Internal change
PiperOrigin-RevId: 515187906
This commit is contained in:
MediaPipe Team
Copybara-Service
parent
8d9f627fd9
commit
c12eae229f
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@ -322,10 +322,8 @@ class FaceDetectorGraph : public core::ModelTaskGraph {
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// detection bounding boxes.
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auto& detection_transformation =
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graph.AddNode("DetectionTransformationCalculator");
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detection_projection.Out(kDetectionsTag) >>
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detection_transformation.In(kDetectionsTag);
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preprocessing.Out(kImageSizeTag) >>
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detection_transformation.In(kImageSizeTag);
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face_detections >> detection_transformation.In(kDetectionsTag);
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image_size >> detection_transformation.In(kImageSizeTag);
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auto face_pixel_detections =
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detection_transformation.Out(kPixelDetectionsTag)
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.Cast<std::vector<Detection>>();
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@ -97,7 +97,8 @@ void ConfigureFaceGeometryEnvGeneratorCalculator(
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// SideInputs:
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// ENVIRONMENT - ENVIRONMENT
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// Environment that describes the current virtual scene. If not provided, a
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// default environment will be used which can be applied to common webcam.
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// default environment will be used which is good enough for most general
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// use cases.
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//
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//
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// Outputs:
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@ -142,7 +143,7 @@ class FaceGeometryFromLandmarksGraph : public Subgraph {
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std::optional<SidePacket<Environment>> environment, Graph& graph) {
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if (!environment.has_value()) {
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// If there is no provided Environment, use a a default environment which
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// is good enough for most general use case.
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// is good enough for most general use cases.
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auto& env_generator = graph.AddNode(
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"mediapipe.tasks.vision.face_geometry."
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"FaceGeometryEnvGeneratorCalculator");
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@ -142,3 +142,50 @@ cc_library(
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"//mediapipe/tasks/cc/components/containers:landmark",
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],
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)
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cc_library(
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name = "face_landmarker_graph",
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srcs = ["face_landmarker_graph.cc"],
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deps = [
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":face_landmarks_detector_graph",
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"//mediapipe/calculators/core:begin_loop_calculator",
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"//mediapipe/calculators/core:clip_vector_size_calculator_cc_proto",
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"//mediapipe/calculators/core:end_loop_calculator",
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"//mediapipe/calculators/core:gate_calculator",
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"//mediapipe/calculators/core:gate_calculator_cc_proto",
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"//mediapipe/calculators/core:pass_through_calculator",
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"//mediapipe/calculators/core:previous_loopback_calculator",
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"//mediapipe/calculators/image:image_properties_calculator",
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"//mediapipe/calculators/util:association_calculator_cc_proto",
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"//mediapipe/calculators/util:association_norm_rect_calculator",
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"//mediapipe/calculators/util:collection_has_min_size_calculator",
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"//mediapipe/calculators/util:collection_has_min_size_calculator_cc_proto",
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"//mediapipe/framework/api2:builder",
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"//mediapipe/framework/api2:port",
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"//mediapipe/framework/formats:classification_cc_proto",
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"//mediapipe/framework/formats:detection_cc_proto",
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"//mediapipe/framework/formats:image",
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"//mediapipe/framework/formats:landmark_cc_proto",
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"//mediapipe/framework/formats:rect_cc_proto",
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"//mediapipe/framework/formats:tensor",
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"//mediapipe/framework/port:status",
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"//mediapipe/tasks/cc:common",
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"//mediapipe/tasks/cc/components/utils:gate",
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"//mediapipe/tasks/cc/core:model_asset_bundle_resources",
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"//mediapipe/tasks/cc/core:model_resources_cache",
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"//mediapipe/tasks/cc/core:model_task_graph",
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"//mediapipe/tasks/cc/core:utils",
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"//mediapipe/tasks/cc/metadata/utils:zip_utils",
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"//mediapipe/tasks/cc/vision/face_detector:face_detector_graph",
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"//mediapipe/tasks/cc/vision/face_detector/proto:face_detector_graph_options_cc_proto",
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"//mediapipe/tasks/cc/vision/face_geometry:face_geometry_from_landmarks_graph",
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"//mediapipe/tasks/cc/vision/face_geometry/proto:environment_cc_proto",
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"//mediapipe/tasks/cc/vision/face_geometry/proto:face_geometry_cc_proto",
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"//mediapipe/tasks/cc/vision/face_landmarker/proto:face_blendshapes_graph_options_cc_proto",
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"//mediapipe/tasks/cc/vision/face_landmarker/proto:face_landmarker_graph_options_cc_proto",
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"//mediapipe/tasks/cc/vision/face_landmarker/proto:face_landmarks_detector_graph_options_cc_proto",
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"//mediapipe/util:graph_builder_utils",
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"@com_google_absl//absl/strings:str_format",
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],
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alwayslink = 1,
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)
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@ -0,0 +1,520 @@
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/* Copyright 2023 The MediaPipe Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include <memory>
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#include <type_traits>
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#include <utility>
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#include <vector>
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#include "absl/strings/str_format.h"
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#include "mediapipe/calculators/core/clip_vector_size_calculator.pb.h"
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#include "mediapipe/calculators/core/gate_calculator.pb.h"
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#include "mediapipe/calculators/util/association_calculator.pb.h"
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#include "mediapipe/calculators/util/collection_has_min_size_calculator.pb.h"
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#include "mediapipe/framework/api2/builder.h"
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#include "mediapipe/framework/api2/port.h"
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#include "mediapipe/framework/formats/classification.pb.h"
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#include "mediapipe/framework/formats/detection.pb.h"
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#include "mediapipe/framework/formats/image.h"
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#include "mediapipe/framework/formats/landmark.pb.h"
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#include "mediapipe/framework/formats/rect.pb.h"
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#include "mediapipe/framework/formats/tensor.h"
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#include "mediapipe/framework/port/status_macros.h"
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#include "mediapipe/tasks/cc/common.h"
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#include "mediapipe/tasks/cc/components/utils/gate.h"
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#include "mediapipe/tasks/cc/core/model_asset_bundle_resources.h"
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#include "mediapipe/tasks/cc/core/model_resources_cache.h"
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#include "mediapipe/tasks/cc/core/model_task_graph.h"
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#include "mediapipe/tasks/cc/core/utils.h"
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#include "mediapipe/tasks/cc/metadata/utils/zip_utils.h"
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#include "mediapipe/tasks/cc/vision/face_detector/proto/face_detector_graph_options.pb.h"
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#include "mediapipe/tasks/cc/vision/face_geometry/proto/environment.pb.h"
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#include "mediapipe/tasks/cc/vision/face_geometry/proto/face_geometry.pb.h"
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#include "mediapipe/tasks/cc/vision/face_landmarker/proto/face_blendshapes_graph_options.pb.h"
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#include "mediapipe/tasks/cc/vision/face_landmarker/proto/face_landmarker_graph_options.pb.h"
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#include "mediapipe/tasks/cc/vision/face_landmarker/proto/face_landmarks_detector_graph_options.pb.h"
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#include "mediapipe/util/graph_builder_utils.h"
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namespace mediapipe {
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namespace tasks {
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namespace vision {
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namespace face_landmarker {
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namespace {
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using ::mediapipe::NormalizedRect;
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using ::mediapipe::api2::Input;
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using ::mediapipe::api2::Output;
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using ::mediapipe::api2::builder::Graph;
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using ::mediapipe::api2::builder::SidePacket;
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using ::mediapipe::api2::builder::Source;
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using ::mediapipe::tasks::components::utils::DisallowIf;
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using ::mediapipe::tasks::core::ModelAssetBundleResources;
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using ::mediapipe::tasks::metadata::SetExternalFile;
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using ::mediapipe::tasks::vision::face_detector::proto::
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FaceDetectorGraphOptions;
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using ::mediapipe::tasks::vision::face_geometry::proto::Environment;
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using ::mediapipe::tasks::vision::face_geometry::proto::FaceGeometry;
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using ::mediapipe::tasks::vision::face_landmarker::proto::
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FaceLandmarkerGraphOptions;
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using ::mediapipe::tasks::vision::face_landmarker::proto::
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FaceLandmarksDetectorGraphOptions;
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constexpr char kImageTag[] = "IMAGE";
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constexpr char kNormRectTag[] = "NORM_RECT";
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constexpr char kNormLandmarksTag[] = "NORM_LANDMARKS";
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constexpr char kFaceRectsTag[] = "FACE_RECTS";
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constexpr char kFaceRectsNextFrameTag[] = "FACE_RECTS_NEXT_FRAME";
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constexpr char kExpandedFaceRectsTag[] = "EXPANDED_FACE_RECTS";
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constexpr char kDetectionsTag[] = "DETECTIONS";
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constexpr char kLoopTag[] = "LOOP";
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constexpr char kPrevLoopTag[] = "PREV_LOOP";
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constexpr char kMainTag[] = "MAIN";
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constexpr char kIterableTag[] = "ITERABLE";
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constexpr char kFaceLandmarksTag[] = "FACE_LANDMARKS";
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constexpr char kFaceGeometryTag[] = "FACE_GEOMETRY";
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constexpr char kEnvironmentTag[] = "ENVIRONMENT";
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constexpr char kBlendshapesTag[] = "BLENDSHAPES";
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constexpr char kImageSizeTag[] = "IMAGE_SIZE";
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constexpr char kSizeTag[] = "SIZE";
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constexpr char kFaceDetectorTFLiteName[] = "face_detector.tflite";
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constexpr char kFaceLandmarksDetectorTFLiteName[] =
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"face_landmarks_detector.tflite";
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constexpr char kFaceBlendshapeTFLiteName[] = "face_blendshapes.tflite";
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struct FaceLandmarkerOutputs {
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Source<std::vector<NormalizedLandmarkList>> landmark_lists;
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Source<std::vector<NormalizedRect>> face_rects_next_frame;
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Source<std::vector<NormalizedRect>> face_rects;
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Source<std::vector<Detection>> detections;
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std::optional<Source<std::vector<ClassificationList>>> face_blendshapes;
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std::optional<Source<std::vector<FaceGeometry>>> face_geometry;
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Source<Image> image;
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};
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// Sets the base options in the sub tasks.
