
  detection_2.add_label_id(6);
  detection_2.add_score(0.7);
  detection_2.add_score(0.6);
  runner_->MutableInputs()
      ->Tag(kClipLabelOtherTag)
      .packets.push_back(MakePacket<Detection>(detection_2).At(Timestamp(2)));
  runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
      Adopt(input_sequence.release());
  MP_ASSERT_OK(runner_->Run());
  const std::vector<Packet>& output_packets =
      runner_->Outputs().Tag(kSequenceExampleTag).packets;
  ASSERT_EQ(1, output_packets.size());
  const tf::SequenceExample& output_sequence =
      output_packets[0].Get<tf::SequenceExample>();
  ASSERT_THAT(
      mpms::GetClipLabelString("TEST", output_sequence),
      testing::ElementsAre("old_label_1", "old_label_2", "label_1", "label_2"));
  ASSERT_THAT(mpms::GetClipLabelIndex("TEST", output_sequence),
              testing::ElementsAre(1, 2, 9, 8));
  ASSERT_THAT(mpms::GetClipLabelConfidence("TEST", output_sequence),
              testing::ElementsAre(0.1, 0.2, 0.9, 0.8));
  ASSERT_THAT(
      mpms::GetClipLabelString("OTHER", output_sequence),
      testing::ElementsAre("old_label_3", "old_label_4", "label_3", "label_4"));
  ASSERT_THAT(mpms::GetClipLabelIndex("OTHER", output_sequence),
              testing::ElementsAre(3, 4, 7, 6));
  ASSERT_THAT(mpms::GetClipLabelConfidence("OTHER", output_sequence),
              testing::ElementsAre(0.3, 0.4, 0.7, 0.6));
 }
 TEST_F(PackMediaSequenceCalculatorTest,
       DifferentClipLabelScoreAndConfidenceSize) {
  SetUpCalculator(
      /*input_streams=*/{"CLIP_LABEL_TEST:test", "CLIP_LABEL_OTHER:test2"},
      /*features=*/{}, /*output_only_if_all_present=*/false,
      /*replace_instead_of_append=*/true);
  auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
  Detection detection_1;
  // 2 labels and 1 score.
  detection_1.add_label("label_1");
  detection_1.add_label("label_2");
  detection_1.add_score(0.1);
  runner_->MutableInputs()
      ->Tag(kClipLabelTestTag)
      .packets.push_back(MakePacket<Detection>(detection_1).At(Timestamp(1)));
  Detection detection_2;
  detection_2.add_label("label_3");
  detection_2.add_label("label_4");
  detection_2.add_score(0.3);
  detection_2.add_score(0.4);
  runner_->MutableInputs()
      ->Tag(kClipLabelOtherTag)
      .packets.push_back(MakePacket<Detection>(detection_2).At(Timestamp(2)));
  runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
      Adopt(input_sequence.release());
  ASSERT_THAT(runner_->Run(),
              testing::status::StatusIs(absl::StatusCode::kInvalidArgument));
 }
 TEST_F(PackMediaSequenceCalculatorTest, AddClipMediaId) {
  SetUpCalculator(
      /*input_streams=*/{"FLOAT_FEATURE_TEST:test",
                         "FLOAT_FEATURE_OTHER:test2"},
      /*features=*/{},
      /*output_only_if_all_present=*/false,
      /*replace_instead_of_append=*/true,
      /*output_as_zero_timestamp=*/false, /*input_side_packets=*/
      {"SEQUENCE_EXAMPLE:input_sequence", "CLIP_MEDIA_ID:video_id"});
  auto input_sequence = absl::make_unique<tf::SequenceExample>();
  const std::string test_video_id = "test_video_id";
  int num_timesteps = 2;
  for (int i = 0; i < num_timesteps; ++i) {
    auto vf_ptr = ::absl::make_unique<std::vector<float>>(2, 2 << i);
    runner_->MutableInputs()
        ->Tag(kFloatFeatureTestTag)
        .packets.push_back(Adopt(vf_ptr.release()).At(Timestamp(i)));
    vf_ptr = ::absl::make_unique<std::vector<float>>(2, 2 << i);
    runner_->MutableInputs()
        ->Tag(kFloatFeatureOtherTag)
        .packets.push_back(Adopt(vf_ptr.release()).At(Timestamp(i)));
  }
  runner_->MutableSidePackets()->Tag(kClipMediaIdTag) =
      MakePacket<std::string>(test_video_id);
  runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
      Adopt(input_sequence.release());
  MP_ASSERT_OK(runner_->Run());
  const std::vector<Packet>& output_packets =
      runner_->Outputs().Tag(kSequenceExampleTag).packets;
  ASSERT_EQ(1, output_packets.size());
  const tf::SequenceExample& output_sequence =
      output_packets[0].Get<tf::SequenceExample>();
  ASSERT_EQ(test_video_id, mpms::GetClipMediaId(output_sequence));
 }
 TEST_F(PackMediaSequenceCalculatorTest, ReplaceClipMediaId) {
  SetUpCalculator(
      /*input_streams=*/{"FLOAT_FEATURE_TEST:test",
                         "FLOAT_FEATURE_OTHER:test2"},
      /*features=*/{},
      /*output_only_if_all_present=*/false,
      /*replace_instead_of_append=*/true,
      /*output_as_zero_timestamp=*/false, /*input_side_packets=*/
      {"SEQUENCE_EXAMPLE:input_sequence", "CLIP_MEDIA_ID:video_id"});
  auto input_sequence = absl::make_unique<tf::SequenceExample>();
  const std::string existing_video_id = "existing_video_id";
  mpms::SetClipMediaId(existing_video_id, input_sequence.get());
  const std::string test_video_id = "test_video_id";
  int num_timesteps = 2;
  for (int i = 0; i < num_timesteps; ++i) {
    auto vf_ptr = ::absl::make_unique<std::vector<float>>(2, 2 << i);
    runner_->MutableInputs()
        ->Tag(kFloatFeatureTestTag)
        .packets.push_back(Adopt(vf_ptr.release()).At(Timestamp(i)));
    vf_ptr = ::absl::make_unique<std::vector<float>>(2, 2 << i);
    runner_->MutableInputs()
        ->Tag(kFloatFeatureOtherTag)
        .packets.push_back(Adopt(vf_ptr.release()).At(Timestamp(i)));
  }
  runner_->MutableSidePackets()->Tag(kClipMediaIdTag) =
      MakePacket<std::string>(test_video_id).At(Timestamp(0));
  runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
      Adopt(input_sequence.release());
  MP_ASSERT_OK(runner_->Run());
  const std::vector<Packet>& output_packets =
      runner_->Outputs().Tag(kSequenceExampleTag).packets;
  ASSERT_EQ(1, output_packets.size());
  const tf::SequenceExample& output_sequence =
      output_packets[0].Get<tf::SequenceExample>();
  ASSERT_EQ(test_video_id, mpms::GetClipMediaId(output_sequence));
 }
 TEST_F(PackMediaSequenceCalculatorTest, MissingStreamOK) {
  SetUpCalculator(
      {"FORWARD_FLOW_ENCODED:flow", "FLOAT_FEATURE_I3D_FLOW:feature"}, {},
@@ -1535,8 +767,7 @@ TEST_F(PackMediaSequenceCalculatorTest, MissingStreamOK) {
  cv::Mat image(2, 3, CV_8UC3, cv::Scalar(0, 0, 255));
  std::vector<uchar> bytes;
-  ASSERT_TRUE(
+  ASSERT_TRUE(cv::imencode(".jpg", image, bytes, {80}));
      cv::imencode(".jpg", image, bytes, {cv::IMWRITE_HDR_COMPRESSION, 1}));
  std::string test_flow_string(bytes.begin(), bytes.end());
  OpenCvImageEncoderCalculatorResults encoded_flow;
  encoded_flow.set_encoded_image(test_flow_string);
@@ -1582,8 +813,7 @@ TEST_F(PackMediaSequenceCalculatorTest, MissingStreamNotOK) {
  mpms::SetClipMediaId(test_video_id, input_sequence.get());
  cv::Mat image(2, 3, CV_8UC3, cv::Scalar(0, 0, 255));
  std::vector<uchar> bytes;
-  ASSERT_TRUE(
+  ASSERT_TRUE(cv::imencode(".jpg", image, bytes, {80}));
      cv::imencode(".jpg", image, bytes, {cv::IMWRITE_HDR_COMPRESSION, 1}));
  std::string test_flow_string(bytes.begin(), bytes.end());
  OpenCvImageEncoderCalculatorResults encoded_flow;
  encoded_flow.set_encoded_image(test_flow_string);
@@ -1740,8 +970,7 @@ TEST_F(PackMediaSequenceCalculatorTest, TestReconcilingAnnotations) {
  auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
  cv::Mat image(2, 3, CV_8UC3, cv::Scalar(0, 0, 255));
  std::vector<uchar> bytes;
-  ASSERT_TRUE(
+  ASSERT_TRUE(cv::imencode(".jpg", image, bytes, {80}));
      cv::imencode(".jpg", image, bytes, {cv::IMWRITE_HDR_COMPRESSION, 1}));
  OpenCvImageEncoderCalculatorResults encoded_image;
  encoded_image.set_encoded_image(bytes.data(), bytes.size());
  encoded_image.set_width(2);
@@ -1792,8 +1021,7 @@ TEST_F(PackMediaSequenceCalculatorTest, TestOverwritingAndReconciling) {
  auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
  cv::Mat image(2, 3, CV_8UC3, cv::Scalar(0, 0, 255));
  std::vector<uchar> bytes;
-  ASSERT_TRUE(
+  ASSERT_TRUE(cv::imencode(".jpg", image, bytes, {80}));
      cv::imencode(".jpg", image, bytes, {cv::IMWRITE_HDR_COMPRESSION, 1}));
  OpenCvImageEncoderCalculatorResults encoded_image;
  encoded_image.set_encoded_image(bytes.data(), bytes.size());
  int height = 2;
@@ -1829,7 +1057,6 @@ TEST_F(PackMediaSequenceCalculatorTest, TestOverwritingAndReconciling) {
    mpms::AddBBoxNumRegions(-1, input_sequence.get());
    mpms::AddBBoxLabelString({"anything"}, input_sequence.get());
    mpms::AddBBoxLabelIndex({-1}, input_sequence.get());
    mpms::AddBBoxLabelConfidence({-1}, input_sequence.get());
    mpms::AddBBoxClassString({"anything"}, input_sequence.get());
    mpms::AddBBoxClassIndex({-1}, input_sequence.get());
    mpms::AddBBoxTrackString({"anything"}, input_sequence.get());
@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "absl/log/absl_log.h"
 #include "mediapipe/calculators/tensorflow/tensor_squeeze_dimensions_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/port/ret_check.h"
@@ -100,11 +99,10 @@ class TensorSqueezeDimensionsCalculator : public CalculatorBase {
      }
    }
    if (remove_dims_.empty()) {
-      ABSL_LOG(ERROR)
+      LOG(ERROR) << "TensorSqueezeDimensionsCalculator is squeezing input with "
-          << "TensorSqueezeDimensionsCalculator is squeezing input with "
+                    "no single-dimensions. Calculator will be a no-op.";
-             "no single-dimensions. Calculator will be a no-op.";
+      LOG(ERROR) << "Input to TensorSqueezeDimensionsCalculator has shape "
-      ABSL_LOG(ERROR) << "Input to TensorSqueezeDimensionsCalculator has shape "
+                 << tensor_shape.DebugString();
                      << tensor_shape.DebugString();
    }
  }
 };
@@ -14,7 +14,6 @@
 #include <iostream>
 #include "absl/log/absl_check.h"
 #include "mediapipe/calculators/tensorflow/tensor_to_image_frame_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/formats/image_frame.h"
@@ -100,7 +99,7 @@ absl::Status TensorToImageFrameCalculator::Process(CalculatorContext* cc) {
  const tf::Tensor& input_tensor = cc->Inputs().Tag(kTensor).Get<tf::Tensor>();
  int32_t depth = 1;
  if (input_tensor.dims() != 2) {  // Depth is 1 for 2D tensors.
