Add mediapipe tasks face detector graph
PiperOrigin-RevId: 504078951
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Copybara-Service
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61
mediapipe/tasks/cc/vision/face_detector/BUILD
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61
mediapipe/tasks/cc/vision/face_detector/BUILD
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# Copyright 2023 The MediaPipe Authors. All Rights Reserved.
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#
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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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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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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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package(default_visibility = [
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# "//mediapipe/tasks:internal",
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"//visibility:public",
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])
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licenses(["notice"])
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cc_library(
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name = "face_detector_graph",
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srcs = ["face_detector_graph.cc"],
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deps = [
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"//mediapipe/calculators/core:clip_vector_size_calculator",
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"//mediapipe/calculators/core:clip_vector_size_calculator_cc_proto",
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"//mediapipe/calculators/tensor:image_to_tensor_calculator_cc_proto",
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"//mediapipe/calculators/tensor:inference_calculator",
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"//mediapipe/calculators/tensor:tensors_to_detections_calculator",
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"//mediapipe/calculators/tensor:tensors_to_detections_calculator_cc_proto",
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"//mediapipe/calculators/tflite:ssd_anchors_calculator",
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"//mediapipe/calculators/tflite:ssd_anchors_calculator_cc_proto",
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"//mediapipe/calculators/util:detection_label_id_to_text_calculator",
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"//mediapipe/calculators/util:detection_label_id_to_text_calculator_cc_proto",
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"//mediapipe/calculators/util:detection_projection_calculator",
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"//mediapipe/calculators/util:detections_to_rects_calculator",
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"//mediapipe/calculators/util:detections_to_rects_calculator_cc_proto",
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"//mediapipe/calculators/util:non_max_suppression_calculator",
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"//mediapipe/calculators/util:non_max_suppression_calculator_cc_proto",
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"//mediapipe/calculators/util:rect_transformation_calculator",
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"//mediapipe/calculators/util:rect_transformation_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:detection_cc_proto",
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"//mediapipe/framework/formats:image",
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"//mediapipe/framework/formats:rect_cc_proto",
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"//mediapipe/framework/formats:tensor",
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"//mediapipe/tasks/cc:common",
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"//mediapipe/tasks/cc/components/processors:image_preprocessing_graph",
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"//mediapipe/tasks/cc/core:model_resources",
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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/core/proto:inference_subgraph_cc_proto",
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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/utils:image_tensor_specs",
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"@com_google_absl//absl/status",
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"@com_google_absl//absl/status:statusor",
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],
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alwayslink = 1,
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)
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208
mediapipe/tasks/cc/vision/face_detector/face_detector_graph.cc
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208
mediapipe/tasks/cc/vision/face_detector/face_detector_graph.cc
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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 <vector>
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#include "absl/status/status.h"
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#include "absl/status/statusor.h"
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#include "mediapipe/calculators/core/clip_vector_size_calculator.pb.h"
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#include "mediapipe/calculators/tensor/image_to_tensor_calculator.pb.h"
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#include "mediapipe/calculators/tensor/tensors_to_detections_calculator.pb.h"
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#include "mediapipe/calculators/tflite/ssd_anchors_calculator.pb.h"
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#include "mediapipe/calculators/util/detection_label_id_to_text_calculator.pb.h"
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#include "mediapipe/calculators/util/detections_to_rects_calculator.pb.h"
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#include "mediapipe/calculators/util/non_max_suppression_calculator.pb.h"
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#include "mediapipe/calculators/util/rect_transformation_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/detection.pb.h"
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#include "mediapipe/framework/formats/image.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/tasks/cc/common.h"
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#include "mediapipe/tasks/cc/components/processors/image_preprocessing_graph.h"
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#include "mediapipe/tasks/cc/core/model_resources.h"
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#include "mediapipe/tasks/cc/core/model_task_graph.h"
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#include "mediapipe/tasks/cc/core/proto/inference_subgraph.pb.h"
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#include "mediapipe/tasks/cc/core/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/utils/image_tensor_specs.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_detector {
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using ::mediapipe::NormalizedRect;
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using ::mediapipe::Tensor;
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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::Source;
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using ::mediapipe::tasks::vision::face_detector::proto::
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FaceDetectorGraphOptions;
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namespace {
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constexpr char kImageTag[] = "IMAGE";
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constexpr char kNormRectTag[] = "NORM_RECT";
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constexpr char kDetectionsTag[] = "DETECTIONS";
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void ConfigureSsdAnchorsCalculator(
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mediapipe::SsdAnchorsCalculatorOptions* options) {
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// TODO config SSD anchors parameters from metadata.