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absl::Status SetSubTaskBaseOptions(const ModelAssetBundleResources& resources,
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FaceLandmarkerGraphOptions* options,
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bool is_copy) {
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auto* face_detector_graph_options =
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options->mutable_face_detector_graph_options();
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if (!face_detector_graph_options->base_options().has_model_asset()) {
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ASSIGN_OR_RETURN(const auto face_detector_file,
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resources.GetModelFile(kFaceDetectorTFLiteName));
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SetExternalFile(face_detector_file,
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face_detector_graph_options->mutable_base_options()
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->mutable_model_asset(),
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is_copy);
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}
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face_detector_graph_options->mutable_base_options()
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->mutable_acceleration()
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->CopyFrom(options->base_options().acceleration());
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face_detector_graph_options->mutable_base_options()->set_use_stream_mode(
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options->base_options().use_stream_mode());
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auto* face_landmarks_detector_graph_options =
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options->mutable_face_landmarks_detector_graph_options();
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if (!face_landmarks_detector_graph_options->base_options()
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.has_model_asset()) {
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ASSIGN_OR_RETURN(const auto face_landmarks_detector_file,
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resources.GetModelFile(kFaceLandmarksDetectorTFLiteName));
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SetExternalFile(
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face_landmarks_detector_file,
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face_landmarks_detector_graph_options->mutable_base_options()
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->mutable_model_asset(),
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is_copy);
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}
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face_landmarks_detector_graph_options->mutable_base_options()
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->mutable_acceleration()
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->CopyFrom(options->base_options().acceleration());
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face_landmarks_detector_graph_options->mutable_base_options()
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->set_use_stream_mode(options->base_options().use_stream_mode());
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absl::StatusOr<absl::string_view> face_blendshape_model =
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resources.GetModelFile(kFaceBlendshapeTFLiteName);
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if (face_blendshape_model.ok()) {
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SetExternalFile(*face_blendshape_model,
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face_landmarks_detector_graph_options
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->mutable_face_blendshapes_graph_options()
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->mutable_base_options()
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->mutable_model_asset(),
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is_copy);
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face_landmarks_detector_graph_options
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->mutable_face_blendshapes_graph_options()
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->mutable_base_options()
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->mutable_acceleration()
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->mutable_xnnpack();
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LOG(WARNING) << "Face blendshape model contains CPU only ops. Sets "
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<< "FaceBlendshapesGraph acceleartion to Xnnpack.";
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}
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return absl::OkStatus();
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}
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} // namespace
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// A "mediapipe.tasks.vision.face_landmarker.FaceLandmarkerGraph" performs face
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// landmarks detection. The FaceLandmarkerGraph consists of three subgraphs:
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// FaceDetectorGraph, MultipleFaceLandmarksDetectorGraph and
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// FaceGeometryFromLandmarksGraph.
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//
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// MultipleFaceLandmarksDetectorGraph detects landmarks from bounding boxes
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// produced by FaceDetectorGraph. FaceLandmarkerGraph tracks the landmarks over
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// time, and skips the FaceDetectorGraph. If the tracking is lost or the
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// detected faces are less than configured max number faces, FaceDetectorGraph
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// would be triggered to detect faces.
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//
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// FaceGeometryFromLandmarksGraph finds the transformation from canonical face
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// to the detected faces. This transformation is useful for renderring face
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// effects on the detected faces. This subgraph is added if users request a
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// FaceGeometry Tag.
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//
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//
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// Inputs:
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// IMAGE - Image
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// Image to perform face landmarks detection on.
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// NORM_RECT - NormalizedRect @Optional
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// Describes image rotation and region of image to perform landmarks
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// detection on. If not provided, whole image is used for face landmarks
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// detection.
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//
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// SideInputs:
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// ENVIRONMENT - ENVIRONMENT @optional
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// Environment that describes the current virtual scene. If not provided, a
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// default environment will be used which is good enough for most general
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// use case
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//
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// Outputs:
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// NORM_LANDMARKS: - std::vector<NormalizedLandmarkList>
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// Vector of detected face landmarks.
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// BLENDSHAPES: - std::vector<ClassificationList> @optional
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// Blendshape classification, available when the given model asset contains
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// blendshapes model.
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// All 52 blendshape coefficients:
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// 0 - _neutral (ignore it)
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// 1 - browDownLeft
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// 2 - browDownRight
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// 3 - browInnerUp
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// 4 - browOuterUpLeft
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// 5 - browOuterUpRight
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// 6 - cheekPuff
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// 7 - cheekSquintLeft
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// 8 - cheekSquintRight
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// 9 - eyeBlinkLeft
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// 10 - eyeBlinkRight
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// 11 - eyeLookDownLeft
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// 12 - eyeLookDownRight
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// 13 - eyeLookInLeft
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// 14 - eyeLookInRight
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// 15 - eyeLookOutLeft
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// 16 - eyeLookOutRight
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// 17 - eyeLookUpLeft
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// 18 - eyeLookUpRight
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// 19 - eyeSquintLeft
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// 20 - eyeSquintRight
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// 21 - eyeWideLeft
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// 22 - eyeWideRight
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// 23 - jawForward
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// 24 - jawLeft
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// 25 - jawOpen
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// 26 - jawRight
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// 27 - mouthClose
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// 28 - mouthDimpleLeft
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// 29 - mouthDimpleRight
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// 30 - mouthFrownLeft
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// 31 - mouthFrownRight
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// 32 - mouthFunnel
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// 33 - mouthLeft
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// 34 - mouthLowerDownLeft
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// 35 - mouthLowerDownRight
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// 36 - mouthPressLeft
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// 37 - mouthPressRight
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// 38 - mouthPucker
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// 39 - mouthRight
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// 40 - mouthRollLower
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// 41 - mouthRollUpper
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// 42 - mouthShrugLower
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// 43 - mouthShrugUpper
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// 44 - mouthSmileLeft
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// 45 - mouthSmileRight
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// 46 - mouthStretchLeft
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// 47 - mouthStretchRight
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// 48 - mouthUpperUpLeft
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// 49 - mouthUpperUpRight
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// 50 - noseSneerLeft
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// 51 - noseSneerRight
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// FACE_GEOMETRY - std::vector<FaceGeometry> @optional
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// A vector of 3D transform data for each detected face.
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// FACE_RECTS_NEXT_FRAME - std::vector<NormalizedRect>
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// Vector of the expanded rects enclosing the whole face RoI for landmark
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// detection on the next frame.
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// FACE_RECTS - std::vector<NormalizedRect>
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// Detected face bounding boxes in normalized coordinates from face
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// detection.
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// DETECTIONS - std::vector<Detection>
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// Detected faces with maximum `num_faces` specified in options.
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// IMAGE - Image
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// The input image that the face landmarker runs on and has the pixel data
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// stored on the target storage (CPU vs GPU).
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// All returned coordinates are in the unrotated and uncropped input image
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// coordinates system.
