Update face detector graph for downstream face landmarks graph.
PiperOrigin-RevId: 511566984
This commit is contained in:
MediaPipe Team
Copybara-Service
parent
fbbc13d756
commit
000aeeb036
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@ -31,9 +31,8 @@ cc_library(
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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:detection_transformation_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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@ -21,7 +21,6 @@ limitations under the License.
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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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@ -58,21 +57,40 @@ 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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constexpr char kAnchorsTag[] = "ANCHORS";
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constexpr char kImageSizeTag[] = "IMAGE_SIZE";
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constexpr char kNormRectsTag[] = "NORM_RECTS";
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constexpr char kProjectionMatrixTag[] = "PROJECTION_MATRIX";
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constexpr char kTensorsTag[] = "TENSORS";
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constexpr char kMatrixTag[] = "MATRIX";
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constexpr char kFaceRectsTag[] = "FACE_RECTS";
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constexpr char kExpandedFaceRectsTag[] = "EXPANDED_FACE_RECTS";
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constexpr char kPixelDetectionsTag[] = "PIXEL_DETECTIONS";
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struct FaceDetectionOuts {
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Source<std::vector<Detection>> face_detections;
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Source<std::vector<NormalizedRect>> face_rects;
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Source<std::vector<NormalizedRect>> expanded_face_rects;
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Source<Image> image;
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};
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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_num_layers(4);
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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_input_size_height(128);
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options->set_input_size_width(128);
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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_strides(8);
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options->add_strides(16);
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options->add_strides(16);
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options->add_strides(16);
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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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options->set_interpolated_scale_aspect_ratio(1.0);
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}
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void ConfigureTensorsToDetectionsCalculator(
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@ -80,7 +98,7 @@ void ConfigureTensorsToDetectionsCalculator(
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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_boxes(896);
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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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@ -90,10 +108,10 @@ void ConfigureTensorsToDetectionsCalculator(
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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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options->set_x_scale(128.0);
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options->set_y_scale(128.0);
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options->set_w_scale(128.0);
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options->set_h_scale(128.0);
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}
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void ConfigureNonMaxSuppressionCalculator(
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@ -107,8 +125,70 @@ void ConfigureNonMaxSuppressionCalculator(
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mediapipe::NonMaxSuppressionCalculatorOptions::WEIGHTED);
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}
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void ConfigureDetectionsToRectsCalculator(
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mediapipe::DetectionsToRectsCalculatorOptions* options) {
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// Left eye.
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options->set_rotation_vector_start_keypoint_index(0);
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// Right ete.
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options->set_rotation_vector_end_keypoint_index(1);
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options->set_rotation_vector_target_angle_degrees(0);
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}
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void ConfigureRectTransformationCalculator(
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mediapipe::RectTransformationCalculatorOptions* options) {
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options->set_scale_x(1.5);
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options->set_scale_y(1.5);
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}
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} // namespace
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// A "mediapipe.tasks.vision.face_detector.FaceDetectorGraph" performs face
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// detection.
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//
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// Inputs:
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// IMAGE - Image
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// Image to perform detection on.
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// NORM_RECT - NormalizedRect @Optional
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// Describes image rotation and region of image to perform detection on. If
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// not provided, whole image is used for face detection.
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//
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// Outputs:
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// DETECTIONS - std::vector<Detection>
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// Detected face with maximum `num_faces` specified in options.
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// FACE_RECTS - std::vector<NormalizedRect>
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// Detected face bounding boxes in normalized coordinates.
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// EXPANDED_FACE_RECTS - std::vector<NormalizedRect>
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// Expanded face bounding boxes in normalized coordinates so that bounding
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// boxes likely contain the whole face. This is usually used as RoI for face
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// landmarks detection to run on.
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// IMAGE - Image
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// The input image that the face detector 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_detector.FaceDetectorGraph"
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// input_stream: "IMAGE:image"
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// input_stream: "NORM_RECT:norm_rect"
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// output_stream: "DETECTIONS:palm_detections"
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// output_stream: "FACE_RECTS:face_rects"
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// output_stream: "EXPANDED_FACE_RECTS:expanded_face_rects"
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// output_stream: "IMAGE:image_out"
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// options {
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// [mediapipe.tasks.vision.face_detector.proto.FaceDetectorGraphOptions.ext]
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// {
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// base_options {
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// model_asset {
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// file_name: "face_detection.tflite"
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// }
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// }
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// min_detection_confidence: 0.5
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// num_faces: 2
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// }
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// }
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// }
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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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@ -116,17 +196,24 @@ class FaceDetectorGraph : public core::ModelTaskGraph {
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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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ASSIGN_OR_RETURN(auto outs,
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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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outs.face_detections >>
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graph.Out(kDetectionsTag).Cast<std::vector<Detection>>();
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outs.face_rects >>
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graph.Out(kFaceRectsTag).Cast<std::vector<NormalizedRect>>();
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outs.expanded_face_rects >>
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graph.Out(kExpandedFaceRectsTag).Cast<std::vector<NormalizedRect>>();
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outs.image >> graph.Out(kImageTag).Cast<Image>();
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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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absl::StatusOr<FaceDetectionOuts> 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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@ -149,17 +236,18 @@ class FaceDetectorGraph : public core::ModelTaskGraph {
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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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image_in >> preprocessing.In(kImageTag);
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norm_rect_in >> preprocessing.In(kNormRectTag);
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auto preprocessed_tensors = preprocessing.Out(kTensorsTag);
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auto matrix = preprocessing.Out(kMatrixTag);
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auto image_size = preprocessing.Out(kImageSizeTag);
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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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preprocessed_tensors >> inference.In(kTensorsTag);
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auto model_output_tensors =
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inference.Out("TENSORS").Cast<std::vector<Tensor>>();
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inference.Out(kTensorsTag).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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@ -174,9 +262,9 @@ class FaceDetectorGraph : public core::ModelTaskGraph {
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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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model_output_tensors >> tensors_to_detections.In(kTensorsTag);
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anchors >> tensors_to_detections.SideIn(kAnchorsTag);
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auto detections = tensors_to_detections.Out(kDetectionsTag);
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// Non maximum suppression removes redundant face detections.