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options->set_num_layers(1);
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options->set_min_scale(0.1484375);
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options->set_max_scale(0.75);
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options->set_input_size_height(192);
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options->set_input_size_width(192);
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options->set_anchor_offset_x(0.5);
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options->set_anchor_offset_y(0.5);
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options->add_strides(4);
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options->add_aspect_ratios(1.0);
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options->set_fixed_anchor_size(true);
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options->set_interpolated_scale_aspect_ratio(0.0);
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}
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void ConfigureTensorsToDetectionsCalculator(
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const FaceDetectorGraphOptions& tasks_options,
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mediapipe::TensorsToDetectionsCalculatorOptions* options) {
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// TODO use metadata to configure these fields.
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options->set_num_classes(1);
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options->set_num_boxes(2304);
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options->set_num_coords(16);
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options->set_box_coord_offset(0);
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options->set_keypoint_coord_offset(4);
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options->set_num_keypoints(6);
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options->set_num_values_per_keypoint(2);
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options->set_sigmoid_score(true);
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options->set_score_clipping_thresh(100.0);
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options->set_reverse_output_order(true);
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options->set_min_score_thresh(tasks_options.min_detection_confidence());
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options->set_x_scale(192.0);
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options->set_y_scale(192.0);
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options->set_w_scale(192.0);
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options->set_h_scale(192.0);
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}
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void ConfigureNonMaxSuppressionCalculator(
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const FaceDetectorGraphOptions& tasks_options,
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mediapipe::NonMaxSuppressionCalculatorOptions* options) {
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options->set_min_suppression_threshold(
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tasks_options.min_suppression_threshold());
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options->set_overlap_type(
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mediapipe::NonMaxSuppressionCalculatorOptions::INTERSECTION_OVER_UNION);
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options->set_algorithm(
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mediapipe::NonMaxSuppressionCalculatorOptions::WEIGHTED);
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}
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} // namespace
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class FaceDetectorGraph : 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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ASSIGN_OR_RETURN(const auto* model_resources,
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CreateModelResources<FaceDetectorGraphOptions>(sc));
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Graph graph;
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ASSIGN_OR_RETURN(auto face_detections,
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BuildFaceDetectionSubgraph(
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sc->Options<FaceDetectorGraphOptions>(),
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*model_resources, graph[Input<Image>(kImageTag)],
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graph[Input<NormalizedRect>(kNormRectTag)], graph));
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face_detections >> graph[Output<std::vector<Detection>>(kDetectionsTag)];
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return graph.GetConfig();
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}
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private:
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absl::StatusOr<Source<std::vector<Detection>>> BuildFaceDetectionSubgraph(
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const FaceDetectorGraphOptions& subgraph_options,
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const core::ModelResources& model_resources, Source<Image> image_in,
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Source<NormalizedRect> norm_rect_in, Graph& graph) {
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// Image preprocessing subgraph to convert image to tensor for the tflite
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// model.