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//
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// Example:
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// node {
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// calculator: "mediapipe.tasks.vision.face_landmarker.FaceLandmarkerGraph"
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// input_stream: "IMAGE:image_in"
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// input_stream: "NORM_RECT:norm_rect"
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// output_stream: "NORM_LANDMARKS:face_landmarks"
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// output_stream: "BLENDSHAPES:face_blendshapes"
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// output_stream: "FACE_GEOMETRY:face_geometry"
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// output_stream: "FACE_RECTS_NEXT_FRAME:face_rects_next_frame"
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// output_stream: "FACE_RECTS:face_rects"
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// output_stream: "DETECTIONS:detections"
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// output_stream: "IMAGE:image_out"
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// options {
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// [mediapipe.tasks.vision.face_landmarker.proto.FaceLandmarkerGraphOptions.ext]
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// {
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// base_options {
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// model_asset {
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// file_name: "face_landmarker.task"
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// }
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// }
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// face_detector_graph_options {
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// min_detection_confidence: 0.5
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// num_faces: 2
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// }
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// face_landmarks_detector_graph_options {
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// min_detection_confidence: 0.5
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// }
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// }
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// }
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// }
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class FaceLandmarkerGraph : public core::ModelTaskGraph {
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public:
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absl::StatusOr<CalculatorGraphConfig> GetConfig(
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SubgraphContext* sc) override {
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Graph graph;
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if (sc->Options<FaceLandmarkerGraphOptions>()
|
||||
.base_options()
|
||||
.has_model_asset()) {
|
||||
ASSIGN_OR_RETURN(
|
||||
const auto* model_asset_bundle_resources,
|
||||
CreateModelAssetBundleResources<FaceLandmarkerGraphOptions>(sc));
|
||||
// Copies the file content instead of passing the pointer of file in
|
||||
// memory if the subgraph model resource service is not available.
|
||||
MP_RETURN_IF_ERROR(SetSubTaskBaseOptions(
|
||||
*model_asset_bundle_resources,
|
||||
sc->MutableOptions<FaceLandmarkerGraphOptions>(),
|
||||
!sc->Service(::mediapipe::tasks::core::kModelResourcesCacheService)
|
||||
.IsAvailable()));
|
||||
}
|
||||
std::optional<SidePacket<Environment>> environment;
|
||||
if (HasSideInput(sc->OriginalNode(), kEnvironmentTag)) {
|
||||
environment = std::make_optional<>(
|
||||
graph.SideIn(kEnvironmentTag).Cast<Environment>());
|
||||
}
|
||||
bool output_blendshapes = HasOutput(sc->OriginalNode(), kBlendshapesTag);
|
||||
if (output_blendshapes && !sc->Options<FaceLandmarkerGraphOptions>()
|
||||
.face_landmarks_detector_graph_options()
|
||||
.has_face_blendshapes_graph_options()) {
|
||||
return absl::InvalidArgumentError(absl::StrFormat(
|
||||
"BLENDSHAPES Tag and blendshapes model must be both set. Get "
|
||||
"BLENDSHAPES is set: %v, blendshapes "
|
||||
"model "
|
||||
"is set: %v",
|
||||
output_blendshapes,
|
||||
sc->Options<FaceLandmarkerGraphOptions>()
|
||||
.face_landmarks_detector_graph_options()
|
||||
.has_face_blendshapes_graph_options()));
|
||||
}
|
||||
bool output_geometry = HasOutput(sc->OriginalNode(), kFaceGeometryTag);
|
||||
ASSIGN_OR_RETURN(
|
||||
auto outs,
|
||||
BuildFaceLandmarkerGraph(
|
||||
*sc->MutableOptions<FaceLandmarkerGraphOptions>(),
|
||||
graph[Input<Image>(kImageTag)],
|
||||
graph[Input<NormalizedRect>::Optional(kNormRectTag)], environment,
|
||||
output_blendshapes, output_geometry, graph));
|
||||
outs.landmark_lists >>
|
||||
graph[Output<std::vector<NormalizedLandmarkList>>(kNormLandmarksTag)];
|
||||
outs.face_rects_next_frame >>
|
||||
graph[Output<std::vector<NormalizedRect>>(kFaceRectsNextFrameTag)];
|
||||
outs.face_rects >>
|
||||
graph[Output<std::vector<NormalizedRect>>(kFaceRectsTag)];
|
||||
outs.detections >> graph[Output<std::vector<Detection>>(kDetectionsTag)];
|
||||
outs.image >> graph[Output<Image>(kImageTag)];
|
||||
if (outs.face_blendshapes) {
|
||||
*outs.face_blendshapes >>
|
||||
graph[Output<std::vector<ClassificationList>>(kBlendshapesTag)];
|
||||
}
|
||||
if (outs.face_geometry) {
|
||||
*outs.face_geometry >>
|
||||
graph[Output<std::vector<FaceGeometry>>(kFaceGeometryTag)];
|
||||
}
|
||||
|
||||
// TODO remove when support is fixed.
|
||||
// As mediapipe GraphBuilder currently doesn't support configuring
|
||||
// InputStreamInfo, modifying the CalculatorGraphConfig proto directly.
|
||||
CalculatorGraphConfig config = graph.GetConfig();
|
||||
for (int i = 0; i < config.node_size(); ++i) {
|
||||
if (config.node(i).calculator() == "PreviousLoopbackCalculator") {
|
||||
auto* info = config.mutable_node(i)->add_input_stream_info();
|
||||
info->set_tag_index(kLoopTag);
|
||||
info->set_back_edge(true);
|
||||
break;
|
||||
}
|
||||
}
|
||||
return config;
|
||||
}
|
||||
|
||||
private:
|
||||
// Adds a mediapipe face landmarker graph into the provided builder::Graph
|
||||
// instance.
|
||||
//
|
||||
// tasks_options: the mediapipe tasks module FaceLandmarkerGraphOptions.
|
||||
// image_in: (mediapipe::Image) stream to run face landmark detection on.
|
||||
// graph: the mediapipe graph instance to be updated.
|
||||
absl::StatusOr<FaceLandmarkerOutputs> BuildFaceLandmarkerGraph(
|
||||
FaceLandmarkerGraphOptions& tasks_options, Source<Image> image_in,
|
||||
Source<NormalizedRect> norm_rect_in,
|
||||
std::optional<SidePacket<Environment>> environment,
|
||||
bool output_blendshapes, bool output_geometry, Graph& graph) {
|
||||
const int max_num_faces =
|
||||
tasks_options.face_detector_graph_options().num_faces();
|
||||
|
||||
auto& face_detector =
|
||||
graph.AddNode("mediapipe.tasks.vision.face_detector.FaceDetectorGraph");
|
||||
face_detector.GetOptions<FaceDetectorGraphOptions>().Swap(
|
||||
tasks_options.mutable_face_detector_graph_options());
|
||||
auto& clip_face_rects =
|
||||
graph.AddNode("ClipNormalizedRectVectorSizeCalculator");
|
||||
clip_face_rects.GetOptions<ClipVectorSizeCalculatorOptions>()
|
||||
.set_max_vec_size(max_num_faces);
|
||||
auto clipped_face_rects = clip_face_rects.Out("");
|
||||
|
||||
auto& face_landmarks_detector_graph = graph.AddNode(
|
||||
"mediapipe.tasks.vision.face_landmarker."
|
||||
"MultiFaceLandmarksDetectorGraph");
|
||||
face_landmarks_detector_graph
|
||||
.GetOptions<FaceLandmarksDetectorGraphOptions>()
|
||||
.Swap(tasks_options.mutable_face_landmarks_detector_graph_options());
|
||||
image_in >> face_landmarks_detector_graph.In(kImageTag);
|
||||
clipped_face_rects >> face_landmarks_detector_graph.In(kNormRectTag);
|
||||
|
||||
// TODO: add landmarks smoothing calculators.
|
||||
auto landmarks = face_landmarks_detector_graph.Out(kNormLandmarksTag)
|
||||
.Cast<std::vector<NormalizedLandmarkList>>();
|
||||
auto face_rects_for_next_frame =
|
||||
face_landmarks_detector_graph.Out(kFaceRectsNextFrameTag)
|
||||
.Cast<std::vector<NormalizedRect>>();
|
||||
|
||||
if (tasks_options.base_options().use_stream_mode()) {
|
||||
auto& previous_loopback = graph.AddNode("PreviousLoopbackCalculator");
|
||||
image_in >> previous_loopback.In(kMainTag);
|
||||
auto prev_face_rects_from_landmarks =
|
||||
previous_loopback[Output<std::vector<NormalizedRect>>(kPrevLoopTag)];
|
||||
|
||||
auto& min_size_node =
|
||||
graph.AddNode("NormalizedRectVectorHasMinSizeCalculator");
|
||||
prev_face_rects_from_landmarks >> min_size_node.In(kIterableTag);
|
||||
min_size_node.GetOptions<CollectionHasMinSizeCalculatorOptions>()
|
||||
.set_min_size(max_num_faces);
|
||||
auto has_enough_faces = min_size_node.Out("").Cast<bool>();
|
||||
|
||||
// While in stream mode, skip face detector graph when we successfully
|
||||
// track the faces from the last frame.
|
||||
auto image_for_face_detector =
|
||||
DisallowIf(image_in, has_enough_faces, graph);
|
||||
auto norm_rect_in_for_face_detector =
|
||||
DisallowIf(norm_rect_in, has_enough_faces, graph);
|
||||
image_for_face_detector >> face_detector.In(kImageTag);
|
||||
norm_rect_in_for_face_detector >> face_detector.In(kNormRectTag);
|
||||
auto expanded_face_rects_from_face_detector =
|
||||
face_detector.Out(kExpandedFaceRectsTag);
|
||||
auto& face_association = graph.AddNode("AssociationNormRectCalculator");
|
||||
face_association.GetOptions<mediapipe::AssociationCalculatorOptions>()
|
||||
.set_min_similarity_threshold(
|
||||
tasks_options.min_tracking_confidence());
|
||||
prev_face_rects_from_landmarks >>
|
||||
face_association[Input<std::vector<NormalizedRect>>::Multiple("")][0];
|
||||
expanded_face_rects_from_face_detector >>
|
||||
face_association[Input<std::vector<NormalizedRect>>::Multiple("")][1];
|
||||
auto face_rects = face_association.Out("");
|
||||
face_rects >> clip_face_rects.In("");
|
||||
// Back edge.