-    ABSL_CHECK(3 == input_tensor.dims())
+    CHECK(3 == input_tensor.dims())
        << "Only 2 or 3-D Tensors can be converted to frames. Instead got: "
        << input_tensor.dims();
    depth = input_tensor.dim_size(2);
@@ -15,7 +15,6 @@
 // Calculator converts from one-dimensional Tensor of DT_FLOAT to Matrix
 // OR from (batched) two-dimensional Tensor of DT_FLOAT to Matrix.
 #include "absl/log/absl_check.h"
 #include "mediapipe/calculators/tensorflow/tensor_to_matrix_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/formats/matrix.h"
@@ -37,7 +36,7 @@ constexpr char kReference[] = "REFERENCE";
 absl::Status FillTimeSeriesHeaderIfValid(const Packet& header_packet,
                                         TimeSeriesHeader* header) {
-  ABSL_CHECK(header);
+  CHECK(header);
  if (header_packet.IsEmpty()) {
    return absl::UnknownError("No header found.");
  }
@@ -192,7 +191,7 @@ absl::Status TensorToMatrixCalculator::Process(CalculatorContext* cc) {
      << "Tensor stream packet does not contain a Tensor.";
  const tf::Tensor& input_tensor = cc->Inputs().Tag(kTensor).Get<tf::Tensor>();
-  ABSL_CHECK(1 == input_tensor.dims() || 2 == input_tensor.dims())
+  CHECK(1 == input_tensor.dims() || 2 == input_tensor.dims())
      << "Only 1-D or 2-D Tensors can be converted to matrices.";
  const int32_t length = input_tensor.dim_size(input_tensor.dims() - 1);
  const int32_t width =
@@ -15,16 +15,12 @@
 // Calculator converts from one-dimensional Tensor of DT_FLOAT to vector<float>
 // OR from (batched) two-dimensional Tensor of DT_FLOAT to vector<vector<float>.
 #include <memory>
 #include <vector>
 #include "mediapipe/calculators/tensorflow/tensor_to_vector_float_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"
 #include "tensorflow/core/platform/bfloat16.h"
 namespace mediapipe {
@@ -80,31 +76,21 @@ absl::Status TensorToVectorFloatCalculator::Open(CalculatorContext* cc) {
 absl::Status TensorToVectorFloatCalculator::Process(CalculatorContext* cc) {
  const tf::Tensor& input_tensor =
      cc->Inputs().Index(0).Value().Get<tf::Tensor>();
-  RET_CHECK(tf::DT_FLOAT == input_tensor.dtype() ||
+  RET_CHECK(tf::DT_FLOAT == input_tensor.dtype())
-            tf::DT_BFLOAT16 == input_tensor.dtype())
+      << "expected DT_FLOAT input but got "
      << "expected DT_FLOAT or DT_BFLOAT_16 input but got "
      << tensorflow::DataTypeString(input_tensor.dtype());
  if (options_.tensor_is_2d()) {
    RET_CHECK(2 == input_tensor.dims())
        << "Expected 2-dimensional Tensor, but the tensor shape is: "
        << input_tensor.shape().DebugString();
-    auto output = std::make_unique<std::vector<std::vector<float>>>(
+    auto output = absl::make_unique<std::vector<std::vector<float>>>(
        input_tensor.dim_size(0), std::vector<float>(input_tensor.dim_size(1)));
    for (int i = 0; i < input_tensor.dim_size(0); ++i) {
      auto& instance_output = output->at(i);
-      if (tf::DT_BFLOAT16 == input_tensor.dtype()) {
+      const auto& slice = input_tensor.Slice(i, i + 1).unaligned_flat<float>();
-        const auto& slice =
+      for (int j = 0; j < input_tensor.dim_size(1); ++j) {
-            input_tensor.Slice(i, i + 1).unaligned_flat<tf::bfloat16>();
+        instance_output.at(j) = slice(j);
        for (int j = 0; j < input_tensor.dim_size(1); ++j) {
          instance_output.at(j) = static_cast<float>(slice(j));
        }
      } else {
        const auto& slice =
            input_tensor.Slice(i, i + 1).unaligned_flat<float>();
        for (int j = 0; j < input_tensor.dim_size(1); ++j) {
          instance_output.at(j) = slice(j);
        }
      }
    }
    cc->Outputs().Index(0).Add(output.release(), cc->InputTimestamp());
@@ -115,17 +101,10 @@ absl::Status TensorToVectorFloatCalculator::Process(CalculatorContext* cc) {
          << "tensor shape is: " << input_tensor.shape().DebugString();
    }
    auto output =
-        std::make_unique<std::vector<float>>(input_tensor.NumElements());
+        absl::make_unique<std::vector<float>>(input_tensor.NumElements());
-    if (tf::DT_BFLOAT16 == input_tensor.dtype()) {
+    const auto& tensor_values = input_tensor.unaligned_flat<float>();
-      const auto& tensor_values = input_tensor.unaligned_flat<tf::bfloat16>();
+    for (int i = 0; i < input_tensor.NumElements(); ++i) {
-      for (int i = 0; i < input_tensor.NumElements(); ++i) {
+      output->at(i) = tensor_values(i);
        output->at(i) = static_cast<float>(tensor_values(i));
      }
    } else {
      const auto& tensor_values = input_tensor.unaligned_flat<float>();
      for (int i = 0; i < input_tensor.NumElements(); ++i) {
        output->at(i) = tensor_values(i);
      }
    }
    cc->Outputs().Index(0).Add(output.release(), cc->InputTimestamp());
  }
@@ -12,8 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include <memory>
 #include "mediapipe/calculators/tensorflow/tensor_to_vector_float_calculator_options.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/calculator_runner.h"
@@ -21,7 +19,6 @@
 #include "mediapipe/util/packet_test_util.h"
 #include "tensorflow/core/framework/tensor.h"
 #include "tensorflow/core/framework/types.pb.h"
 #include "tensorflow/core/platform/bfloat16.h"
 namespace mediapipe {
@@ -75,62 +72,6 @@ TEST_F(TensorToVectorFloatCalculatorTest, ConvertsToVectorFloat) {
  }
 }
 TEST_F(TensorToVectorFloatCalculatorTest, CheckBFloat16Type) {
  SetUpRunner(false, false);
  const tf::TensorShape tensor_shape(std::vector<tf::int64>{5});
  auto tensor = std::make_unique<tf::Tensor>(tf::DT_BFLOAT16, tensor_shape);
  auto tensor_vec = tensor->vec<tf::bfloat16>();
  for (int i = 0; i < 5; ++i) {
    tensor_vec(i) = static_cast<tf::bfloat16>(1 << i);
  }
  const int64_t time = 1234;
  runner_->MutableInputs()->Index(0).packets.push_back(
      Adopt(tensor.release()).At(Timestamp(time)));
  EXPECT_TRUE(runner_->Run().ok());
  const std::vector<Packet>& output_packets =
      runner_->Outputs().Index(0).packets;
  EXPECT_EQ(1, output_packets.size());
  EXPECT_EQ(time, output_packets[0].Timestamp().Value());
  const std::vector<float>& output_vector =
      output_packets[0].Get<std::vector<float>>();
  EXPECT_EQ(5, output_vector.size());
  for (int i = 0; i < 5; ++i) {
    const float expected = static_cast<float>(1 << i);
    EXPECT_EQ(expected, output_vector[i]);
  }
 }
 TEST_F(TensorToVectorFloatCalculatorTest, CheckBFloat16TypeAllDim) {
  SetUpRunner(false, true);
  const tf::TensorShape tensor_shape(std::vector<tf::int64>{2, 2, 2});
  auto tensor = std::make_unique<tf::Tensor>(tf::DT_BFLOAT16, tensor_shape);
  auto slice = tensor->flat<tf::bfloat16>();
  for (int i = 0; i < 2 * 2 * 2; ++i) {
    // 2^i can be represented exactly in floating point numbers if 'i' is small.