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auto& preprocessing = graph.AddNode(
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"mediapipe.tasks.components.processors.ImagePreprocessingGraph");
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bool use_gpu =
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components::processors::DetermineImagePreprocessingGpuBackend(
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subgraph_options.base_options().acceleration());
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MP_RETURN_IF_ERROR(components::processors::ConfigureImagePreprocessingGraph(
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model_resources, use_gpu,
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&preprocessing.GetOptions<
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components::processors::proto::ImagePreprocessingGraphOptions>()));
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auto& image_to_tensor_options =
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*preprocessing
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.GetOptions<components::processors::proto::
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ImagePreprocessingGraphOptions>()
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.mutable_image_to_tensor_options();
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image_to_tensor_options.set_keep_aspect_ratio(true);
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image_to_tensor_options.set_border_mode(
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mediapipe::ImageToTensorCalculatorOptions::BORDER_ZERO);
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image_in >> preprocessing.In("IMAGE");
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norm_rect_in >> preprocessing.In("NORM_RECT");
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auto preprocessed_tensors = preprocessing.Out("TENSORS");
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auto matrix = preprocessing.Out("MATRIX");
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// Face detection model inferece.
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auto& inference = AddInference(
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model_resources, subgraph_options.base_options().acceleration(), graph);
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preprocessed_tensors >> inference.In("TENSORS");
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auto model_output_tensors =
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inference.Out("TENSORS").Cast<std::vector<Tensor>>();
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// Generates a single side packet containing a vector of SSD anchors.
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auto& ssd_anchor = graph.AddNode("SsdAnchorsCalculator");
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ConfigureSsdAnchorsCalculator(
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&ssd_anchor.GetOptions<mediapipe::SsdAnchorsCalculatorOptions>());
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auto anchors = ssd_anchor.SideOut("");
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// Converts output tensors to Detections.
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auto& tensors_to_detections =
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graph.AddNode("TensorsToDetectionsCalculator");
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ConfigureTensorsToDetectionsCalculator(
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subgraph_options,
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&tensors_to_detections
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.GetOptions<mediapipe::TensorsToDetectionsCalculatorOptions>());
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model_output_tensors >> tensors_to_detections.In("TENSORS");
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anchors >> tensors_to_detections.SideIn("ANCHORS");
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auto detections = tensors_to_detections.Out("DETECTIONS");
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// Non maximum suppression removes redundant face detections.
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auto& non_maximum_suppression =
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graph.AddNode("NonMaxSuppressionCalculator");
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ConfigureNonMaxSuppressionCalculator(
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subgraph_options,
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&non_maximum_suppression
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.GetOptions<mediapipe::NonMaxSuppressionCalculatorOptions>());
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detections >> non_maximum_suppression.In("");
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auto nms_detections = non_maximum_suppression.Out("");
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// Projects detections back into the input image coordinates system.
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auto& detection_projection = graph.AddNode("DetectionProjectionCalculator");
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nms_detections >> detection_projection.In("DETECTIONS");
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matrix >> detection_projection.In("PROJECTION_MATRIX");
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auto face_detections =
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detection_projection[Output<std::vector<Detection>>("DETECTIONS")];
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return {face_detections};
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}
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};
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REGISTER_MEDIAPIPE_GRAPH(
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::mediapipe::tasks::vision::face_detector::FaceDetectorGraph);
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} // namespace face_detector
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} // namespace vision
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} // namespace tasks
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} // namespace mediapipe
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@ -0,0 +1,183 @@
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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 <cmath>
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#include <iostream>
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#include <memory>
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#include <string>
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#include <utility>
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#include <vector>
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#include "absl/flags/flag.h"
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#include "absl/status/statusor.h"
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#include "absl/strings/str_format.h"