|
||||
face_rects_for_next_frame >> previous_loopback.In(kLoopTag);
|
||||
} else {
|
||||
// While not in stream mode, the input images are not guaranteed to be in
|
||||
// series, and we don't want to enable the tracking and rect associations
|
||||
// between input images. Always use the face detector graph.
|
||||
image_in >> face_detector.In(kImageTag);
|
||||
norm_rect_in >> face_detector.In(kNormRectTag);
|
||||
auto face_rects = face_detector.Out(kExpandedFaceRectsTag);
|
||||
face_rects >> clip_face_rects.In("");
|
||||
}
|
||||
|
||||
// Optional blendshape output.
|
||||
std::optional<Source<std::vector<ClassificationList>>> blendshapes;
|
||||
if (output_blendshapes) {
|
||||
blendshapes = std::make_optional<>(
|
||||
face_landmarks_detector_graph.Out(kBlendshapesTag)
|
||||
.Cast<std::vector<ClassificationList>>());
|
||||
}
|
||||
|
||||
// Optional face geometry output.
|
||||
std::optional<Source<std::vector<FaceGeometry>>> face_geometry;
|
||||
if (output_geometry) {
|
||||
auto& image_properties = graph.AddNode("ImagePropertiesCalculator");
|
||||
image_in >> image_properties.In(kImageTag);
|
||||
auto image_size = image_properties.Out(kSizeTag);
|
||||
auto& face_geometry_from_landmarks = graph.AddNode(
|
||||
"mediapipe.tasks.vision.face_geometry."
|
||||
"FaceGeometryFromLandmarksGraph");
|
||||
if (environment.has_value()) {
|
||||
*environment >> face_geometry_from_landmarks.SideIn(kEnvironmentTag);
|
||||
}
|
||||
landmarks >> face_geometry_from_landmarks.In(kFaceLandmarksTag);
|
||||
image_size >> face_geometry_from_landmarks.In(kImageSizeTag);
|
||||
face_geometry = face_geometry_from_landmarks.Out(kFaceGeometryTag)
|
||||
.Cast<std::vector<FaceGeometry>>();
|
||||
}
|
||||
|
||||
// TODO: Replace PassThroughCalculator with a calculator that
|
||||
// converts the pixel data to be stored on the target storage (CPU vs GPU).
|
||||
auto& pass_through = graph.AddNode("PassThroughCalculator");
|
||||
image_in >> pass_through.In("");
|
||||
|
||||
return {{
|
||||
/* landmark_lists= */ landmarks,
|
||||
/* face_rects_next_frame= */
|
||||
face_rects_for_next_frame,
|
||||
/* face_rects= */
|
||||
face_detector.Out(kFaceRectsTag).Cast<std::vector<NormalizedRect>>(),
|
||||
/* face_detections */
|
||||
face_detector.Out(kDetectionsTag).Cast<std::vector<Detection>>(),
|
||||
/* face_blendshapes= */ blendshapes,
|
||||
/* face_geometry= */ face_geometry,
|
||||
/* image= */
|
||||
pass_through[Output<Image>("")],
|
||||
}};
|
||||
}
|
||||
};
|
||||
|
||||
REGISTER_MEDIAPIPE_GRAPH(
|
||||
::mediapipe::tasks::vision::face_landmarker::FaceLandmarkerGraph);
|
||||
|
||||
} // namespace face_landmarker
|
||||
} // namespace vision
|
||||
} // namespace tasks
|
||||
} // namespace mediapipe
|
||||
|
|
@ -0,0 +1,311 @@
|
|||
/* Copyright 2023 The MediaPipe Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
==============================================================================*/
|
||||
|
||||
#include <optional>
|
||||
|
||||
#include "absl/flags/flag.h"
|
||||
#include "absl/status/statusor.h"
|
||||
#include "absl/strings/str_format.h"
|
||||
#include "absl/strings/string_view.h"
|
||||
#include "mediapipe/framework/api2/builder.h"
|
||||
#include "mediapipe/framework/api2/port.h"
|
||||
#include "mediapipe/framework/calculator_framework.h"
|
||||
#include "mediapipe/framework/deps/file_path.h"
|
||||
#include "mediapipe/framework/formats/classification.pb.h"
|
||||
#include "mediapipe/framework/formats/image.h"
|
||||
#include "mediapipe/framework/formats/landmark.pb.h"
|
||||
#include "mediapipe/framework/formats/rect.pb.h"
|
||||
#include "mediapipe/framework/packet.h"
|
||||
#include "mediapipe/framework/port/file_helpers.h"
|
||||
#include "mediapipe/framework/port/gmock.h"
|
||||
#include "mediapipe/framework/port/gtest.h"
|
||||
#include "mediapipe/tasks/cc/core/mediapipe_builtin_op_resolver.h"
|
||||
#include "mediapipe/tasks/cc/core/proto/base_options.pb.h"
|
||||
#include "mediapipe/tasks/cc/core/proto/external_file.pb.h"
|
||||
#include "mediapipe/tasks/cc/core/task_runner.h"
|
||||
#include "mediapipe/tasks/cc/vision/face_detector/proto/face_detector_graph_options.pb.h"
|
||||
#include "mediapipe/tasks/cc/vision/face_geometry/proto/face_geometry.pb.h"
|
||||
#include "mediapipe/tasks/cc/vision/face_landmarker/proto/face_landmarker_graph_options.pb.h"
|
||||
#include "mediapipe/tasks/cc/vision/face_landmarker/proto/face_landmarks_detector_graph_options.pb.h"
|
||||
#include "mediapipe/tasks/cc/vision/utils/image_utils.h"
|
||||
|
||||
namespace mediapipe {
|
||||
namespace tasks {
|
||||
namespace vision {
|
||||
namespace face_landmarker {
|
||||
namespace {
|
||||
|
||||
using ::file::Defaults;
|
||||
using ::file::GetTextProto;
|
||||
using ::mediapipe::api2::Input;
|
||||
using ::mediapipe::api2::Output;
|
||||
using ::mediapipe::api2::builder::Graph;
|
||||
using ::mediapipe::api2::builder::Source;
|
||||
using ::mediapipe::file::JoinPath;
|
||||
using ::mediapipe::tasks::core::TaskRunner;
|
||||
using ::mediapipe::tasks::vision::DecodeImageFromFile;
|
||||
using ::mediapipe::tasks::vision::face_geometry::proto::FaceGeometry;
|
||||
using ::mediapipe::tasks::vision::face_landmarker::proto::
|
||||
FaceLandmarkerGraphOptions;
|
||||
using ::testing::EqualsProto;
|
||||
using ::testing::Pointwise;
|
||||
using ::testing::TestParamInfo;
|
||||
using ::testing::TestWithParam;
|
||||
using ::testing::Values;
|
||||
using ::testing::proto::Approximately;
|
||||
using ::testing::proto::Partially;
|
||||
|
||||
constexpr char kTestDataDirectory[] = "/mediapipe/tasks/testdata/vision/";
|
||||
constexpr char kFaceLandmarkerModelBundleName[] = "face_landmarker.task";
|
||||
constexpr char kFaceLandmarkerWithBlendshapesModelBundleName[] =
|
||||
"face_landmarker_with_blendshapes.task";
|
||||
constexpr char kPortraitImageName[] = "portrait.jpg";
|
||||
constexpr char kCatImageName[] = "cat.jpg";
|
||||
constexpr char kPortraitExpectedFaceLandamrksName[] =
|
||||
"portrait_expected_face_landmarks.pbtxt";
|
||||
constexpr char kPortraitExpectedFaceLandamrksWithAttentionName[] =
|
||||
"portrait_expected_face_landmarks_with_attention.pbtxt";
|
||||
constexpr char kPortraitExpectedBlendshapesName[] =
|
||||
"portrait_expected_blendshapes_with_attention.pbtxt";
|
||||
constexpr char kPortraitExpectedFaceGeometryName[] =
|
||||
"portrait_expected_face_geometry_with_attention.pbtxt";
|
||||
|
||||
constexpr char kImageTag[] = "IMAGE";
|
||||
constexpr char kImageName[] = "image";
|
||||
constexpr char kNormRectTag[] = "NORM_RECT";
|
||||
constexpr char kNormRectName[] = "norm_rect";
|
||||
constexpr char kNormLandmarksTag[] = "NORM_LANDMARKS";
|
||||
constexpr char kNormLandmarksName[] = "norm_landmarks";
|
||||
constexpr char kBlendshapesTag[] = "BLENDSHAPES";
|
||||
constexpr char kBlendshapesName[] = "blendshapes";
|
||||
constexpr char kFaceGeometryTag[] = "FACE_GEOMETRY";
|
||||
constexpr char kFaceGeometryName[] = "face_geometry";
|
||||
|
||||
constexpr float kLandmarksDiffMargin = 0.03;
|
||||
constexpr float kBlendshapesDiffMargin = 0.1;
|
||||
constexpr float kFaceGeometryDiffMargin = 0.01;
|
||||
|
||||
template <typename ProtoT>
|
||||
ProtoT GetExpectedProto(absl::string_view filename) {
|
||||
ProtoT expected_proto;
|
||||
MP_EXPECT_OK(GetTextProto(file::JoinPath("./", kTestDataDirectory, filename),
|
||||
&expected_proto, Defaults()));
|
||||
return expected_proto;
|
||||
}
|
||||
|
||||
// Struct holding the parameters for parameterized FaceLandmarkerGraphTest
|
||||
// class.