    slice(i) = static_cast<tf::bfloat16>(1 << i);
  }
  const int64_t time = 1234;
  runner_->MutableInputs()->Index(0).packets.push_back(
      Adopt(tensor.release()).At(Timestamp(time)));
  EXPECT_TRUE(runner_->Run().ok());
  const std::vector<Packet>& output_packets =
      runner_->Outputs().Index(0).packets;
  EXPECT_EQ(1, output_packets.size());
  EXPECT_EQ(time, output_packets[0].Timestamp().Value());
  const std::vector<float>& output_vector =
      output_packets[0].Get<std::vector<float>>();
  EXPECT_EQ(2 * 2 * 2, output_vector.size());
  for (int i = 0; i < 2 * 2 * 2; ++i) {
    const float expected = static_cast<float>(1 << i);
    EXPECT_EQ(expected, output_vector[i]);
  }
 }
 TEST_F(TensorToVectorFloatCalculatorTest, ConvertsBatchedToVectorVectorFloat) {
  SetUpRunner(true, false);
  const tf::TensorShape tensor_shape(std::vector<tf::int64>{1, 5});
@@ -20,7 +20,6 @@
 #include <vector>
 #include "absl/base/thread_annotations.h"
 #include "absl/log/absl_check.h"
 #include "absl/memory/memory.h"
 #include "absl/strings/str_split.h"
 #include "absl/synchronization/mutex.h"
@@ -516,7 +515,7 @@ class TensorFlowInferenceCalculator : public CalculatorBase {
        tf::Tensor concated;
        const tf::Status concat_status =
            tf::tensor::Concat(keyed_tensors.second, &concated);
-        ABSL_CHECK(concat_status.ok()) << concat_status.ToString();
+        CHECK(concat_status.ok()) << concat_status.ToString();
        input_tensors.emplace_back(tag_to_tensor_map_[keyed_tensors.first],
                                   concated);
      }
@@ -598,7 +597,7 @@ class TensorFlowInferenceCalculator : public CalculatorBase {
        std::vector<tf::Tensor> split_tensors;
        const tf::Status split_status =
            tf::tensor::Split(outputs[i], split_vector, &split_tensors);
-        ABSL_CHECK(split_status.ok()) << split_status.ToString();
+        CHECK(split_status.ok()) << split_status.ToString();
        // Loop over timestamps so that we don't copy the padding.
        for (int j = 0; j < inference_state->batch_timestamps_.size(); ++j) {
          tf::Tensor output_tensor(split_tensors[j]);
@@ -17,8 +17,6 @@
 #include <vector>
 #include "absl/flags/flag.h"
 #include "absl/log/absl_check.h"
 #include "absl/log/absl_log.h"
 #include "mediapipe/calculators/tensorflow/tensorflow_inference_calculator.pb.h"
 #include "mediapipe/calculators/tensorflow/tensorflow_session_from_frozen_graph_generator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
@@ -120,7 +118,7 @@ class TensorflowInferenceCalculatorTest : public ::testing::Test {
  // Create tensor from Vector and add as a Packet to the provided tag as input.
  void AddVectorToInputsAsPacket(const std::vector<Packet>& packets,
                                 const std::string& tag) {
-    ABSL_CHECK(!packets.empty())
+    CHECK(!packets.empty())
        << "Please specify at least some data in the packet";
    auto packets_ptr = absl::make_unique<std::vector<Packet>>(packets);
    runner_->MutableInputs()->Tag(tag).packets.push_back(
@@ -588,12 +586,12 @@ TEST_F(TensorflowInferenceCalculatorTest, TestRecurrentStates) {
      runner_->Outputs().Tag(kMultipliedTag).packets;
  ASSERT_EQ(2, output_packets_mult.size());
  const tf::Tensor& tensor_mult = output_packets_mult[0].Get<tf::Tensor>();
-  ABSL_LOG(INFO) << "timestamp: " << 0;
+  LOG(INFO) << "timestamp: " << 0;
  auto expected_tensor = tf::test::AsTensor<int32_t>({3, 8, 15});
  tf::test::ExpectTensorEqual<int32_t>(tensor_mult, expected_tensor);
  const tf::Tensor& tensor_mult1 = output_packets_mult[1].Get<tf::Tensor>();
  auto expected_tensor1 = tf::test::AsTensor<int32_t>({9, 32, 75});
-  ABSL_LOG(INFO) << "timestamp: " << 1;
+  LOG(INFO) << "timestamp: " << 1;
  tf::test::ExpectTensorEqual<int32_t>(tensor_mult1, expected_tensor1);
  EXPECT_EQ(2, runner_
@@ -629,12 +627,12 @@ TEST_F(TensorflowInferenceCalculatorTest, TestRecurrentStateOverride) {
      runner_->Outputs().Tag(kMultipliedTag).packets;
  ASSERT_EQ(2, output_packets_mult.size());
  const tf::Tensor& tensor_mult = output_packets_mult[0].Get<tf::Tensor>();
-  ABSL_LOG(INFO) << "timestamp: " << 0;
+  LOG(INFO) << "timestamp: " << 0;
  auto expected_tensor = tf::test::AsTensor<int32_t>({3, 4, 5});
  tf::test::ExpectTensorEqual<int32_t>(tensor_mult, expected_tensor);
  const tf::Tensor& tensor_mult1 = output_packets_mult[1].Get<tf::Tensor>();
  auto expected_tensor1 = tf::test::AsTensor<int32_t>({3, 4, 5});
-  ABSL_LOG(INFO) << "timestamp: " << 1;
+  LOG(INFO) << "timestamp: " << 1;
  tf::test::ExpectTensorEqual<int32_t>(tensor_mult1, expected_tensor1);
  EXPECT_EQ(2, runner_
@@ -23,12 +23,12 @@
 #include <string>
 #include "absl/log/absl_log.h"
 #include "mediapipe/calculators/tensorflow/tensorflow_session.h"
 #include "mediapipe/calculators/tensorflow/tensorflow_session_from_frozen_graph_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/deps/clock.h"
 #include "mediapipe/framework/deps/monotonic_clock.h"
 #include "mediapipe/framework/port/logging.h"
 #include "mediapipe/framework/port/ret_check.h"
 #include "mediapipe/framework/port/status.h"
 #include "mediapipe/framework/tool/status_util.h"
@@ -156,8 +156,8 @@ class TensorFlowSessionFromFrozenGraphCalculator : public CalculatorBase {
    cc->OutputSidePackets().Tag(kSessionTag).Set(Adopt(session.release()));
    const uint64_t end_time = absl::ToUnixMicros(clock->TimeNow());
-    ABSL_LOG(INFO) << "Loaded frozen model in: " << end_time - start_time
+    LOG(INFO) << "Loaded frozen model in: " << end_time - start_time
-                   << " microseconds.";
+              << " microseconds.";
    return absl::OkStatus();
  }
@@ -24,13 +24,13 @@
 #include <string>
 #include "absl/log/absl_log.h"
 #include "mediapipe/calculators/tensorflow/tensorflow_session.h"
 #include "mediapipe/calculators/tensorflow/tensorflow_session_from_frozen_graph_generator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/deps/clock.h"
 #include "mediapipe/framework/deps/monotonic_clock.h"
 #include "mediapipe/framework/port/file_helpers.h"
 #include "mediapipe/framework/port/logging.h"
 #include "mediapipe/framework/port/ret_check.h"
 #include "mediapipe/framework/port/status.h"
 #include "mediapipe/framework/tool/status_util.h"
@@ -155,8 +155,8 @@ class TensorFlowSessionFromFrozenGraphGenerator : public PacketGenerator {
    output_side_packets->Tag(kSessionTag) = Adopt(session.release());
    const uint64_t end_time = absl::ToUnixMicros(clock->TimeNow());
-    ABSL_LOG(INFO) << "Loaded frozen model in: " << end_time - start_time
+    LOG(INFO) << "Loaded frozen model in: " << end_time - start_time
-                   << " microseconds.";
+              << " microseconds.";
    return absl::OkStatus();
  }
 };
@@ -17,7 +17,6 @@
 #if !defined(__ANDROID__)
 #include "mediapipe/framework/port/file_helpers.h"
 #endif
 #include "absl/log/absl_log.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"
@@ -70,7 +69,7 @@ const std::string MaybeConvertSignatureToTag(
                   [](unsigned char c) { return std::toupper(c); });
    output = absl::StrReplaceAll(
        output, {{"/", "_"}, {"-", "_"}, {".", "_"}, {":", "_"}});
-    ABSL_LOG(INFO) << "Renamed TAG from: " << name << " to " << output;
+    LOG(INFO) << "Renamed TAG from: " << name << " to " << output;
    return output;
  } else {
    return name;
@@ -19,7 +19,6 @@
 #if !defined(__ANDROID__)
 #include "mediapipe/framework/port/file_helpers.h"
 #endif
 #include "absl/log/absl_log.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"
@@ -76,7 +75,7 @@ const std::string MaybeConvertSignatureToTag(
                   [](unsigned char c) { return std::toupper(c); });
    output = absl::StrReplaceAll(
        output, {{"/", "_"}, {"-", "_"}, {".", "_"}, {":", "_"}});
-    ABSL_LOG(INFO) << "Renamed TAG from: " << name << " to " << output;
+    LOG(INFO) << "Renamed TAG from: " << name << " to " << output;
    return output;
  } else {
    return name;
@@ -13,7 +13,6 @@
 // limitations under the License.