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#include "absl/strings/string_view.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/calculator_framework.h"
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#include "mediapipe/framework/deps/file_path.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/rect.pb.h"
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#include "mediapipe/framework/packet.h"
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#include "mediapipe/framework/port/file_helpers.h"
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#include "mediapipe/framework/port/gmock.h"
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#include "mediapipe/framework/port/gtest.h"
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#include "mediapipe/framework/port/parse_text_proto.h"
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#include "mediapipe/tasks/cc/core/mediapipe_builtin_op_resolver.h"
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#include "mediapipe/tasks/cc/core/model_resources.h"
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#include "mediapipe/tasks/cc/core/proto/base_options.pb.h"
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#include "mediapipe/tasks/cc/core/proto/external_file.pb.h"
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#include "mediapipe/tasks/cc/core/task_runner.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/utils/image_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_detector {
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namespace {
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using ::file::Defaults;
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using ::file::GetTextProto;
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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::Source;
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using ::mediapipe::file::JoinPath;
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using ::mediapipe::tasks::core::TaskRunner;
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using ::mediapipe::tasks::vision::DecodeImageFromFile;
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using ::mediapipe::tasks::vision::face_detector::proto::
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FaceDetectorGraphOptions;
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using ::testing::EqualsProto;
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using ::testing::Pointwise;
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using ::testing::TestParamInfo;
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using ::testing::TestWithParam;
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using ::testing::Values;
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using ::testing::proto::Approximately;
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using ::testing::proto::Partially;
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constexpr char kTestDataDirectory[] = "/mediapipe/tasks/testdata/vision/";
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constexpr char kFullRangeBlazeFaceModel[] = "face_detection_full_range.tflite";
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constexpr char kFullRangeSparseBlazeFaceModel[] =
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"face_detection_full_range_sparse.tflite";
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constexpr char kPortraitImage[] = "portrait.jpg";
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constexpr char kPortraitExpectedDetection[] =
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"portrait_expected_detection.pbtxt";
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constexpr char kImageTag[] = "IMAGE";
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constexpr char kImageName[] = "image";
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constexpr char kNormRectTag[] = "NORM_RECT";
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constexpr char kNormRectName[] = "norm_rect";
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constexpr char kDetectionsTag[] = "DETECTIONS";
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constexpr char kDetectionsName[] = "detections";
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constexpr float kFaceDetectionMaxDiff = 0.01;
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// Helper function to create a TaskRunner.
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absl::StatusOr<std::unique_ptr<TaskRunner>> CreateTaskRunner(
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absl::string_view model_name) {
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Graph graph;
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auto& face_detector_graph =
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graph.AddNode("mediapipe.tasks.vision.face_detector.FaceDetectorGraph");
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auto options = std::make_unique<FaceDetectorGraphOptions>();
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options->mutable_base_options()->mutable_model_asset()->set_file_name(
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JoinPath("./", kTestDataDirectory, model_name));
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options->set_min_detection_confidence(0.6);
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options->set_min_suppression_threshold(0.3);
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face_detector_graph.GetOptions<FaceDetectorGraphOptions>().Swap(
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options.get());
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graph[Input<Image>(kImageTag)].SetName(kImageName) >>
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face_detector_graph.In(kImageTag);
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graph[Input<NormalizedRect>(kNormRectTag)].SetName(kNormRectName) >>
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face_detector_graph.In(kNormRectTag);
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face_detector_graph.Out(kDetectionsTag).SetName(kDetectionsName) >>
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graph[Output<std::vector<Detection>>(kDetectionsTag)];
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return TaskRunner::Create(
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graph.GetConfig(), std::make_unique<core::MediaPipeBuiltinOpResolver>());
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}
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|
||||
Detection GetExpectedFaceDetectionResult(absl::string_view file_name) {
|
||||
Detection detection;
|
||||
CHECK_OK(GetTextProto(file::JoinPath("./", kTestDataDirectory, file_name),
|
||||
&detection, Defaults()))
|
||||
<< "Expected face detection result does not exist.";
|
||||
return detection;
|
||||
}
|
||||
|
||||
struct TestParams {
|
||||
// The name of this test, for convenience when displaying test results.
|
||||
std::string test_name;
|
||||
// The filename of face landmark detection model.