|
||||
struct FaceLandmarkerGraphTestParams {
|
||||
// The name of this test, for convenience when displaying test results.
|
||||
std::string test_name;
|
||||
// The filename of the model to test.
|
||||
std::string input_model_name;
|
||||
// The filename of the test image.
|
||||
std::string test_image_name;
|
||||
// The expected output landmarks positions.
|
||||
std::optional<std::vector<NormalizedLandmarkList>> expected_landmarks_list;
|
||||
// The expected output blendshape classification.
|
||||
std::optional<std::vector<ClassificationList>> expected_blendshapes;
|
||||
// The expected output face geometry.
|
||||
std::optional<std::vector<FaceGeometry>> expected_face_geometry;
|
||||
// The max value difference between expected_positions and detected positions.
|
||||
float landmarks_diff_threshold;
|
||||
// The max value difference between expected blendshapes and actual
|
||||
// blendshapes.
|
||||
float blendshapes_diff_threshold;
|
||||
// The max value difference between expected blendshape and actual face
|
||||
// geometry.
|
||||
float face_geometry_diff_threshold;
|
||||
};
|
||||
|
||||
// Helper function to create a FaceLandmarkerGraph TaskRunner.
|
||||
absl::StatusOr<std::unique_ptr<TaskRunner>> CreateFaceLandmarkerGraphTaskRunner(
|
||||
absl::string_view model_name, bool output_blendshape,
|
||||
bool output_face_geometry) {
|
||||
Graph graph;
|
||||
|
||||
auto& face_landmarker = graph.AddNode(
|
||||
"mediapipe.tasks.vision.face_landmarker."
|
||||
"FaceLandmarkerGraph");
|
||||
|
||||
auto* options = &face_landmarker.GetOptions<FaceLandmarkerGraphOptions>();
|
||||
options->mutable_base_options()->mutable_model_asset()->set_file_name(
|
||||
JoinPath("./", kTestDataDirectory, model_name));
|
||||
options->mutable_face_detector_graph_options()->set_num_faces(1);
|
||||
options->mutable_base_options()->set_use_stream_mode(true);
|
||||
|
||||
graph[Input<Image>(kImageTag)].SetName(kImageName) >>
|
||||
face_landmarker.In(kImageTag);
|
||||
graph[Input<NormalizedRect>(kNormRectTag)].SetName(kNormRectName) >>
|
||||
face_landmarker.In(kNormRectTag);
|
||||
|
||||
face_landmarker.Out(kNormLandmarksTag).SetName(kNormLandmarksName) >>
|
||||
graph[Output<std::vector<NormalizedLandmarkList>>(kNormLandmarksTag)];
|
||||
if (output_blendshape) {
|
||||
face_landmarker.Out(kBlendshapesTag).SetName(kBlendshapesName) >>
|
||||
graph[Output<std::vector<ClassificationList>>(kBlendshapesTag)];
|
||||
}
|
||||
if (output_face_geometry) {
|
||||
face_landmarker.Out(kFaceGeometryTag).SetName(kFaceGeometryName) >>
|
||||
graph[Output<std::vector<FaceGeometry>>(kFaceGeometryTag)];
|
||||
}
|
||||
|
||||
return TaskRunner::Create(
|
||||
graph.GetConfig(),
|
||||
absl::make_unique<tasks::core::MediaPipeBuiltinOpResolver>());
|
||||
}
|
||||
|
||||
// Helper function to construct NormalizeRect proto.
|
||||
NormalizedRect MakeNormRect(float x_center, float y_center, float width,
|
||||
float height, float rotation) {
|
||||
NormalizedRect face_rect;
|
||||
face_rect.set_x_center(x_center);
|
||||
face_rect.set_y_center(y_center);
|
||||
face_rect.set_width(width);
|
||||
face_rect.set_height(height);
|
||||
face_rect.set_rotation(rotation);
|
||||
return face_rect;
|
||||
}
|
||||
|
||||
class FaceLandmarkerGraphTest
|
||||
: public testing::TestWithParam<FaceLandmarkerGraphTestParams> {};
|
||||
|
||||
TEST(FaceLandmarkerGraphTest, FailsWithNoBlendshapesModel) {
|
||||
MP_ASSERT_OK_AND_ASSIGN(
|
||||
Image image, DecodeImageFromFile(
|
||||
JoinPath("./", kTestDataDirectory, kPortraitImageName)));
|
||||
auto result =
|
||||
CreateFaceLandmarkerGraphTaskRunner(kFaceLandmarkerModelBundleName,
|
||||
/*output_blendshape=*/true,
|
||||
/*output_face_geometry=*/false);
|
||||
EXPECT_EQ(result.status().code(), absl::StatusCode::kInvalidArgument);
|
||||
EXPECT_THAT(result.status().message(),
|
||||
testing::HasSubstr(
|
||||
"BLENDSHAPES Tag and blendshapes model must be both set."));
|
||||
}
|
||||
|
||||
TEST_P(FaceLandmarkerGraphTest, Succeeds) {
|
||||
MP_ASSERT_OK_AND_ASSIGN(
|
||||
Image image, DecodeImageFromFile(JoinPath("./", kTestDataDirectory,
|
||||
GetParam().test_image_name)));
|
||||
MP_ASSERT_OK_AND_ASSIGN(auto task_runner,
|
||||
CreateFaceLandmarkerGraphTaskRunner(
|
||||
GetParam().input_model_name,
|
||||
GetParam().expected_blendshapes.has_value(),
|
||||
GetParam().expected_face_geometry.has_value()));
|
||||
|
||||
auto output_packets = task_runner->Process(
|
||||
{{kImageName, MakePacket<Image>(std::move(image))},
|
||||
{kNormRectName,
|
||||
MakePacket<NormalizedRect>(MakeNormRect(0.5, 0.5, 1.0, 1.0, 0))}});
|
||||
MP_ASSERT_OK(output_packets);
|
||||
|
||||
if (GetParam().expected_landmarks_list) {
|
||||
const std::vector<NormalizedLandmarkList>& landmarks_lists =
|
||||
(*output_packets)[kNormLandmarksName]
|
||||
.Get<std::vector<NormalizedLandmarkList>>();
|
||||
EXPECT_THAT(landmarks_lists,
|
||||
Pointwise(Approximately(Partially(EqualsProto()),
|
||||
GetParam().landmarks_diff_threshold),
|
||||
*GetParam().expected_landmarks_list));
|
||||
}
|
||||
|
||||
if (GetParam().expected_blendshapes) {
|
||||
const std::vector<ClassificationList>& blendshapes =
|
||||
(*output_packets)[kBlendshapesName]
|
||||
.Get<std::vector<ClassificationList>>();
|
||||
EXPECT_THAT(blendshapes,
|
||||
Pointwise(Approximately(Partially(EqualsProto()),
|
||||
GetParam().blendshapes_diff_threshold),
|
||||
*GetParam().expected_blendshapes));
|
||||
}
|
||||
if (GetParam().expected_face_geometry) {
|
||||
const std::vector<FaceGeometry>& face_geometry =
|
||||
(*output_packets)[kFaceGeometryName].Get<std::vector<FaceGeometry>>();
|
||||
EXPECT_THAT(
|
||||
face_geometry,
|
||||
Pointwise(Approximately(Partially(EqualsProto()),
|
||||
GetParam().face_geometry_diff_threshold),
|
||||
*GetParam().expected_face_geometry));
|
||||
}
|
||||
}
|
||||
|
||||
INSTANTIATE_TEST_SUITE_P(
|
||||
FaceLandmarkerGraphTests, FaceLandmarkerGraphTest,
|
||||
Values(FaceLandmarkerGraphTestParams{
|
||||
/* test_name= */ "Portrait",
|
||||
/* input_model_name= */ kFaceLandmarkerModelBundleName,
|
||||
/* test_image_name= */ kPortraitImageName,
|
||||
/* expected_landmarks_list= */
|
||||
{{GetExpectedProto<NormalizedLandmarkList>(
|
||||
kPortraitExpectedFaceLandamrksName)}},
|
||||
/* expected_blendshapes= */ std::nullopt,
|
||||
/* expected_face_geometry= */ std::nullopt,
|
||||
/* landmarks_diff_threshold= */ kLandmarksDiffMargin,
|
||||
/* blendshapes_diff_threshold= */ kBlendshapesDiffMargin,
|
||||
/* face_geometry_diff_threshold= */
|
||||
kFaceGeometryDiffMargin},
|
||||
FaceLandmarkerGraphTestParams{
|
||||
/* test_name= */ "NoFace",
|
||||
/* input_model_name= */ kFaceLandmarkerModelBundleName,
|
||||
/* test_image_name= */ kCatImageName,
|
||||
/* expected_landmarks_list= */ std::nullopt,
|
||||
/* expected_blendshapes= */ std::nullopt,
|
||||
/* expected_face_geometry= */ std::nullopt,
|
||||
/* landmarks_diff_threshold= */ kLandmarksDiffMargin,
|
||||
/* blendshapes_diff_threshold= */ kBlendshapesDiffMargin,
|
||||
/* face_geometry_diff_threshold= */
|
||||
kFaceGeometryDiffMargin},