 #include "absl/container/flat_hash_map.h"
 #include "absl/log/absl_log.h"
 #include "absl/strings/match.h"
 #include "mediapipe/calculators/core/packet_resampler_calculator.pb.h"
 #include "mediapipe/calculators/tensorflow/unpack_media_sequence_calculator.pb.h"
@@ -202,8 +201,8 @@ class UnpackMediaSequenceCalculator : public CalculatorBase {
    first_timestamp_seen_ = Timestamp::OneOverPostStream().Value();
    for (const auto& map_kv : sequence_->feature_lists().feature_list()) {
      if (absl::StrContains(map_kv.first, "/timestamp")) {
-        ABSL_LOG(INFO) << "Found feature timestamps: " << map_kv.first
+        LOG(INFO) << "Found feature timestamps: " << map_kv.first
-                       << " with size: " << map_kv.second.feature_size();
+                  << " with size: " << map_kv.second.feature_size();
        int64_t recent_timestamp = Timestamp::PreStream().Value();
        for (int i = 0; i < map_kv.second.feature_size(); ++i) {
          int64_t next_timestamp =
@@ -310,8 +309,8 @@ class UnpackMediaSequenceCalculator : public CalculatorBase {
        audio_decoder_options->set_end_time(
            end_time + options.extra_padding_from_media_decoder());
      }
-      ABSL_LOG(INFO) << "Created AudioDecoderOptions:\n"
+      LOG(INFO) << "Created AudioDecoderOptions:\n"
-                     << audio_decoder_options->DebugString();
+                << audio_decoder_options->DebugString();
      cc->OutputSidePackets()
          .Tag(kAudioDecoderOptions)
          .Set(Adopt(audio_decoder_options.release()));
@@ -332,8 +331,8 @@ class UnpackMediaSequenceCalculator : public CalculatorBase {
            ->set_end_time(Timestamp::FromSeconds(end_time).Value());
      }
-      ABSL_LOG(INFO) << "Created PacketResamplerOptions:\n"
+      LOG(INFO) << "Created PacketResamplerOptions:\n"
-                     << resampler_options->DebugString();
+                << resampler_options->DebugString();
      cc->OutputSidePackets()
          .Tag(kPacketResamplerOptions)
          .Set(Adopt(resampler_options.release()));
@@ -352,8 +351,7 @@ class UnpackMediaSequenceCalculator : public CalculatorBase {
  absl::Status Process(CalculatorContext* cc) override {
    if (timestamps_.empty()) {
      // This occurs when we only have metadata to unpack.
-      ABSL_LOG(INFO)
+      LOG(INFO) << "only unpacking metadata because there are no timestamps.";
          << "only unpacking metadata because there are no timestamps.";
      return tool::StatusStop();
    }
    // In Process(), we loop through timestamps on a reference stream and emit
@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "absl/log/absl_log.h"
 #include "absl/memory/memory.h"
 #include "absl/strings/numbers.h"
 #include "mediapipe/calculators/core/packet_resampler_calculator.pb.h"
@@ -82,7 +81,7 @@ class UnpackMediaSequenceCalculatorTest : public ::testing::Test {
    if (options != nullptr) {
      *config.mutable_options() = *options;
    }
-    ABSL_LOG(INFO) << config.DebugString();
+    LOG(INFO) << config.DebugString();
    runner_ = absl::make_unique<CalculatorRunner>(config);
  }
@@ -14,8 +14,6 @@
 #include <iterator>
 #include "absl/log/absl_check.h"
 #include "absl/log/absl_log.h"
 #include "mediapipe/calculators/tensorflow/lapped_tensor_buffer_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/packet.h"
@@ -48,7 +46,7 @@ std::string GetQuantizedFeature(
                               .Get(index)
                               .bytes_list()
                               .value();
-  ABSL_CHECK_EQ(1, bytes_list.size());
+  CHECK_EQ(1, bytes_list.size());
  return bytes_list.Get(0);
 }
 }  // namespace
@@ -151,9 +149,8 @@ class UnpackYt8mSequenceExampleCalculator : public CalculatorBase {
            .Set(MakePacket<int>(segment_size));
      }
    }
-    ABSL_LOG(INFO) << "Reading the sequence example that contains yt8m id: "
+    LOG(INFO) << "Reading the sequence example that contains yt8m id: "
-                   << yt8m_id
+              << yt8m_id << ". Feature list length: " << feature_list_length_;
                   << ". Feature list length: " << feature_list_length_;
    return absl::OkStatus();
  }
@@ -14,7 +14,6 @@
 //
 // Converts vector<float> (or vector<vector<float>>) to 1D (or 2D) tf::Tensor.
 #include "absl/log/absl_log.h"
 #include "mediapipe/calculators/tensorflow/vector_float_to_tensor_calculator_options.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/port/ret_check.h"
@@ -69,7 +68,7 @@ absl::Status VectorFloatToTensorCalculator::GetContract(
        // Output vector<float>.
    );
  } else {
-    ABSL_LOG(FATAL) << "input size not supported";
+    LOG(FATAL) << "input size not supported";
  }
  RET_CHECK_EQ(cc->Outputs().NumEntries(), 1)
      << "Only one output stream is supported.";
@@ -126,7 +125,7 @@ absl::Status VectorFloatToTensorCalculator::Process(CalculatorContext* cc) {
    }
    cc->Outputs().Index(0).Add(output.release(), cc->InputTimestamp());
  } else {
-    ABSL_LOG(FATAL) << "input size not supported";
+    LOG(FATAL) << "input size not supported";
  }
  return absl::OkStatus();
 }
@@ -15,8 +15,6 @@
 // Converts a single int or vector<int> or vector<vector<int>> to 1D (or 2D)
 // tf::Tensor.
 #include "absl/log/absl_check.h"
 #include "absl/log/absl_log.h"
 #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"
@@ -88,7 +86,7 @@ absl::Status VectorIntToTensorCalculator::GetContract(CalculatorContract* cc) {
      cc->Inputs().Tag(kVectorInt).Set<std::vector<int>>();
    }
  } else {
-    ABSL_LOG(FATAL) << "input size not supported";
+    LOG(FATAL) << "input size not supported";
  }
  RET_CHECK_EQ(cc->Outputs().NumEntries(), 1)
      << "Only one output stream is supported.";
@@ -115,11 +113,11 @@ absl::Status VectorIntToTensorCalculator::Process(CalculatorContext* cc) {
            .Get<std::vector<std::vector<int>>>();
    const int32_t rows = input.size();
-    ABSL_CHECK_GE(rows, 1);
+    CHECK_GE(rows, 1);
    const int32_t cols = input[0].size();
-    ABSL_CHECK_GE(cols, 1);
+    CHECK_GE(cols, 1);
    for (int i = 1; i < rows; ++i) {
-      ABSL_CHECK_EQ(input[i].size(), cols);
+      CHECK_EQ(input[i].size(), cols);
    }
    if (options_.transpose()) {
      tensor_shape = tf::TensorShape({cols, rows});
@@ -142,7 +140,7 @@ absl::Status VectorIntToTensorCalculator::Process(CalculatorContext* cc) {
              AssignMatrixValue<int>(c, r, input[r][c], output.get());
              break;
            default:
-              ABSL_LOG(FATAL) << "tensor data type is not supported.";
+              LOG(FATAL) << "tensor data type is not supported.";
          }
        }
      }
@@ -160,7 +158,7 @@ absl::Status VectorIntToTensorCalculator::Process(CalculatorContext* cc) {
              AssignMatrixValue<int>(r, c, input[r][c], output.get());
              break;
            default:
-              ABSL_LOG(FATAL) << "tensor data type is not supported.";
+              LOG(FATAL) << "tensor data type is not supported.";
          }
        }
      }
@@ -173,7 +171,7 @@ absl::Status VectorIntToTensorCalculator::Process(CalculatorContext* cc) {
    } else {
      input = cc->Inputs().Tag(kVectorInt).Value().Get<std::vector<int>>();
    }
-    ABSL_CHECK_GE(input.size(), 1);
+    CHECK_GE(input.size(), 1);
    const int32_t length = input.size();
    tensor_shape = tf::TensorShape({length});
    auto output = ::absl::make_unique<tf::Tensor>(options_.tensor_data_type(),
@@ -190,12 +188,12 @@ absl::Status VectorIntToTensorCalculator::Process(CalculatorContext* cc) {
          output->tensor<int, 1>()(i) = input.at(i);
          break;
        default:
-          ABSL_LOG(FATAL) << "tensor data type is not supported.";
+          LOG(FATAL) << "tensor data type is not supported.";
      }
    }
    cc->Outputs().Tag(kTensorOut).Add(output.release(), cc->InputTimestamp());
  } else {
-    ABSL_LOG(FATAL) << "input size not supported";
+    LOG(FATAL) << "input size not supported";
  }
  return absl::OkStatus();
 }
@@ -15,7 +15,6 @@
 // Converts vector<std::string> (or vector<vector<std::string>>) to 1D (or 2D)
 // tf::Tensor.
 #include "absl/log/absl_log.h"
 #include "mediapipe/calculators/tensorflow/vector_string_to_tensor_calculator_options.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/port/ret_check.h"
@@ -70,7 +69,7 @@ absl::Status VectorStringToTensorCalculator::GetContract(
        // Input vector<std::string>.