|
||||
std::string face_detection_model_name;
|
||||
// The filename of test image.
|
||||
std::string test_image_name;
|
||||
// Expected face detection results.
|
||||
std::vector<Detection> expected_result;
|
||||
};
|
||||
|
||||
class FaceDetectorGraphTest : public testing::TestWithParam<TestParams> {};
|
||||
|
||||
TEST_P(FaceDetectorGraphTest, Succeed) {
|
||||
MP_ASSERT_OK_AND_ASSIGN(
|
||||
Image image, DecodeImageFromFile(JoinPath("./", kTestDataDirectory,
|
||||
GetParam().test_image_name)));
|
||||
NormalizedRect input_norm_rect;
|
||||
input_norm_rect.set_x_center(0.5);
|
||||
input_norm_rect.set_y_center(0.5);
|
||||
input_norm_rect.set_width(1.0);
|
||||
input_norm_rect.set_height(1.0);
|
||||
MP_ASSERT_OK_AND_ASSIGN(
|
||||
auto task_runner, CreateTaskRunner(GetParam().face_detection_model_name));
|
||||
auto output_packets = task_runner->Process(
|
||||
{{kImageName, MakePacket<Image>(std::move(image))},
|
||||
{kNormRectName,
|
||||
MakePacket<NormalizedRect>(std::move(input_norm_rect))}});
|
||||
MP_ASSERT_OK(output_packets);
|
||||
const std::vector<Detection>& face_detections =
|
||||
(*output_packets)[kDetectionsName].Get<std::vector<Detection>>();
|
||||
EXPECT_THAT(face_detections, Pointwise(Approximately(Partially(EqualsProto()),
|
||||
kFaceDetectionMaxDiff),
|
||||
GetParam().expected_result));
|
||||
}
|
||||
|
||||
INSTANTIATE_TEST_SUITE_P(
|
||||
FaceDetectorGraphTest, FaceDetectorGraphTest,
|
||||
Values(TestParams{.test_name = "FullRange",
|
||||
.face_detection_model_name = kFullRangeBlazeFaceModel,
|
||||
.test_image_name = kPortraitImage,
|
||||
.expected_result = {GetExpectedFaceDetectionResult(
|
||||
kPortraitExpectedDetection)}},
|
||||
TestParams{
|
||||
.test_name = "FullRangeSparse",
|
||||
.face_detection_model_name = kFullRangeSparseBlazeFaceModel,
|
||||
.test_image_name = kPortraitImage,
|
||||
.expected_result = {GetExpectedFaceDetectionResult(
|
||||
kPortraitExpectedDetection)}}),
|
||||
[](const TestParamInfo<FaceDetectorGraphTest::ParamType>& info) {
|
||||
return info.param.test_name;
|
||||
});