|
||||
FaceLandmarkerGraphTestParams{
|
||||
/* test_name= */ "PortraitWithBlendshape",
|
||||
/* input_model_name= */
|
||||
kFaceLandmarkerWithBlendshapesModelBundleName,
|
||||
/* test_image_name= */ kPortraitImageName,
|
||||
/* expected_landmarks_list= */
|
||||
{{GetExpectedProto<NormalizedLandmarkList>(
|
||||
kPortraitExpectedFaceLandamrksWithAttentionName)}},
|
||||
/* expected_blendshapes= */
|
||||
{{GetExpectedProto<ClassificationList>(
|
||||
kPortraitExpectedBlendshapesName)}},
|
||||
/* expected_face_geometry= */ std::nullopt,
|
||||
/*landmarks_diff_threshold= */ kLandmarksDiffMargin,
|
||||
/*blendshapes_diff_threshold= */ kBlendshapesDiffMargin,
|
||||
/*face_geometry_diff_threshold= */ kFaceGeometryDiffMargin},
|
||||
FaceLandmarkerGraphTestParams{
|
||||
/* test_name= */ "PortraitWithBlendshapeWithFaceGeometry",
|
||||
/* input_model_name= */
|
||||
kFaceLandmarkerWithBlendshapesModelBundleName,
|
||||
/* test_image_name= */ kPortraitImageName,
|
||||
/* expected_landmarks_list= */
|
||||
{{GetExpectedProto<NormalizedLandmarkList>(
|
||||
kPortraitExpectedFaceLandamrksWithAttentionName)}},
|
||||
/* expected_blendshapes= */
|
||||
{{GetExpectedProto<ClassificationList>(
|
||||
kPortraitExpectedBlendshapesName)}},
|
||||
/* expected_face_geometry= */
|
||||
{{GetExpectedProto<FaceGeometry>(
|
||||
kPortraitExpectedFaceGeometryName)}},
|
||||
/*landmarks_diff_threshold= */ kLandmarksDiffMargin,
|
||||
/*blendshapes_diff_threshold= */ kBlendshapesDiffMargin,
|
||||
/*face_geometry_diff_threshold= */ kFaceGeometryDiffMargin}),
|
||||
[](const TestParamInfo<FaceLandmarkerGraphTest::ParamType>& info) {
|
||||
return info.param.test_name;
|
||||
});
|
||||
|
||||
} // namespace
|
||||
} // namespace face_landmarker
|
||||
} // namespace vision
|
||||
} // namespace tasks
|
||||
} // namespace mediapipe
|
||||
|
|
@ -214,13 +214,13 @@ ClassificationList GetBlendshapes(absl::string_view filename) {
|
|||
// Helper function to construct NormalizeRect proto.
|
||||
NormalizedRect MakeNormRect(float x_center, float y_center, float width,
|
||||
float height, float rotation) {
|
||||
NormalizedRect hand_rect;
|
||||
hand_rect.set_x_center(x_center);
|
||||
hand_rect.set_y_center(y_center);
|
||||
hand_rect.set_width(width);
|
||||
hand_rect.set_height(height);
|
||||
hand_rect.set_rotation(rotation);
|
||||
return hand_rect;
|
||||
NormalizedRect face_rect;
|
||||
face_rect.set_x_center(x_center);
|
||||
face_rect.set_y_center(y_center);
|
||||
face_rect.set_width(width);
|
||||
face_rect.set_height(height);
|
||||
face_rect.set_rotation(rotation);
|
||||
return face_rect;
|
||||
}
|
||||
|
||||
// Struct holding the parameters for parameterized FaceLandmarksDetectionTest
|
||||
|
|
@ -234,9 +234,9 @@ struct SingeFaceTestParams {
|
|||
std::optional<std::string> blendshape_model_name;
|
||||
// The filename of the test image.
|
||||
std::string test_image_name;
|
||||
// RoI on image to detect hands.
|
||||
// RoI on image to detect faces.
|
||||
NormalizedRect norm_rect;
|
||||
// Expected hand presence value.
|
||||
// Expected face presence value.
|
||||
bool expected_presence;
|
||||
// The expected output landmarks positions.
|
||||
NormalizedLandmarkList expected_landmarks;
|
||||
|
|
@ -258,9 +258,9 @@ struct MultiFaceTestParams {
|
|||
std::optional<std::string> blendshape_model_name;
|
||||
// The filename of the test image.
|
||||
std::string test_image_name;
|
||||
// RoI on image to detect hands.
|
||||
// RoI on image to detect faces.
|
||||
std::vector<NormalizedRect> norm_rects;
|
||||
// Expected hand presence value.
|
||||
// Expected face presence value.
|
||||
std::vector<bool> expected_presence;
|
||||
// The expected output landmarks positions.
|
||||
std::optional<std::vector<NormalizedLandmarkList>> expected_landmarks_lists;
|
||||
|
|
@ -299,7 +299,6 @@ TEST_P(SingleFaceLandmarksDetectionTest, Succeeds) {
|
|||
(*output_packets)[kNormLandmarksName].Get<NormalizedLandmarkList>();
|
||||
const NormalizedLandmarkList& expected_landmarks =
|
||||
GetParam().expected_landmarks;
|
||||
|
||||
EXPECT_THAT(
|
||||
landmarks,
|
||||
Approximately(Partially(EqualsProto(expected_landmarks)),
|
||||
|
|
@ -395,7 +394,9 @@ INSTANTIATE_TEST_SUITE_P(
|
|||
kFaceLandmarksDetectionWithAttentionModel,
|
||||
/* blendshape_model_name= */ kFaceBlendshapesModel,
|
||||
/* test_image_name= */ kPortraitImageName,
|
||||
/* norm_rect= */ MakeNormRect(0.4987, 0.2211, 0.2877, 0.2303, 0),
|
||||
/* norm_rect= */
|
||||
MakeNormRect(0.48906386, 0.22731927, 0.42905223, 0.34357703,
|
||||
0.008304443),
|
||||
/* expected_presence= */ true,
|
||||
/* expected_landmarks= */
|
||||
GetExpectedLandmarkList(
|
||||
|
|
@ -444,7 +445,9 @@ INSTANTIATE_TEST_SUITE_P(
|
|||
kFaceLandmarksDetectionWithAttentionModel,
|
||||
/* blendshape_model_name= */ kFaceBlendshapesModel,
|
||||
/* test_image_name= */ kPortraitImageName,
|
||||
/* norm_rects= */ {MakeNormRect(0.4987, 0.2211, 0.2877, 0.2303, 0)},
|
||||
/* norm_rects= */
|
||||
{MakeNormRect(0.48906386, 0.22731927, 0.42905223, 0.34357703,
|
||||
0.008304443)},
|
||||
/* expected_presence= */ {true},
|
||||
/* expected_landmarks_list= */
|
||||
{{GetExpectedLandmarkList(
|
||||
|
|
|
|||
|
|
@ -50,3 +50,15 @@ mediapipe_proto_library(
|
|||
"//mediapipe/framework:calculator_proto",
|
||||
],
|
||||
)
|
||||
|
||||
mediapipe_proto_library(
|
||||
name = "face_landmarker_graph_options_proto",
|
||||
srcs = ["face_landmarker_graph_options.proto"],
|
||||
deps = [
|
||||
":face_landmarks_detector_graph_options_proto",
|
||||
"//mediapipe/framework:calculator_options_proto",
|
||||
"//mediapipe/framework:calculator_proto",
|
||||
"//mediapipe/tasks/cc/core/proto:base_options_proto",
|
||||
"//mediapipe/tasks/cc/vision/face_detector/proto:face_detector_graph_options_proto",
|
||||
],
|
||||
)
|
||||
|
|
|
|||
|
|
@ -0,0 +1,48 @@
|
|||
/* Copyright 2023 The MediaPipe Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
==============================================================================*/
|
||||
|
||||
syntax = "proto2";
|
||||
|
||||
package mediapipe.tasks.vision.face_landmarker.proto;
|
||||
|
||||
import "mediapipe/framework/calculator.proto";
|
||||
import "mediapipe/framework/calculator_options.proto";
|
||||
import "mediapipe/tasks/cc/core/proto/base_options.proto";
|
||||
import "mediapipe/tasks/cc/vision/face_detector/proto/face_detector_graph_options.proto";
|
||||
import "mediapipe/tasks/cc/vision/face_landmarker/proto/face_landmarks_detector_graph_options.proto";
|
||||
|
||||
option java_package = "com.google.mediapipe.tasks.vision.facelandmarker.proto";
|
||||
option java_outer_classname = "FaceLandmarkerGraphOptionsProto";
|
||||
|
||||
message FaceLandmarkerGraphOptions {
|
||||
extend mediapipe.CalculatorOptions {
|
||||
optional FaceLandmarkerGraphOptions ext = 508968150;
|
||||
}
|
||||
// Base options for configuring Task library, such as specifying the TfLite
|
||||
// model file with metadata, accelerator options, etc.
|
||||
optional core.proto.BaseOptions base_options = 1;
|
||||
|
||||
// Options for face detector graph.