    );
  } else {
-    ABSL_LOG(FATAL) << "input size not supported";
+    LOG(FATAL) << "input size not supported";
  }
  RET_CHECK_EQ(cc->Outputs().NumEntries(), 1)
      << "Only one output stream is supported.";
@@ -130,7 +129,7 @@ absl::Status VectorStringToTensorCalculator::Process(CalculatorContext* cc) {
    }
    cc->Outputs().Index(0).Add(output.release(), cc->InputTimestamp());
  } else {
-    ABSL_LOG(FATAL) << "input size not supported";
+    LOG(FATAL) << "input size not supported";
  }
  return absl::OkStatus();
 }
@@ -103,8 +103,6 @@ cc_library(
        "//mediapipe/framework/formats/object_detection:anchor_cc_proto",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/log:absl_log",
    ],
    alwayslink = 1,
 )
@@ -198,13 +196,10 @@ cc_library(
    deps = [
        ":tflite_inference_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/port:logging",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/stream_handler:fixed_size_input_stream_handler",
        "//mediapipe/util/tflite:config",
        "//mediapipe/util/tflite:tflite_model_loader",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_absl//absl/memory",
        "@org_tensorflow//tensorflow/lite:framework",
        "@org_tensorflow//tensorflow/lite/delegates/xnnpack:xnnpack_delegate",
@@ -280,7 +275,6 @@ cc_library(
        "//mediapipe/framework/stream_handler:fixed_size_input_stream_handler",
        "//mediapipe/util:resource_util",
        "//mediapipe/util/tflite:config",
        "@com_google_absl//absl/log:absl_check",
        "@org_tensorflow//tensorflow/lite:framework",
        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
    ] + selects.with_or({
@@ -398,8 +392,6 @@ cc_library(
        "//mediapipe/framework/formats/object_detection:anchor_cc_proto",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/util/tflite:config",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_absl//absl/strings:str_format",
        "@com_google_absl//absl/types:span",
        "@org_tensorflow//tensorflow/lite:framework",
@@ -436,7 +428,6 @@ cc_library(
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/util:resource_util",
        "@com_google_absl//absl/container:node_hash_map",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/strings:str_format",
        "@com_google_absl//absl/types:span",
        "@org_tensorflow//tensorflow/lite:framework",
@@ -465,7 +456,6 @@ cc_library(
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework/formats:landmark_cc_proto",
        "//mediapipe/framework/port:ret_check",
        "@com_google_absl//absl/log:absl_check",
        "@org_tensorflow//tensorflow/lite:framework",
    ],
    alwayslink = 1,
@@ -16,8 +16,6 @@
 #include <utility>
 #include <vector>
 #include "absl/log/absl_check.h"
 #include "absl/log/absl_log.h"
 #include "mediapipe/calculators/tflite/ssd_anchors_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/formats/object_detection/anchor.pb.h"
@@ -274,13 +272,13 @@ absl::Status SsdAnchorsCalculator::GenerateAnchors(
  if (options.feature_map_height_size()) {
    if (options.strides_size()) {
-      ABSL_LOG(ERROR) << "Found feature map shapes. Strides will be ignored.";
+      LOG(ERROR) << "Found feature map shapes. Strides will be ignored.";
    }
-    ABSL_CHECK_EQ(options.feature_map_height_size(), kNumLayers);
+    CHECK_EQ(options.feature_map_height_size(), kNumLayers);
-    ABSL_CHECK_EQ(options.feature_map_height_size(),
+    CHECK_EQ(options.feature_map_height_size(),
-                  options.feature_map_width_size());
+             options.feature_map_width_size());
  } else {
-    ABSL_CHECK_EQ(options.strides_size(), kNumLayers);
+    CHECK_EQ(options.strides_size(), kNumLayers);
  }
  if (options.multiscale_anchor_generation()) {
@@ -15,7 +15,6 @@
 #include <string>
 #include <vector>
 #include "absl/log/absl_check.h"
 #include "mediapipe/calculators/tflite/tflite_converter_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/formats/image_frame.h"
@@ -644,7 +643,7 @@ absl::Status TfLiteConverterCalculator::LoadOptions(CalculatorContext* cc) {
  if (options.has_output_tensor_float_range()) {
    output_range_.emplace(options.output_tensor_float_range().min(),
                          options.output_tensor_float_range().max());
-    ABSL_CHECK_GT(output_range_->second, output_range_->first);
+    CHECK_GT(output_range_->second, output_range_->first);
  }
  // Custom div and sub values.
@@ -662,9 +661,9 @@ absl::Status TfLiteConverterCalculator::LoadOptions(CalculatorContext* cc) {
  // Get desired way to handle input channels.
  max_num_channels_ = options.max_num_channels();
-  ABSL_CHECK_GE(max_num_channels_, 1);
+  CHECK_GE(max_num_channels_, 1);
-  ABSL_CHECK_LE(max_num_channels_, 4);
+  CHECK_LE(max_num_channels_, 4);
-  ABSL_CHECK_NE(max_num_channels_, 2);
+  CHECK_NE(max_num_channels_, 2);
 #if defined(MEDIAPIPE_IOS)
  if (cc->Inputs().HasTag(kGpuBufferTag))
    // Currently on iOS, tflite gpu input tensor must be 4 channels,
@@ -17,12 +17,9 @@
 #include <string>
 #include <vector>
 #include "absl/log/absl_check.h"
 #include "absl/log/absl_log.h"
 #include "absl/memory/memory.h"
 #include "mediapipe/calculators/tflite/tflite_inference_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/port/logging.h"
 #include "mediapipe/framework/port/ret_check.h"
 #include "mediapipe/util/tflite/config.h"
@@ -112,8 +109,8 @@ std::unique_ptr<tflite::Interpreter> BuildEdgeTpuInterpreter(
    edgetpu::EdgeTpuContext* edgetpu_context) {
  resolver->AddCustom(edgetpu::kCustomOp, edgetpu::RegisterCustomOp());
  std::unique_ptr<tflite::Interpreter> interpreter;
-  ABSL_CHECK_EQ(tflite::InterpreterBuilder(model, *resolver)(&interpreter),
+  CHECK_EQ(tflite::InterpreterBuilder(model, *resolver)(&interpreter),
-                kTfLiteOk);
+           kTfLiteOk);
  interpreter->SetExternalContext(kTfLiteEdgeTpuContext, edgetpu_context);
  return interpreter;
 }
@@ -409,12 +406,11 @@ absl::Status TfLiteInferenceCalculator::Open(CalculatorContext* cc) {
  }
  if (use_advanced_gpu_api_ && !gpu_input_) {
-    ABSL_LOG(WARNING)
+    LOG(WARNING) << "Cannot use advanced GPU APIs, input must be GPU buffers."
-        << "Cannot use advanced GPU APIs, input must be GPU buffers."
+                    "Falling back to the default TFLite API.";
           "Falling back to the default TFLite API.";
    use_advanced_gpu_api_ = false;
  }
-  ABSL_CHECK(!use_advanced_gpu_api_ || gpu_inference_);
+  CHECK(!use_advanced_gpu_api_ || gpu_inference_);
  MP_RETURN_IF_ERROR(LoadModel(cc));
@@ -806,10 +802,9 @@ absl::Status TfLiteInferenceCalculator::InitTFLiteGPURunner(
      const int tensor_idx = interpreter_->inputs()[i];
      interpreter_->SetTensorParametersReadWrite(tensor_idx, kTfLiteFloat32, "",
                                                 shape, quant);
-      ABSL_CHECK(interpreter_->ResizeInputTensor(tensor_idx, shape) ==
+      CHECK(interpreter_->ResizeInputTensor(tensor_idx, shape) == kTfLiteOk);
                 kTfLiteOk);
    }
-    ABSL_CHECK(interpreter_->AllocateTensors() == kTfLiteOk);
+    CHECK(interpreter_->AllocateTensors() == kTfLiteOk);
  }
  // Create and bind OpenGL buffers for outputs.
@@ -1058,7 +1053,7 @@ absl::Status TfLiteInferenceCalculator::LoadDelegate(CalculatorContext* cc) {
          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) {
-        ABSL_LOG(WARNING) << "Please ensure input GPU tensor is 4 channels.";
+        LOG(WARNING) << "Please ensure input GPU tensor is 4 channels.";
      }
      const std::string shader_source =
          absl::Substitute(R"(#include <metal_stdlib>
@@ -17,7 +17,6 @@
 #include <vector>
 #include "absl/container/node_hash_map.h"
 #include "absl/log/absl_check.h"
 #include "absl/strings/str_format.h"
 #include "absl/types/span.h"
 #include "mediapipe/calculators/tflite/tflite_tensors_to_classification_calculator.pb.h"
@@ -173,7 +172,7 @@ absl::Status TfLiteTensorsToClassificationCalculator::Process(
  // Note that partial_sort will raise error when top_k_ >
  // classification_list->classification_size().
-  ABSL_CHECK_GE(classification_list->classification_size(), top_k_);
+  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(),
@@ -15,8 +15,6 @@
 #include <unordered_map>
 #include <vector>
 #include "absl/log/absl_check.h"
 #include "absl/log/absl_log.h"
 #include "absl/strings/str_format.h"
 #include "absl/types/span.h"
 #include "mediapipe/calculators/tflite/tflite_tensors_to_detections_calculator.pb.h"
@@ -95,7 +93,7 @@ void ConvertRawValuesToAnchors(const float* raw_anchors, int num_boxes,
 void ConvertAnchorsToRawValues(const std::vector<Anchor>& anchors,
                               int num_boxes, float* raw_anchors) {
-  ABSL_CHECK_EQ(anchors.size(), num_boxes);
+  CHECK_EQ(anchors.size(), num_boxes);
  int box = 0;
  for (const auto& anchor : anchors) {
    raw_anchors[box * kNumCoordsPerBox + 0] = anchor.y_center();
@@ -290,14 +288,14 @@ absl::Status TfLiteTensorsToDetectionsCalculator::ProcessCPU(
    const TfLiteTensor* raw_score_tensor = &input_tensors[1];
    // TODO: Add flexible input tensor size handling.
