Project import generated by Copybara.

GitOrigin-RevId: 08c2016a4df5aef571b464a4d4491f38c6b2af10

mediapipe/graphs/face_detection/face_detection_back_desktop_live.pbtxt

@@ -40,8 +40,8 @@ node: {
   output_stream: "LETTERBOX_PADDING:letterbox_padding"
   node_options: {
     [type.googleapis.com/mediapipe.ImageTransformationCalculatorOptions] {
-      output_width: 256
-      output_height: 256
+      output_width: 192
+      output_height: 192
       scale_mode: FIT
     }
   }
@@ -76,19 +76,17 @@ node {
   output_side_packet: "anchors"
   node_options: {
     [type.googleapis.com/mediapipe.SsdAnchorsCalculatorOptions] {
-      num_layers: 4
-      min_scale: 0.15625
+      num_layers: 1
+      min_scale: 0.1484375
       max_scale: 0.75
-      input_size_height: 256
-      input_size_width: 256
+      input_size_height: 192
+      input_size_width: 192
       anchor_offset_x: 0.5
       anchor_offset_y: 0.5
-      strides: 16
-      strides: 32
-      strides: 32
-      strides: 32
+      strides: 4
       aspect_ratios: 1.0
       fixed_anchor_size: true
+      interpolated_scale_aspect_ratio: 0.0
     }
   }
 }
@@ -104,7 +102,7 @@ node {
   node_options: {
     [type.googleapis.com/mediapipe.TfLiteTensorsToDetectionsCalculatorOptions] {
       num_classes: 1
-      num_boxes: 896
+      num_boxes: 2304
       num_coords: 16
       box_coord_offset: 0
       keypoint_coord_offset: 4
@@ -113,11 +111,11 @@ node {
       sigmoid_score: true
       score_clipping_thresh: 100.0
       reverse_output_order: true
-      x_scale: 256.0
-      y_scale: 256.0
-      h_scale: 256.0
-      w_scale: 256.0
-      min_score_thresh: 0.65
+      x_scale: 192.0
+      y_scale: 192.0
+      h_scale: 192.0
+      w_scale: 192.0
+      min_score_thresh: 0.6
     }
   }
 }

mediapipe/graphs/face_detection/face_detection_back_mobile_gpu.pbtxt

@@ -41,8 +41,8 @@ node: {
   output_stream: "LETTERBOX_PADDING:letterbox_padding"
   node_options: {
     [type.googleapis.com/mediapipe.ImageTransformationCalculatorOptions] {
-      output_width: 256
-      output_height: 256
+      output_width: 192
+      output_height: 192
       scale_mode: FIT
     }
   }
@@ -77,19 +77,17 @@ node {
   output_side_packet: "anchors"
   node_options: {
     [type.googleapis.com/mediapipe.SsdAnchorsCalculatorOptions] {
-      num_layers: 4
-      min_scale: 0.15625
+      num_layers: 1
+      min_scale: 0.1484375
       max_scale: 0.75
-      input_size_height: 256
-      input_size_width: 256
+      input_size_height: 192
+      input_size_width: 192
       anchor_offset_x: 0.5
       anchor_offset_y: 0.5
-      strides: 16
-      strides: 32
-      strides: 32
-      strides: 32
+      strides: 4
       aspect_ratios: 1.0
       fixed_anchor_size: true
+      interpolated_scale_aspect_ratio: 0.0
     }
   }
 }
@@ -105,7 +103,7 @@ node {
   node_options: {
     [type.googleapis.com/mediapipe.TfLiteTensorsToDetectionsCalculatorOptions] {
       num_classes: 1
-      num_boxes: 896
+      num_boxes: 2304
       num_coords: 16
       box_coord_offset: 0
       keypoint_coord_offset: 4
@@ -114,11 +112,11 @@ node {
       sigmoid_score: true
       score_clipping_thresh: 100.0
       reverse_output_order: true
-      x_scale: 256.0
-      y_scale: 256.0
-      h_scale: 256.0
-      w_scale: 256.0
-      min_score_thresh: 0.65
+      x_scale: 192.0
+      y_scale: 192.0
+      h_scale: 192.0
+      w_scale: 192.0
+      min_score_thresh: 0.6
     }
   }
 }

mediapipe/graphs/instant_motion_tracking/calculators/matrices_manager_calculator.cc

@@ -15,9 +15,9 @@
 #include <cmath>
 #include <memory>
 
+#include "Eigen/Core"
 #include "Eigen/Dense"
-#include "Eigen/src/Core/util/Constants.h"
-#include "Eigen/src/Geometry/Quaternion.h"
+#include "Eigen/Geometry"
 #include "absl/memory/memory.h"
 #include "absl/strings/str_cat.h"
 #include "absl/strings/str_join.h"

mediapipe/graphs/object_detection_3d/calculators/annotations_to_model_matrices_calculator.cc