|
||||
optional face_detector.proto.FaceDetectorGraphOptions
|
||||
face_detector_graph_options = 2;
|
||||
|
||||
// Options for face landmarks detector graph.
|
||||
optional FaceLandmarksDetectorGraphOptions
|
||||
face_landmarks_detector_graph_options = 3;
|
||||
|
||||
// Minimum confidence for face landmarks tracking to be considered
|
||||
// successfully.
|
||||
optional float min_tracking_confidence = 4 [default = 0.5];
|
||||
}
|
||||
5
mediapipe/tasks/testdata/vision/BUILD
vendored
5
mediapipe/tasks/testdata/vision/BUILD
vendored
|
|
@ -44,6 +44,7 @@ mediapipe_files(srcs = [
|
|||
"face_detection_short_range.tflite",
|
||||
"face_landmark.tflite",
|
||||
"face_landmark_with_attention.tflite",
|
||||
"face_landmarker.task",
|
||||
"fist.jpg",
|
||||
"fist.png",
|
||||
"hair_segmentation.tflite",
|
||||
|
|
@ -92,6 +93,7 @@ exports_files(
|
|||
"face_geometry_expected_out.pbtxt",
|
||||
"gesture_recognizer.task",
|
||||
"portrait_expected_detection.pbtxt",
|
||||
"portrait_expected_face_geometry_with_attention.pbtxt",
|
||||
"portrait_rotated_expected_detection.pbtxt",
|
||||
],
|
||||
)
|
||||
|
|
@ -153,6 +155,7 @@ filegroup(
|
|||
"face_detection_short_range.tflite",
|
||||
"face_landmark.tflite",
|
||||
"face_landmark_with_attention.tflite",
|
||||
"face_landmarker.task",
|
||||
"hair_segmentation.tflite",
|
||||
"hand_landmark_full.tflite",
|
||||
"hand_landmark_lite.tflite",
|
||||
|
|
@ -166,7 +169,6 @@ filegroup(
|
|||
"mobilenet_v2_1.0_224.tflite",
|
||||
"mobilenet_v3_small_100_224_embedder.tflite",
|
||||
"palm_detection_full.tflite",
|
||||
"portrait_expected_face_landmarks.pbtxt",
|
||||
"selfie_segm_128_128_3.tflite",
|
||||
"selfie_segm_144_256_3.tflite",
|
||||
],
|
||||
|
|
@ -189,6 +191,7 @@ filegroup(
|
|||
"pointing_up_landmarks.pbtxt",
|
||||
"pointing_up_rotated_landmarks.pbtxt",
|
||||
"portrait_expected_detection.pbtxt",
|
||||
"portrait_expected_face_geometry_with_attention.pbtxt",
|
||||
"portrait_expected_face_landmarks.pbtxt",
|
||||
"portrait_expected_face_landmarks_with_attention.pbtxt",
|
||||
"portrait_rotated_expected_detection.pbtxt",
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
# proto-file: mediapipe/tasks/cc/vision/face_geometry/proto/environment.proto
|
||||
# proto-message: Environment
|
||||
# proto-file: mediapipe/tasks/cc/vision/face_geometry/proto/face_geometry.proto
|
||||
# proto-message: FaceGeometry
|
||||
mesh {
|
||||
vertex_type: VERTEX_PT
|
||||
primitive_type: TRIANGLE
|
||||
|
|
|
|||
BIN
mediapipe/tasks/testdata/vision/face_landmarker.task
vendored
Normal file
BIN
mediapipe/tasks/testdata/vision/face_landmarker.task
vendored
Normal file
Binary file not shown.
BIN
mediapipe/tasks/testdata/vision/face_landmarker_with_blendshapes.task
vendored
Normal file
BIN
mediapipe/tasks/testdata/vision/face_landmarker_with_blendshapes.task
vendored
Normal file
Binary file not shown.
|
|
@ -2,261 +2,261 @@
|
|||
# proto-message: ClassificationList
|
||||
classification {
|
||||
index: 0
|
||||
score: 4.9559007e-06
|
||||
score: 2.922153e-05
|
||||
label: "_neutral"
|
||||
}
|
||||
classification {
|
||||
index: 1
|
||||
score: 0.22943014
|
||||
score: 0.7923543
|
||||
label: "browDownLeft"
|
||||
}
|
||||
classification {
|
||||
index: 2
|
||||
score: 0.22297752
|
||||
score: 0.81483257
|
||||
label: "browDownRight"
|
||||
}
|
||||
classification {
|
||||
index: 3
|
||||
score: 0.015948873
|
||||
score: 0.0002845049
|
||||
label: "browInnerUp"
|
||||
}
|
||||
classification {
|
||||
index: 4
|
||||
score: 0.006946607
|
||||
score: 0.00049632485
|
||||
label: "browOuterUpLeft"
|
||||
}
|
||||
classification {
|
||||
index: 5
|
||||
score: 0.0070318673
|
||||
score: 0.00050830405
|
||||
label: "browOuterUpRight"
|
||||
}
|
||||
classification {
|
||||
index: 6
|
||||
score: 0.0013679645
|
||||
score: 0.0014010799
|
||||
label: "cheekPuff"
|
||||
}
|
||||
classification {
|
||||
index: 7
|
||||
score: 7.1003383e-06
|
||||
score: 3.1523705e-06
|
||||
label: "cheekSquintLeft"
|
||||
}
|
||||
classification {
|
||||
index: 8
|
||||
score: 5.78299e-06
|
||||
score: 4.7487533e-06
|
||||
label: "cheekSquintRight"
|
||||
}
|
||||
classification {
|
||||
index: 9
|
||||
score: 0.20132238
|
||||
score: 0.2633514
|
||||
label: "eyeBlinkLeft"
|
||||
}
|
||||
classification {
|
||||
index: 10
|
||||
score: 0.16521452
|
||||
score: 0.29687604
|
||||
label: "eyeBlinkRight"
|
||||
}
|
||||
classification {
|
||||
index: 11
|
||||
score: 0.03764786
|
||||
score: 0.15565884
|
||||
label: "eyeLookDownLeft"
|
||||
}
|
||||
classification {
|
||||
index: 12
|
||||
score: 0.04828824
|
||||
score: 0.18480143
|
||||
label: "eyeLookDownRight"
|
||||
}
|
||||
classification {
|
||||
index: 13
|
||||
score: 0.016539993
|
||||
score: 0.054997284
|
||||
label: "eyeLookInLeft"
|
||||
}
|
||||
classification {
|
||||
index: 14
|
||||
score: 0.20026363
|
||||
score: 0.10678173
|
||||
label: "eyeLookInRight"
|
||||
}
|
||||
classification {
|
||||
index: 15
|
||||
score: 0.21363346
|
||||
score: 0.099223085
|
||||
label: "eyeLookOutLeft"
|
||||
}
|
||||
classification {
|
||||
index: 16
|
||||
score: 0.024430025
|
||||
score: 0.06485316
|
||||
label: "eyeLookOutRight"
|
||||
}
|
||||
classification {
|
||||
index: 17
|
||||
score: 0.30147508
|
||||
score: 0.09108365
|
||||
label: "eyeLookUpLeft"
|
||||
}
|
||||
classification {
|
||||
index: 18
|
||||
score: 0.28701693
|
||||
score: 0.090983614
|
||||
label: "eyeLookUpRight"
|
||||
}
|
||||
classification {
|
||||
index: 19
|
||||
score: 0.67143106
|
||||
score: 0.7040458
|
||||
label: "eyeSquintLeft"
|
||||
}
|
||||
classification {
|
||||
index: 20
|
||||
score: 0.5306328
|
||||
score: 0.5759947
|
||||
label: "eyeSquintRight"
|
||||
}
|
||||
classification {
|
||||
index: 21
|
||||
score: 0.0041342233
|
||||
score: 0.002923721
|
||||
label: "eyeWideLeft"
|
||||
}
|
||||
classification {
|
||||
index: 22
|
||||
score: 0.005231879
|
||||
score: 0.0027232585
|
||||
label: "eyeWideRight"
|
||||
}
|
||||
classification {
|
||||
index: 23
|
||||
score: 0.009427094
|
||||
score: 0.0028721786
|
||||
label: "jawForward"
|
||||
}
|
||||
classification {
|
||||
index: 24
|
||||
score: 0.0015789346
|
||||
score: 0.0014818686
|
||||
label: "jawLeft"
|
||||
}
|
||||
classification {
|
||||
index: 25
|
||||
score: 0.073719256
|
||||
score: 0.13099338
|
||||
label: "jawOpen"
|
||||
}
|
||||
classification {
|
||||
index: 26
|
||||
score: 0.00046979196
|
||||
score: 0.00025238062
|
||||
label: "jawRight"
|
||||
}
|
||||
classification {
|
||||
index: 27
|
||||
score: 0.0011400756
|
||||
score: 0.013557238
|
||||
label: "mouthClose"
|
||||
}
|
||||
classification {
|
||||
index: 28
|
||||
score: 0.0060502808
|
||||
score: 0.040049534
|
||||
label: "mouthDimpleLeft"
|
||||
}
|
||||
classification {
|
||||
index: 29
|
||||
score: 0.013351685
|
||||
score: 0.017489946
|
||||
label: "mouthDimpleRight"
|
||||
}
|
||||
classification {
|
||||
index: 30
|
||||
score: 0.09859665
|
||||
score: 0.00069562776
|
||||
label: "mouthFrownLeft"
|
||||
}
|
||||
classification {
|
||||
index: 31
|
||||
score: 0.08897466
|
||||
score: 0.00082510535
|
||||
label: "mouthFrownRight"
|
||||
}
|
||||
classification {
|
||||
index: 32
|
||||
score: 0.0020718675
|
||||
score: 0.008079494
|
||||
label: "mouthFunnel"
|
||||
}
|
||||
classification {
|
||||
index: 33
|
||||
score: 6.42887e-06
|
||||
score: 0.000491791
|
||||
label: "mouthLeft"
|
||||
}
|
||||
classification {
|
||||
index: 34
|
||||
score: 0.68950605
|
||||
score: 0.067228556
|
||||
label: "mouthLowerDownLeft"