-    ABSL_CHECK_EQ(raw_box_tensor->dims->size, 3);
+    CHECK_EQ(raw_box_tensor->dims->size, 3);
-    ABSL_CHECK_EQ(raw_box_tensor->dims->data[0], 1);
+    CHECK_EQ(raw_box_tensor->dims->data[0], 1);
-    ABSL_CHECK_EQ(raw_box_tensor->dims->data[1], num_boxes_);
+    CHECK_EQ(raw_box_tensor->dims->data[1], num_boxes_);
-    ABSL_CHECK_EQ(raw_box_tensor->dims->data[2], num_coords_);
+    CHECK_EQ(raw_box_tensor->dims->data[2], num_coords_);
-    ABSL_CHECK_EQ(raw_score_tensor->dims->size, 3);
+    CHECK_EQ(raw_score_tensor->dims->size, 3);
-    ABSL_CHECK_EQ(raw_score_tensor->dims->data[0], 1);
+    CHECK_EQ(raw_score_tensor->dims->data[0], 1);
-    ABSL_CHECK_EQ(raw_score_tensor->dims->data[1], num_boxes_);
+    CHECK_EQ(raw_score_tensor->dims->data[1], num_boxes_);
-    ABSL_CHECK_EQ(raw_score_tensor->dims->data[2], num_classes_);
+    CHECK_EQ(raw_score_tensor->dims->data[2], num_classes_);
    const float* raw_boxes = raw_box_tensor->data.f;
    const float* raw_scores = raw_score_tensor->data.f;
@@ -305,13 +303,13 @@ absl::Status TfLiteTensorsToDetectionsCalculator::ProcessCPU(
    if (!anchors_init_) {
      if (input_tensors.size() == kNumInputTensorsWithAnchors) {
        const TfLiteTensor* anchor_tensor = &input_tensors[2];
-        ABSL_CHECK_EQ(anchor_tensor->dims->size, 2);
+        CHECK_EQ(anchor_tensor->dims->size, 2);
-        ABSL_CHECK_EQ(anchor_tensor->dims->data[0], num_boxes_);
+        CHECK_EQ(anchor_tensor->dims->data[0], num_boxes_);
-        ABSL_CHECK_EQ(anchor_tensor->dims->data[1], kNumCoordsPerBox);
+        CHECK_EQ(anchor_tensor->dims->data[1], kNumCoordsPerBox);
        const float* raw_anchors = anchor_tensor->data.f;
        ConvertRawValuesToAnchors(raw_anchors, num_boxes_, &anchors_);
      } else if (side_packet_anchors_) {
-        ABSL_CHECK(!cc->InputSidePackets().Tag("ANCHORS").IsEmpty());
+        CHECK(!cc->InputSidePackets().Tag("ANCHORS").IsEmpty());
        anchors_ =
            cc->InputSidePackets().Tag("ANCHORS").Get<std::vector<Anchor>>();
      } else {
@@ -411,7 +409,7 @@ absl::Status TfLiteTensorsToDetectionsCalculator::ProcessGPU(
        CopyBuffer(input_tensors[1], gpu_data_->raw_scores_buffer));
    if (!anchors_init_) {
      if (side_packet_anchors_) {
-        ABSL_CHECK(!cc->InputSidePackets().Tag("ANCHORS").IsEmpty());
+        CHECK(!cc->InputSidePackets().Tag("ANCHORS").IsEmpty());
        const auto& anchors =
            cc->InputSidePackets().Tag("ANCHORS").Get<std::vector<Anchor>>();
        std::vector<float> raw_anchors(num_boxes_ * kNumCoordsPerBox);
@@ -419,7 +417,7 @@ absl::Status TfLiteTensorsToDetectionsCalculator::ProcessGPU(
        MP_RETURN_IF_ERROR(gpu_data_->raw_anchors_buffer.Write<float>(
            absl::MakeSpan(raw_anchors)));
      } else {
-        ABSL_CHECK_EQ(input_tensors.size(), kNumInputTensorsWithAnchors);
+        CHECK_EQ(input_tensors.size(), kNumInputTensorsWithAnchors);
        MP_RETURN_IF_ERROR(
            CopyBuffer(input_tensors[2], gpu_data_->raw_anchors_buffer));
      }
@@ -479,7 +477,7 @@ absl::Status TfLiteTensorsToDetectionsCalculator::ProcessGPU(
                    commandBuffer:[gpu_helper_ commandBuffer]];
  if (!anchors_init_) {
    if (side_packet_anchors_) {
-      ABSL_CHECK(!cc->InputSidePackets().Tag("ANCHORS").IsEmpty());
+      CHECK(!cc->InputSidePackets().Tag("ANCHORS").IsEmpty());
      const auto& anchors =
          cc->InputSidePackets().Tag("ANCHORS").Get<std::vector<Anchor>>();
      std::vector<float> raw_anchors(num_boxes_ * kNumCoordsPerBox);
@@ -543,7 +541,7 @@ absl::Status TfLiteTensorsToDetectionsCalculator::ProcessGPU(
                                         output_detections));
 #else
-  ABSL_LOG(ERROR) << "GPU input on non-Android not supported yet.";
+  LOG(ERROR) << "GPU input on non-Android not supported yet.";
 #endif  // MEDIAPIPE_TFLITE_GL_INFERENCE
  return absl::OkStatus();
 }
@@ -569,12 +567,12 @@ absl::Status TfLiteTensorsToDetectionsCalculator::LoadOptions(
  num_coords_ = options_.num_coords();
  // Currently only support 2D when num_values_per_keypoint equals to 2.
-  ABSL_CHECK_EQ(options_.num_values_per_keypoint(), 2);
+  CHECK_EQ(options_.num_values_per_keypoint(), 2);
  // Check if the output size is equal to the requested boxes and keypoints.
-  ABSL_CHECK_EQ(options_.num_keypoints() * options_.num_values_per_keypoint() +
+  CHECK_EQ(options_.num_keypoints() * options_.num_values_per_keypoint() +
-                    kNumCoordsPerBox,
+               kNumCoordsPerBox,
-                num_coords_);
+           num_coords_);
  for (int i = 0; i < options_.ignore_classes_size(); ++i) {
    ignore_classes_.insert(options_.ignore_classes(i));
@@ -899,11 +897,10 @@ void main() {
    int max_wg_size;  //  typically <= 1024
    glGetIntegeri_v(GL_MAX_COMPUTE_WORK_GROUP_SIZE, 1,
                    &max_wg_size);  // y-dim
-    ABSL_CHECK_LT(num_classes_, max_wg_size)
+    CHECK_LT(num_classes_, max_wg_size)
        << "# classes must be < " << max_wg_size;
    // TODO support better filtering.
-    ABSL_CHECK_LE(ignore_classes_.size(), 1)
+    CHECK_LE(ignore_classes_.size(), 1) << "Only ignore class 0 is allowed";
        << "Only ignore class 0 is allowed";
    // Shader program
    GlShader score_shader;
@@ -1118,7 +1115,7 @@ kernel void scoreKernel(
      ignore_classes_.size() ? 1 : 0);
  // TODO support better filtering.
-  ABSL_CHECK_LE(ignore_classes_.size(), 1) << "Only ignore class 0 is allowed";
+  CHECK_LE(ignore_classes_.size(), 1) << "Only ignore class 0 is allowed";
  {
    // Shader program
@@ -1150,8 +1147,7 @@ kernel void scoreKernel(
                            options:MTLResourceStorageModeShared];
    // # filter classes supported is hardware dependent.
    int max_wg_size = gpu_data_->score_program.maxTotalThreadsPerThreadgroup;
-    ABSL_CHECK_LT(num_classes_, max_wg_size)
+    CHECK_LT(num_classes_, max_wg_size) << "# classes must be <" << max_wg_size;
        << "# classes must be <" << max_wg_size;
  }
 #endif  // MEDIAPIPE_TFLITE_GL_INFERENCE
@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "absl/log/absl_check.h"
 #include "mediapipe/calculators/tflite/tflite_tensors_to_landmarks_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/formats/landmark.pb.h"
@@ -200,7 +199,7 @@ absl::Status TfLiteTensorsToLandmarksCalculator::Process(
    num_values *= raw_tensor->dims->data[i];
  }
  const int num_dimensions = num_values / num_landmarks_;
-  ABSL_CHECK_GT(num_dimensions, 0);
+  CHECK_GT(num_dimensions, 0);
  const float* raw_landmarks = raw_tensor->data.f;
@@ -183,9 +183,9 @@ cc_library(
        "//mediapipe/framework:calculator_options_cc_proto",
        "//mediapipe/framework:timestamp",
        "//mediapipe/framework/deps:clock",
        "//mediapipe/framework/port:logging",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_absl//absl/strings",
        "@com_google_absl//absl/time",
    ],
@@ -248,12 +248,11 @@ cc_library(
        ":annotation_overlay_calculator_cc_proto",
        "//mediapipe/framework:calculator_framework",
        "//mediapipe/framework:calculator_options_cc_proto",
        "//mediapipe/framework/formats:image",
        "//mediapipe/framework/formats:image_format_cc_proto",
        "//mediapipe/framework/formats:image_frame",
        "//mediapipe/framework/formats:image_frame_opencv",
        "//mediapipe/framework/formats:image_opencv",
        "//mediapipe/framework/formats:video_stream_header",
        "//mediapipe/framework/port:logging",
        "//mediapipe/framework/port:opencv_core",
        "//mediapipe/framework/port:opencv_imgproc",
        "//mediapipe/framework/port:status",
@@ -261,7 +260,6 @@ cc_library(
        "//mediapipe/util:annotation_renderer",
        "//mediapipe/util:color_cc_proto",
        "//mediapipe/util:render_data_cc_proto",
        "@com_google_absl//absl/log:absl_log",
        "@com_google_absl//absl/strings",
    ] + select({
        "//mediapipe/gpu:disable_gpu": [],
@@ -269,7 +267,6 @@ cc_library(
            "//mediapipe/gpu:gl_calculator_helper",
            "//mediapipe/gpu:gl_simple_shaders",
            "//mediapipe/gpu:gpu_buffer",
            "//mediapipe/gpu:gpu_buffer_format",
            "//mediapipe/gpu:shader_util",
        ],
    }),
@@ -377,10 +374,9 @@ cc_library(
        "//mediapipe/framework/formats:detection_cc_proto",
        "//mediapipe/framework/formats:image_frame",
        "//mediapipe/framework/formats:location",
        "//mediapipe/framework/port:logging",
        "//mediapipe/framework/port:rectangle",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/log:absl_log",
    ],
    alwayslink = 1,
 )
@@ -679,7 +675,6 @@ cc_library(
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/util:color_cc_proto",
        "//mediapipe/util:render_data_cc_proto",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/memory",
        "@com_google_absl//absl/strings",
    ],
@@ -736,7 +731,6 @@ cc_library(
        "//mediapipe/framework/port:statusor",
        "//mediapipe/util:color_cc_proto",
        "//mediapipe/util:render_data_cc_proto",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/strings",
    ],
    alwayslink = 1,
@@ -752,7 +746,6 @@ cc_library(
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/util:color_cc_proto",
        "//mediapipe/util:render_data_cc_proto",
        "@com_google_absl//absl/log:absl_check",
    ],
    alwayslink = 1,
 )
@@ -1156,7 +1149,6 @@ cc_library(
        "//mediapipe/framework/port:file_helpers",
        "//mediapipe/framework/port:ret_check",
        "//mediapipe/framework/port:status",
        "@com_google_absl//absl/log:absl_log",
    ],
    alwayslink = 1,
 )
@@ -1217,7 +1209,6 @@ cc_library(
        "//mediapipe/framework/port:rectangle",
        "//mediapipe/framework/port:status",
        "//mediapipe/util:rectangle_util",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/memory",
    ],
    alwayslink = 1,
@@ -1489,7 +1480,6 @@ cc_library(
        "//mediapipe/framework/formats:landmark_cc_proto",
        "//mediapipe/framework/port:core_proto",
        "//mediapipe/framework/port:ret_check",
        "@com_google_absl//absl/log:absl_check",
        "@com_google_absl//absl/memory",
    ],
    alwayslink = 1,
@@ -14,17 +14,15 @@
 #include <memory>
 #include "absl/log/absl_log.h"
 #include "absl/strings/str_cat.h"
 #include "mediapipe/calculators/util/annotation_overlay_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/calculator_options.pb.h"
 #include "mediapipe/framework/formats/image.h"
 #include "mediapipe/framework/formats/image_format.pb.h"
 #include "mediapipe/framework/formats/image_frame.h"
 #include "mediapipe/framework/formats/image_frame_opencv.h"
 #include "mediapipe/framework/formats/image_opencv.h"
 #include "mediapipe/framework/formats/video_stream_header.h"
 #include "mediapipe/framework/port/logging.h"
 #include "mediapipe/framework/port/opencv_core_inc.h"
 #include "mediapipe/framework/port/opencv_imgproc_inc.h"
 #include "mediapipe/framework/port/status.h"
@@ -37,7 +35,6 @@
 #include "mediapipe/gpu/gl_calculator_helper.h"
 #include "mediapipe/gpu/gl_simple_shaders.h"
 #include "mediapipe/gpu/gpu_buffer.h"
 #include "mediapipe/gpu/gpu_buffer_format.h"
 #include "mediapipe/gpu/shader_util.h"
 #endif  // !MEDIAPIPE_DISABLE_GPU
@@ -48,7 +45,6 @@ namespace {
 constexpr char kVectorTag[] = "VECTOR";
 constexpr char kGpuBufferTag[] = "IMAGE_GPU";
 constexpr char kImageFrameTag[] = "IMAGE";
 constexpr char kImageTag[] = "UIMAGE";  // Universal Image
 enum { ATTRIB_VERTEX, ATTRIB_TEXTURE_POSITION, NUM_ATTRIBUTES };
@@ -61,16 +57,13 @@ size_t RoundUp(size_t n, size_t m) { return ((n + m - 1) / m) * m; }  // NOLINT
 constexpr uchar kAnnotationBackgroundColor = 2;  // Grayscale value.