|
||||
|
||||
} // namespace
|
||||
} // namespace face_detector
|
||||
} // namespace vision
|
||||
} // namespace tasks
|
||||
} // namespace mediapipe
|
||||
31
mediapipe/tasks/cc/vision/face_detector/proto/BUILD
Normal file
31
mediapipe/tasks/cc/vision/face_detector/proto/BUILD
Normal file
|
|
@ -0,0 +1,31 @@
|
|||
# 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.
|
||||
|
||||
load("//mediapipe/framework/port:build_config.bzl", "mediapipe_proto_library")
|
||||
|
||||
package(default_visibility = [
|
||||
"//mediapipe/tasks:internal",
|
||||
])
|
||||
|
||||
licenses(["notice"])
|
||||
|
||||
mediapipe_proto_library(
|
||||
name = "face_detector_graph_options_proto",
|
||||
srcs = ["face_detector_graph_options.proto"],
|
||||
deps = [
|
||||
"//mediapipe/framework:calculator_options_proto",
|
||||
"//mediapipe/framework:calculator_proto",
|
||||
"//mediapipe/tasks/cc/core/proto:base_options_proto",
|
||||
],
|
||||
)
|
||||
|
|
@ -0,0 +1,42 @@
|
|||
/* 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_detector.proto;
|
||||
|
||||
import "mediapipe/framework/calculator.proto";
|
||||
import "mediapipe/framework/calculator_options.proto";
|
||||
import "mediapipe/tasks/cc/core/proto/base_options.proto";
|
||||
|
||||
option java_package = "com.google.mediapipe.tasks.vision.facedetector.proto";
|
||||
option java_outer_classname = "FaceDetectorGraphOptionsProto";
|
||||
|
||||
message FaceDetectorGraphOptions {
|
||||
extend mediapipe.CalculatorOptions {
|
||||
optional FaceDetectorGraphOptions ext = 502141897;
|
||||
}
|
||||
// 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;
|
||||
|
||||
// Minimum confidence value ([0.0, 1.0]) for confidence score to be considered
|
||||
// successfully detecting a face in the image.
|
||||
optional float min_detection_confidence = 2 [default = 0.5];
|
||||
|
||||
// IoU threshold ([0,0, 1.0]) for non-maximu-suppression to be considered
|
||||
// duplicate detetions.
|
||||
optional float min_suppression_threshold = 3 [default = 0.5];
|
||||
}
|
||||
8
mediapipe/tasks/testdata/vision/BUILD
vendored
8
mediapipe/tasks/testdata/vision/BUILD
vendored
|
|
@ -37,6 +37,8 @@ mediapipe_files(srcs = [
|
|||
"coco_ssd_mobilenet_v1_1.0_quant_2018_06_29.tflite",
|
||||
"coco_ssd_mobilenet_v1_1.0_quant_2018_06_29_with_dummy_score_calibration.tflite",
|
||||
"deeplabv3.tflite",
|
||||
"face_detection_full_range.tflite",
|
||||
"face_detection_full_range_sparse.tflite",
|
||||
"fist.jpg",
|
||||
"fist.png",
|
||||
"hand_landmark_full.tflite",
|
||||
|
|
@ -58,6 +60,7 @@ mediapipe_files(srcs = [
|
|||
"palm_detection_full.tflite",
|
||||
"pointing_up.jpg",
|
||||
"pointing_up_rotated.jpg",
|
||||
"portrait.jpg",
|
||||
"right_hands.jpg",
|
||||
"right_hands_rotated.jpg",
|
||||
"segmentation_golden_rotation0.png",
|
||||
|
|
@ -79,6 +82,7 @@ exports_files(
|
|||
"expected_right_down_hand_landmarks.prototxt",
|
||||
"expected_right_up_hand_landmarks.prototxt",
|
||||
"gesture_recognizer.task",
|
||||
"portrait_expected_detection.pbtxt",
|
||||
],
|
||||
)
|
||||
|
||||
|
|
@ -106,6 +110,7 @@ filegroup(
|
|||
"multi_objects_rotated.jpg",
|
||||
"pointing_up.jpg",
|
||||
"pointing_up_rotated.jpg",
|
||||
"portrait.jpg",
|
||||
"right_hands.jpg",
|
||||
"right_hands_rotated.jpg",
|
||||
"segmentation_golden_rotation0.png",
|
||||
|
|
@ -129,6 +134,8 @@ filegroup(
|
|||
"coco_ssd_mobilenet_v1_1.0_quant_2018_06_29.tflite",
|
||||
"coco_ssd_mobilenet_v1_1.0_quant_2018_06_29_with_dummy_score_calibration.tflite",
|
||||
"deeplabv3.tflite",
|
||||
"face_detection_full_range.tflite",
|
||||