|
||||
}
|
||||
classification {
|
||||
index: 35
|
||||
score: 0.7864029
|
||||
score: 0.17653553
|
||||
label: "mouthLowerDownRight"
|
||||
}
|
||||
classification {
|
||||
index: 36
|
||||
score: 0.056456964
|
||||
score: 0.14764099
|
||||
label: "mouthPressLeft"
|
||||
}
|
||||
classification {
|
||||
index: 37
|
||||
score: 0.037348792
|
||||
score: 0.11692603
|
||||
label: "mouthPressRight"
|
||||
}
|
||||
classification {
|
||||
index: 38
|
||||
score: 0.00067001814
|
||||
score: 0.0016829089
|
||||
label: "mouthPucker"
|
||||
}
|
||||
classification {
|
||||
index: 39
|
||||
score: 0.005189785
|
||||
score: 0.0010300461
|
||||
label: "mouthRight"
|
||||
}
|
||||
classification {
|
||||
index: 40
|
||||
score: 0.018723497
|
||||
score: 0.01507229
|
||||
label: "mouthRollLower"
|
||||
}
|
||||
classification {
|
||||
index: 41
|
||||
score: 0.052819636
|
||||
score: 0.11626337
|
||||
label: "mouthRollUpper"
|
||||
}
|
||||
classification {
|
||||
index: 42
|
||||
score: 0.0033772716
|
||||
score: 0.004975724
|
||||
label: "mouthShrugLower"
|
||||
}
|
||||
classification {
|
||||
index: 43
|
||||
score: 0.0031609535
|
||||
score: 0.004570691
|
||||
label: "mouthShrugUpper"
|
||||
}
|
||||
classification {
|
||||
index: 44
|
||||
score: 0.49639142
|
||||
score: 0.9271871
|
||||
label: "mouthSmileLeft"
|
||||
}
|
||||
classification {
|
||||
index: 45
|
||||
score: 0.4014515
|
||||
score: 0.9062751
|
||||
label: "mouthSmileRight"
|
||||
}
|
||||
classification {
|
||||
index: 46
|
||||
score: 0.5825701
|
||||
score: 0.037454817
|
||||
label: "mouthStretchLeft"
|
||||
}
|
||||
classification {
|
||||
index: 47
|
||||
score: 0.73058575
|
||||
score: 0.1777958
|
||||
label: "mouthStretchRight"
|
||||
}
|
||||
classification {
|
||||
index: 48
|
||||
score: 0.13561466
|
||||
score: 0.8198947
|
||||
label: "mouthUpperUpLeft"
|
||||
}
|
||||
classification {
|
||||
index: 49
|
||||
score: 0.20078722
|
||||
score: 0.769086
|
||||
label: "mouthUpperUpRight"
|
||||
}
|
||||
classification {
|
||||
index: 50
|
||||
score: 3.3396598e-06
|
||||
score: 7.096563e-07
|
||||
label: "noseSneerLeft"
|
||||
}
|
||||
classification {
|
||||
index: 51
|
||||
score: 1.3096546e-05
|
||||
score: 9.818824e-06
|
||||
label: "noseSneerRight"
|
||||
}
|
||||
|
|
|
|||
5060
mediapipe/tasks/testdata/vision/portrait_expected_face_geometry_with_attention.pbtxt
vendored
Normal file
5060
mediapipe/tasks/testdata/vision/portrait_expected_face_geometry_with_attention.pbtxt
vendored
Normal file
File diff suppressed because it is too large
Load Diff
50
third_party/external_files.bzl
vendored
50
third_party/external_files.bzl
vendored
|
|
@ -70,6 +70,12 @@ def external_files():
|
|||
urls = ["https://storage.googleapis.com/mediapipe-assets/BUILD?generation=1661875663693976"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_BUILD_orig",
|
||||
sha256 = "64d5343a6a5f9be06db0a5074a2260f9ae63a989fe01702832cd215680dc19c1",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/BUILD.orig?generation=1678323576393653"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_burger_crop_jpg",
|
||||
sha256 = "8f58de573f0bf59a49c3d86cfabb9ad4061481f574aa049177e8da3963dddc50",
|
||||
|
|
@ -300,8 +306,20 @@ def external_files():
|
|||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_face_geometry_expected_out_pbtxt",
|
||||
sha256 = "611b203bca40e547ae75bf0822fda0695d512d02940e7af08a70068eaa8524f7",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/face_geometry_expected_out.pbtxt?generation=1677787710308910"],
|
||||
sha256 = "4a4ed08055a5bc9281472dd60180d11f0cdc9a15fa1788d87a58af3d06b2c6e4",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/face_geometry_expected_out.pbtxt?generation=1678323580380646"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_face_landmarker_task",
|
||||
sha256 = "7cf2bbf1842c429e9defee38e7f1c4238978d8a6faf2da145bb19846f86bd2f4",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/face_landmarker.task?generation=1678323583183024"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_face_landmarker_with_blendshapes_task",
|
||||
sha256 = "a75c1ba70e4b8568000af2ad0b355ed559ab5d5793db50fa9ad241f8dc4fad5f",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/face_landmarker_with_blendshapes.task?generation=1678323586260800"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
|
|
@ -316,6 +334,12 @@ def external_files():
|
|||
urls = ["https://storage.googleapis.com/mediapipe-assets/face_landmark_with_attention.tflite?generation=1676415468821650"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_face_stylization_dummy_tflite",
|
||||
sha256 = "f57fd2d5638def25466f6fec142eb3397d8ad99a9bd0a9344b622bad7c3f0376",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/face_stylization_dummy.tflite?generation=1678323589048063"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_feature_tensor_meta_json",
|
||||
sha256 = "b2c30ddfd495956ce81085f8a143422f4310b002cfbf1c594ff2ee0576e29d6f",
|
||||
|
|
@ -508,6 +532,12 @@ def external_files():
|
|||
urls = ["https://storage.googleapis.com/mediapipe-assets/labels.txt?generation=1667892497527642"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_language_detector_tflite",
|
||||
sha256 = "5f64d821110dd2a3280546e8cd59dff09547e25d5f5c9711ec3f03416414dbb2",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/language_detector.tflite?generation=1678323592870401"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_left_hands_jpg",
|
||||
sha256 = "4b5134daa4cb60465535239535f9f74c2842aba3aa5fd30bf04ef5678f93d87f",
|
||||
|
|
@ -780,8 +810,8 @@ def external_files():
|
|||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_portrait_expected_blendshapes_with_attention_pbtxt",
|
||||
sha256 = "0142d56705093c3d79ea5ee79b8e9454499abee00fc059491e6ca14f5fbab862",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/portrait_expected_blendshapes_with_attention.pbtxt?generation=1678218364703223"],
|
||||
sha256 = "3f8f698d8ed81346c6f13d1cc85190fd4a58b021e664d336997d29818b8ffbb6",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/portrait_expected_blendshapes_with_attention.pbtxt?generation=1678323598426417"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
|
|
@ -790,6 +820,12 @@ def external_files():
|
|||
urls = ["https://storage.googleapis.com/mediapipe-assets/portrait_expected_detection.pbtxt?generation=1677044311581104"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_portrait_expected_face_geometry_with_attention_pbtxt",
|
||||
sha256 = "5cc57b8da3ad0527dce581fe1309f6b36043e5837e3f4f5af5e24005a99dc52a",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/portrait_expected_face_geometry_with_attention.pbtxt?generation=1678323601064393"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_portrait_expected_face_landmarks_pbtxt",
|
||||
sha256 = "4ac8587379bd072c36cda0d7345f5e592fae51b30522475e0b49c18aab108ce7",
|
||||
|
|
@ -850,6 +886,12 @@ def external_files():
|
|||
urls = ["https://storage.googleapis.com/mediapipe-assets/pose_landmark_lite.tflite?generation=1661875901231143"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_ptm_512_hdt_ptm_woid_tflite",
|
||||
sha256 = "2baa1c9783d03dd26f91e3c49efbcab11dd1361ff80e40e7209e81f84f281b6a",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/ptm_512_hdt_ptm_woid.tflite?generation=1678323604771164"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_README_md",
|
||||
sha256 = "a96d08c9c70cd9717207ed72c926e02e5eada751f00bdc5d3a7e82e3492b72cb",
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user