 // Future Image type.
-inline bool HasImageTag(mediapipe::CalculatorContext* cc) {
+inline bool HasImageTag(mediapipe::CalculatorContext* cc) { return false; }
  return cc->Inputs().HasTag(kImageTag);
 }
 }  // namespace
 // A calculator for rendering data on images.
 //
 // Inputs:
 //  1. IMAGE or IMAGE_GPU (optional): An ImageFrame (or GpuBuffer),
 //     or UIMAGE (an Image).
 //     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.
@@ -83,7 +76,6 @@ inline bool HasImageTag(mediapipe::CalculatorContext* cc) {
 //
 // Output:
 //  1. IMAGE or IMAGE_GPU: A rendered ImageFrame (or GpuBuffer),
 //     or UIMAGE (an Image).
 //  Note: Output types should match their corresponding input stream type.
 //
 // For CPU input frames, only SRGBA, SRGB and GRAY8 format are supported. The
@@ -143,9 +135,6 @@ class AnnotationOverlayCalculator : public CalculatorBase {
  absl::Status CreateRenderTargetCpu(CalculatorContext* cc,
                                     std::unique_ptr<cv::Mat>& image_mat,
                                     ImageFormat::Format* target_format);
  absl::Status CreateRenderTargetCpuImage(CalculatorContext* cc,
                                          std::unique_ptr<cv::Mat>& image_mat,
                                          ImageFormat::Format* target_format);
  template <typename Type, const char* Tag>
  absl::Status CreateRenderTargetGpu(CalculatorContext* cc,
                                     std::unique_ptr<cv::Mat>& image_mat);
@@ -183,38 +172,30 @@ class AnnotationOverlayCalculator : public CalculatorBase {
 REGISTER_CALCULATOR(AnnotationOverlayCalculator);
 absl::Status AnnotationOverlayCalculator::GetContract(CalculatorContract* cc) {
-  RET_CHECK_GE(cc->Inputs().NumEntries(), 1);
+  CHECK_GE(cc->Inputs().NumEntries(), 1);
  bool use_gpu = false;
-  RET_CHECK(cc->Inputs().HasTag(kImageFrameTag) +
+  if (cc->Inputs().HasTag(kImageFrameTag) &&
-                cc->Inputs().HasTag(kGpuBufferTag) +
+      cc->Inputs().HasTag(kGpuBufferTag)) {
-                cc->Inputs().HasTag(kImageTag) <=
+    return absl::InternalError("Cannot have multiple input images.");
-            1);
+  }
-  RET_CHECK(cc->Outputs().HasTag(kImageFrameTag) +
+  if (cc->Inputs().HasTag(kGpuBufferTag) !=
-                cc->Outputs().HasTag(kGpuBufferTag) +
+      cc->Outputs().HasTag(kGpuBufferTag)) {
-                cc->Outputs().HasTag(kImageTag) ==
+    return absl::InternalError("GPU output must have GPU input.");
-            1);
+  }
  // Input image to render onto copy of. Should be same type as output.
 #if !MEDIAPIPE_DISABLE_GPU
  if (cc->Inputs().HasTag(kGpuBufferTag)) {
    cc->Inputs().Tag(kGpuBufferTag).Set<mediapipe::GpuBuffer>();
-    RET_CHECK(cc->Outputs().HasTag(kGpuBufferTag));
+    CHECK(cc->Outputs().HasTag(kGpuBufferTag));
    use_gpu = true;
  }
 #endif  // !MEDIAPIPE_DISABLE_GPU
  if (cc->Inputs().HasTag(kImageFrameTag)) {
    cc->Inputs().Tag(kImageFrameTag).Set<ImageFrame>();
-    RET_CHECK(cc->Outputs().HasTag(kImageFrameTag));
+    CHECK(cc->Outputs().HasTag(kImageFrameTag));
  }
  if (cc->Inputs().HasTag(kImageTag)) {
    cc->Inputs().Tag(kImageTag).Set<mediapipe::Image>();
    RET_CHECK(cc->Outputs().HasTag(kImageTag));
 #if !MEDIAPIPE_DISABLE_GPU
    use_gpu = true;  // Prepare GPU resources because images can come in on GPU.
 #endif
  }
  // Data streams to render.
@@ -239,9 +220,6 @@ absl::Status AnnotationOverlayCalculator::GetContract(CalculatorContract* cc) {
  if (cc->Outputs().HasTag(kImageFrameTag)) {
    cc->Outputs().Tag(kImageFrameTag).Set<ImageFrame>();
  }
  if (cc->Outputs().HasTag(kImageTag)) {
    cc->Outputs().Tag(kImageTag).Set<mediapipe::Image>();
  }
  if (use_gpu) {
 #if !MEDIAPIPE_DISABLE_GPU
@@ -274,14 +252,9 @@ absl::Status AnnotationOverlayCalculator::Open(CalculatorContext* cc) {
  renderer_ = absl::make_unique<AnnotationRenderer>();
  renderer_->SetFlipTextVertically(options_.flip_text_vertically());
  if (use_gpu_) renderer_->SetScaleFactor(options_.gpu_scale_factor());
  if (renderer_->GetScaleFactor() < 1.0 && HasImageTag(cc))
    ABSL_LOG(WARNING)
        << "Annotation scale factor only supports GPU backed Image.";
  // Set the output header based on the input header (if present).
-  const char* tag = HasImageTag(cc) ? kImageTag
+  const char* tag = use_gpu_ ? kGpuBufferTag : kImageFrameTag;
                    : use_gpu_      ? kGpuBufferTag
                                    : kImageFrameTag;
  if (image_frame_available_ && !cc->Inputs().Tag(tag).Header().IsEmpty()) {
    const auto& input_header =
        cc->Inputs().Tag(tag).Header().Get<VideoHeader>();
@@ -307,12 +280,6 @@ absl::Status AnnotationOverlayCalculator::Process(CalculatorContext* cc) {
      cc->Inputs().Tag(kImageFrameTag).IsEmpty()) {
    return absl::OkStatus();
  }
  if (cc->Inputs().HasTag(kImageTag) && cc->Inputs().Tag(kImageTag).IsEmpty()) {
    return absl::OkStatus();
  }
  if (HasImageTag(cc)) {
    use_gpu_ = cc->Inputs().Tag(kImageTag).Get<mediapipe::Image>().UsesGpu();
  }
  // Initialize render target, drawn with OpenCV.