"face_detection_full_range_sparse.tflite",
|
||||
"hand_landmark_full.tflite",
|
||||
"hand_landmark_lite.tflite",
|
||||
"hand_landmarker.task",
|
||||
|
|
@ -161,6 +168,7 @@ filegroup(
|
|||
"hand_detector_result_two_hands.pbtxt",
|
||||
"pointing_up_landmarks.pbtxt",
|
||||
"pointing_up_rotated_landmarks.pbtxt",
|
||||
"portrait_expected_detection.pbtxt",
|
||||
"thumb_up_landmarks.pbtxt",
|
||||
"thumb_up_rotated_landmarks.pbtxt",
|
||||
"victory_landmarks.pbtxt",
|
||||
|
|
|
|||
35
mediapipe/tasks/testdata/vision/portrait_expected_detection.pbtxt
vendored
Normal file
35
mediapipe/tasks/testdata/vision/portrait_expected_detection.pbtxt
vendored
Normal file
|
|
@ -0,0 +1,35 @@
|
|||
# proto-file: mediapipe/framework/formats/detection.proto
|
||||
# proto-message: Detection
|
||||
location_data {
|
||||
format: RELATIVE_BOUNDING_BOX
|
||||
relative_bounding_box {
|
||||
xmin: 0.35494408
|
||||
ymin: 0.1059662
|
||||
width: 0.28768203
|
||||
height: 0.23037356
|
||||
}
|
||||
relative_keypoints {
|
||||
x: 0.44416338
|
||||
y: 0.17643969
|
||||
}
|
||||
relative_keypoints {
|
||||
x: 0.55514044
|
||||
y: 0.17731678
|
||||
}
|
||||
relative_keypoints {
|
||||
x: 0.5046702
|
||||
y: 0.2265771
|
||||
}
|
||||
relative_keypoints {
|
||||
x: 0.50227845
|
||||
y: 0.2719954
|
||||
}
|
||||
relative_keypoints {
|
||||
x: 0.37245658
|
||||
y: 0.20143759
|
||||
}
|
||||
relative_keypoints {
|
||||
x: 0.6084143
|
||||
y: 0.20409837
|
||||
}
|
||||
}
|
||||
20
third_party/external_files.bzl
vendored
20
third_party/external_files.bzl
vendored
|
|
@ -240,14 +240,14 @@ def external_files():
|
|||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_face_detection_full_range_sparse_tflite",
|
||||
sha256 = "671dd2f9ed11a78436fc21cc42357a803dfc6f73e9fb86541be942d5716c2dce",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/face_detection_full_range_sparse.tflite?generation=1661875739104017"],
|
||||
sha256 = "2c3728e6da56f21e21a320433396fb06d40d9088f2247c05e5635a688d45dfe1",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/face_detection_full_range_sparse.tflite?generation=1674261618323821"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_face_detection_full_range_tflite",
|
||||
sha256 = "99bf9494d84f50acc6617d89873f71bf6635a841ea699c17cb3377f9507cfec3",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/face_detection_full_range.tflite?generation=1661875742733283"],
|
||||
sha256 = "3698b18f063835bc609069ef052228fbe86d9c9a6dc8dcb7c7c2d69aed2b181b",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/face_detection_full_range.tflite?generation=1674261620964007"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
|
|
@ -712,6 +712,18 @@ def external_files():
|
|||
urls = ["https://storage.googleapis.com/mediapipe-assets/pointing_up_rotated_landmarks.pbtxt?generation=1666629486774022"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_portrait_expected_detection_pbtxt",
|
||||
sha256 = "bb54e08e87844ef14bb185d5cb808908eb6011bfa6db48bd22d9650f6fda338b",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/portrait_expected_detection.pbtxt?generation=1674261627835475"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_portrait_jpg",
|
||||
sha256 = "a6f11efaa834706db23f275b6115058fa87fc7f14362681e6abe14e82749de3e",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/portrait.jpg?generation=1674261630039907"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_pose_detection_tflite",
|
||||
sha256 = "a63c614bef30d35947f13be361820b1e4e3bec9cfeebf4d11216a18373108e85",
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user