@@ -14,9 +14,9 @@
 
 #include <memory>
 
+#include "Eigen/Core"
 #include "Eigen/Dense"
-#include "Eigen/src/Core/util/Constants.h"
-#include "Eigen/src/Geometry/Quaternion.h"
+#include "Eigen/Geometry"
 #include "absl/memory/memory.h"
 #include "absl/strings/str_cat.h"
 #include "absl/strings/str_join.h"

mediapipe/graphs/selfie_segmentation/BUILD

@@ -0,0 +1,54 @@
+# Copyright 2021 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.
+
+load(
+    "//mediapipe/framework/tool:mediapipe_graph.bzl",
+    "mediapipe_binary_graph",
+)
+
+licenses(["notice"])
+
+package(default_visibility = ["//visibility:public"])
+
+cc_library(
+    name = "selfie_segmentation_gpu_deps",
+    deps = [
+        "//mediapipe/calculators/core:flow_limiter_calculator",
+        "//mediapipe/calculators/image:recolor_calculator",
+        "//mediapipe/modules/selfie_segmentation:selfie_segmentation_gpu",
+    ],
+)
+
+mediapipe_binary_graph(
+    name = "selfie_segmentation_gpu_binary_graph",
+    graph = "selfie_segmentation_gpu.pbtxt",
+    output_name = "selfie_segmentation_gpu.binarypb",
+    deps = [":selfie_segmentation_gpu_deps"],
+)
+
+cc_library(
+    name = "selfie_segmentation_cpu_deps",
+    deps = [
+        "//mediapipe/calculators/core:flow_limiter_calculator",
+        "//mediapipe/calculators/image:recolor_calculator",
+        "//mediapipe/modules/selfie_segmentation:selfie_segmentation_cpu",
+    ],
+)
+
+mediapipe_binary_graph(
+    name = "selfie_segmentation_cpu_binary_graph",
+    graph = "selfie_segmentation_cpu.pbtxt",
+    output_name = "selfie_segmentation_cpu.binarypb",
+    deps = [":selfie_segmentation_cpu_deps"],
+)

mediapipe/graphs/selfie_segmentation/selfie_segmentation_cpu.pbtxt

@@ -0,0 +1,52 @@
+# MediaPipe graph that performs selfie segmentation with TensorFlow Lite on CPU.
+
+# CPU buffer. (ImageFrame)
+input_stream: "input_video"
+
+# Output image with rendered results. (ImageFrame)
+output_stream: "output_video"
+
+# Throttles the images flowing downstream for flow control. It passes through
+# the very first incoming image unaltered, and waits for downstream nodes
+# (calculators and subgraphs) in the graph to finish their tasks before it
+# passes through another image. All images that come in while waiting are
+# dropped, limiting the number of in-flight images in most part of the graph to
+# 1. This prevents the downstream nodes from queuing up incoming images and data
+# excessively, which leads to increased latency and memory usage, unwanted in
+# real-time mobile applications. It also eliminates unnecessarily computation,
+# e.g., the output produced by a node may get dropped downstream if the
+# subsequent nodes are still busy processing previous inputs.
+node {
+  calculator: "FlowLimiterCalculator"
+  input_stream: "input_video"
+  input_stream: "FINISHED:output_video"
+  input_stream_info: {
+    tag_index: "FINISHED"
+    back_edge: true
+  }
+  output_stream: "throttled_input_video"
+}
+
+# Subgraph that performs selfie segmentation.
+node {
+  calculator: "SelfieSegmentationCpu"
+  input_stream: "IMAGE:throttled_input_video"
+  output_stream: "SEGMENTATION_MASK:segmentation_mask"
+}
+
+
+# Colors the selfie segmentation with the color specified in the option.
+node {
+  calculator: "RecolorCalculator"
+  input_stream: "IMAGE:throttled_input_video"
+  input_stream: "MASK:segmentation_mask"
+  output_stream: "IMAGE:output_video"
+  node_options: {
+    [type.googleapis.com/mediapipe.RecolorCalculatorOptions] {
+      color { r: 0 g: 0 b: 255 }
+      mask_channel: RED
+      invert_mask: true
+      adjust_with_luminance: false
+    }
+  }
+}

mediapipe/graphs/selfie_segmentation/selfie_segmentation_gpu.pbtxt

@@ -0,0 +1,52 @@
+# MediaPipe graph that performs selfie segmentation with TensorFlow Lite on GPU.
+
+# GPU buffer. (GpuBuffer)
+input_stream: "input_video"
+
+# Output image with rendered results. (GpuBuffer)
+output_stream: "output_video"
+
+# Throttles the images flowing downstream for flow control. It passes through
+# the very first incoming image unaltered, and waits for downstream nodes
+# (calculators and subgraphs) in the graph to finish their tasks before it
+# passes through another image. All images that come in while waiting are
+# dropped, limiting the number of in-flight images in most part of the graph to
+# 1. This prevents the downstream nodes from queuing up incoming images and data
+# excessively, which leads to increased latency and memory usage, unwanted in
+# real-time mobile applications. It also eliminates unnecessarily computation,
+# e.g., the output produced by a node may get dropped downstream if the
+# subsequent nodes are still busy processing previous inputs.
+node {
+  calculator: "FlowLimiterCalculator"
+  input_stream: "input_video"
+  input_stream: "FINISHED:output_video"
+  input_stream_info: {
+    tag_index: "FINISHED"
+    back_edge: true
+  }
+  output_stream: "throttled_input_video"
+}
+
+# Subgraph that performs selfie segmentation.
+node {
+  calculator: "SelfieSegmentationGpu"
+  input_stream: "IMAGE:throttled_input_video"
+  output_stream: "SEGMENTATION_MASK:segmentation_mask"
+}
+
+
+# Colors the selfie segmentation with the color specified in the option.
+node {
+  calculator: "RecolorCalculator"
+  input_stream: "IMAGE_GPU:throttled_input_video"
+  input_stream: "MASK_GPU:segmentation_mask"
+  output_stream: "IMAGE_GPU:output_video"
+  node_options: {
+    [type.googleapis.com/mediapipe.RecolorCalculatorOptions] {
+      color { r: 0 g: 0 b: 255 }
+      mask_channel: RED
+      invert_mask: true
+      adjust_with_luminance: false
+    }
+  }
+}