  std::unique_ptr<cv::Mat> image_mat;
@@ -322,17 +289,10 @@ absl::Status AnnotationOverlayCalculator::Process(CalculatorContext* cc) {
    if (!gpu_initialized_) {
      MP_RETURN_IF_ERROR(
          gpu_helper_.RunInGlContext([this, cc]() -> absl::Status {
            if (HasImageTag(cc)) {
              return GlSetup<mediapipe::Image, kImageTag>(cc);
            }
            return GlSetup<mediapipe::GpuBuffer, kGpuBufferTag>(cc);
          }));
      gpu_initialized_ = true;
    }
    if (HasImageTag(cc)) {
      MP_RETURN_IF_ERROR(
          (CreateRenderTargetGpu<mediapipe::Image, kImageTag>(cc, image_mat)));
    }
    if (cc->Inputs().HasTag(kGpuBufferTag)) {
      MP_RETURN_IF_ERROR(
          (CreateRenderTargetGpu<mediapipe::GpuBuffer, kGpuBufferTag>(
@@ -340,10 +300,6 @@ absl::Status AnnotationOverlayCalculator::Process(CalculatorContext* cc) {
    }
 #endif  // !MEDIAPIPE_DISABLE_GPU
  } else {
    if (cc->Outputs().HasTag(kImageTag)) {
      MP_RETURN_IF_ERROR(
          CreateRenderTargetCpuImage(cc, image_mat, &target_format));
    }
    if (cc->Outputs().HasTag(kImageFrameTag)) {
      MP_RETURN_IF_ERROR(CreateRenderTargetCpu(cc, image_mat, &target_format));
    }
@@ -383,9 +339,6 @@ absl::Status AnnotationOverlayCalculator::Process(CalculatorContext* cc) {
    uchar* image_mat_ptr = image_mat->data;
    MP_RETURN_IF_ERROR(
        gpu_helper_.RunInGlContext([this, cc, image_mat_ptr]() -> absl::Status {
          if (HasImageTag(cc)) {
            return RenderToGpu<mediapipe::Image, kImageTag>(cc, image_mat_ptr);
          }
          return RenderToGpu<mediapipe::GpuBuffer, kGpuBufferTag>(
              cc, image_mat_ptr);
        }));
@@ -428,10 +381,6 @@ absl::Status AnnotationOverlayCalculator::RenderToCpu(
                              ImageFrame::kDefaultAlignmentBoundary);
 #endif  // !MEDIAPIPE_DISABLE_GPU
  if (HasImageTag(cc)) {
    auto out = std::make_unique<mediapipe::Image>(std::move(output_frame));
    cc->Outputs().Tag(kImageTag).Add(out.release(), cc->InputTimestamp());
  }
  if (cc->Outputs().HasTag(kImageFrameTag)) {
    cc->Outputs()
        .Tag(kImageFrameTag)
@@ -450,8 +399,7 @@ absl::Status AnnotationOverlayCalculator::RenderToGpu(CalculatorContext* cc,
  auto input_texture = gpu_helper_.CreateSourceTexture(input_frame);
  auto output_texture = gpu_helper_.CreateDestinationTexture(
-      input_texture.width(), input_texture.height(),
+      width_, height_, mediapipe::GpuBufferFormat::kBGRA32);
      mediapipe::GpuBufferFormat::kBGRA32);
  // Upload render target to GPU.
  {
@@ -480,7 +428,7 @@ absl::Status AnnotationOverlayCalculator::RenderToGpu(CalculatorContext* cc,
  }
  // Send out blended image as GPU packet.
-  auto output_frame = output_texture.template GetFrame<Type>();
+  auto output_frame = output_texture.GetFrame<Type>();
  cc->Outputs().Tag(Tag).Add(output_frame.release(), cc->InputTimestamp());
  // Cleanup
@@ -539,54 +487,6 @@ absl::Status AnnotationOverlayCalculator::CreateRenderTargetCpu(
  return absl::OkStatus();
 }
 absl::Status AnnotationOverlayCalculator::CreateRenderTargetCpuImage(
    CalculatorContext* cc, std::unique_ptr<cv::Mat>& image_mat,
    ImageFormat::Format* target_format) {
  if (image_frame_available_) {
    const auto& input_frame =
        cc->Inputs().Tag(kImageTag).Get<mediapipe::Image>();
    int target_mat_type;
    switch (input_frame.image_format()) {
      case ImageFormat::SRGBA:
        *target_format = ImageFormat::SRGBA;
        target_mat_type = CV_8UC4;
        break;
      case ImageFormat::SRGB:
        *target_format = ImageFormat::SRGB;
        target_mat_type = CV_8UC3;
        break;
      case ImageFormat::GRAY8:
        *target_format = ImageFormat::SRGB;
        target_mat_type = CV_8UC3;
        break;
      default:
        return absl::UnknownError("Unexpected image frame format.");
        break;
    }
    image_mat = absl::make_unique<cv::Mat>(
        input_frame.height(), input_frame.width(), target_mat_type);
    auto input_mat = formats::MatView(&input_frame);
    if (input_frame.image_format() == ImageFormat::GRAY8) {
      cv::Mat rgb_mat;
      cv::cvtColor(*input_mat, rgb_mat, cv::COLOR_GRAY2RGB);
      rgb_mat.copyTo(*image_mat);
    } else {
      input_mat->copyTo(*image_mat);
    }
  } else {
    image_mat = absl::make_unique<cv::Mat>(
        options_.canvas_height_px(), options_.canvas_width_px(), CV_8UC3,
        cv::Scalar(options_.canvas_color().r(), options_.canvas_color().g(),
                   options_.canvas_color().b()));
    *target_format = ImageFormat::SRGB;
  }
  return absl::OkStatus();
 }
 template <typename Type, const char* Tag>
 absl::Status AnnotationOverlayCalculator::CreateRenderTargetGpu(
    CalculatorContext* cc, std::unique_ptr<cv::Mat>& image_mat) {
@@ -18,7 +18,6 @@
 #include <memory>
 #include <vector>
 #include "absl/log/absl_check.h"
 #include "absl/memory/memory.h"
 #include "mediapipe/calculators/util/association_calculator.pb.h"
 #include "mediapipe/framework/calculator_context.h"
@@ -73,7 +72,7 @@ class AssociationCalculator : public CalculatorBase {
      prev_input_stream_id_ = cc->Inputs().GetId("PREV", 0);
    }
    options_ = cc->Options<::mediapipe::AssociationCalculatorOptions>();
-    ABSL_CHECK_GE(options_.min_similarity_threshold(), 0);
+    CHECK_GE(options_.min_similarity_threshold(), 0);
    return absl::OkStatus();
  }
@@ -19,7 +19,6 @@
 #include "mediapipe/framework/port/integral_types.h"
 #include "mediapipe/framework/port/proto_ns.h"
 #include "mediapipe/framework/port/status.h"
 #include "mediapipe/framework/port/status_macros.h"
 #include "mediapipe/util/label_map.pb.h"
 #include "mediapipe/util/resource_util.h"
@@ -86,8 +85,7 @@ absl::Status DetectionLabelIdToTextCalculator::Open(CalculatorContext* cc) {
    ASSIGN_OR_RETURN(string_path,
                     PathToResourceAsFile(options.label_map_path()));
    std::string label_map_string;
-    MP_RETURN_IF_ERROR(
+    MP_RETURN_IF_ERROR(file::GetContents(string_path, &label_map_string));
        mediapipe::GetResourceContents(string_path, &label_map_string));
    std::istringstream stream(label_map_string);
    std::string line;
@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "absl/log/absl_check.h"
 #include "absl/memory/memory.h"
 #include "absl/strings/str_cat.h"
 #include "absl/strings/str_join.h"
@@ -234,13 +233,13 @@ void DetectionsToRenderDataCalculator::AddLabels(
    const Detection& detection,
    const DetectionsToRenderDataCalculatorOptions& options,
    float text_line_height, RenderData* render_data) {
-  ABSL_CHECK(detection.label().empty() || detection.label_id().empty() ||
+  CHECK(detection.label().empty() || detection.label_id().empty() ||
-             detection.label_size() == detection.label_id_size())
+        detection.label_size() == detection.label_id_size())
      << "String or integer labels should be of same size. Or only one of them "
         "is present.";
  const auto num_labels =
      std::max(detection.label_size(), detection.label_id_size());
-  ABSL_CHECK_EQ(detection.score_size(), num_labels)
+  CHECK_EQ(detection.score_size(), num_labels)
      << "Number of scores and labels should match for detection.";
  // Extracts all "label(_id),score" for the detection.
@@ -362,9 +361,9 @@ void DetectionsToRenderDataCalculator::AddDetectionToRenderData(
    const Detection& detection,
    const DetectionsToRenderDataCalculatorOptions& options,
    RenderData* render_data) {
-  ABSL_CHECK(detection.location_data().format() == LocationData::BOUNDING_BOX ||
+  CHECK(detection.location_data().format() == LocationData::BOUNDING_BOX ||
-             detection.location_data().format() ==
+        detection.location_data().format() ==
-                 LocationData::RELATIVE_BOUNDING_BOX)
+            LocationData::RELATIVE_BOUNDING_BOX)
      << "Only Detection with formats of BOUNDING_BOX or RELATIVE_BOUNDING_BOX "
         "are supported.";
  double text_line_height;
@@ -19,7 +19,6 @@
 #include <string>
 #include <vector>
 #include "absl/log/absl_check.h"
 #include "absl/strings/str_cat.h"
 #include "mediapipe/calculators/util/labels_to_render_data_calculator.pb.h"
 #include "mediapipe/framework/calculator_framework.h"
@@ -115,8 +114,7 @@ absl::Status LabelsToRenderDataCalculator::Process(CalculatorContext* cc) {
    video_height_ = video_header.height;
    return absl::OkStatus();
  } else {
-    ABSL_CHECK_EQ(options_.location(),
+    CHECK_EQ(options_.location(), LabelsToRenderDataCalculatorOptions::TOP_LEFT)
                  LabelsToRenderDataCalculatorOptions::TOP_LEFT)
        << "Only TOP_LEFT is supported without VIDEO_PRESTREAM.";
  }
@@ -146,7 +144,7 @@ absl::Status LabelsToRenderDataCalculator::Process(CalculatorContext* cc) {
    if (cc->Inputs().HasTag(kScoresTag)) {
      std::vector<float> score_vector =
          cc->Inputs().Tag(kScoresTag).Get<std::vector<float>>();
-      ABSL_CHECK_EQ(label_vector.size(), score_vector.size());
+      CHECK_EQ(label_vector.size(), score_vector.size());
      scores.resize(label_vector.size());
      for (int i = 0; i < label_vector.size(); ++i) {
        scores[i] = score_vector[i];
--- a/Show More
+++ b/Show More