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auto& non_maximum_suppression =
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@ -190,12 +278,60 @@ class FaceDetectorGraph : public core::ModelTaskGraph {
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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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nms_detections >> detection_projection.In(kDetectionsTag);
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matrix >> detection_projection.In(kProjectionMatrixTag);
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auto face_detections = detection_projection.Out(kDetectionsTag);
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return {face_detections};
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// Clip face detections to maximum number of faces;
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auto& clip_detection_vector_size =
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graph.AddNode("ClipDetectionVectorSizeCalculator");
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clip_detection_vector_size
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.GetOptions<mediapipe::ClipVectorSizeCalculatorOptions>()
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.set_max_vec_size(subgraph_options.num_faces());
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face_detections >> clip_detection_vector_size.In("");
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auto clipped_face_detections =
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clip_detection_vector_size.Out("").Cast<std::vector<Detection>>();
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// Converts results of face detection into a rectangle (normalized by image
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// size) that encloses the face and is rotated such that the line connecting
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// left eye and right eye is aligned with the X-axis of the rectangle.
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auto& detections_to_rects = graph.AddNode("DetectionsToRectsCalculator");
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ConfigureDetectionsToRectsCalculator(
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&detections_to_rects
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.GetOptions<mediapipe::DetectionsToRectsCalculatorOptions>());
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image_size >> detections_to_rects.In(kImageSizeTag);
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clipped_face_detections >> detections_to_rects.In(kDetectionsTag);
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auto face_rects = detections_to_rects.Out(kNormRectsTag)
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.Cast<std::vector<NormalizedRect>>();
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// Expands and shifts the rectangle that contains the face so that it's
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// likely to cover the entire face.
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auto& rect_transformation = graph.AddNode("RectTransformationCalculator");
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ConfigureRectTransformationCalculator(
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&rect_transformation
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.GetOptions<mediapipe::RectTransformationCalculatorOptions>());
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face_rects >> rect_transformation.In(kNormRectsTag);
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image_size >> rect_transformation.In(kImageSizeTag);
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auto expanded_face_rects =
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rect_transformation.Out("").Cast<std::vector<NormalizedRect>>();
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// Calculator to convert relative detection bounding boxes to pixel
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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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auto face_pixel_detections =
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detection_transformation.Out(kPixelDetectionsTag)
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.Cast<std::vector<Detection>>();
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return FaceDetectionOuts{
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/* face_detections= */ face_pixel_detections,
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/* face_rects= */ face_rects,
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/* expanded_face_rects= */ expanded_face_rects,
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/* image= */ preprocessing.Out("IMAGE").Cast<Image>()};
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}
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};
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@ -74,6 +74,8 @@ 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 kShortRangeBlazeFaceModel[] =
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"face_detection_short_range.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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@ -161,17 +163,11 @@ TEST_P(FaceDetectorGraphTest, Succeed) {
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INSTANTIATE_TEST_SUITE_P(
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FaceDetectorGraphTest, FaceDetectorGraphTest,
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Values(TestParams{.test_name = "FullRange",
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.face_detection_model_name = kFullRangeBlazeFaceModel,
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Values(TestParams{.test_name = "ShortRange",
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.face_detection_model_name = kShortRangeBlazeFaceModel,
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.test_image_name = kPortraitImage,
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.expected_result = {GetExpectedFaceDetectionResult(
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kPortraitExpectedDetection)}},
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TestParams{
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.test_name = "FullRangeSparse",
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.face_detection_model_name = kFullRangeSparseBlazeFaceModel,
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.test_image_name = kPortraitImage,
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.expected_result = {GetExpectedFaceDetectionResult(
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kPortraitExpectedDetection)}}),
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kPortraitExpectedDetection)}}),
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[](const TestParamInfo<FaceDetectorGraphTest::ParamType>& info) {
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return info.param.test_name;
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});
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@ -39,4 +39,7 @@ message FaceDetectorGraphOptions {
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// IoU threshold ([0,0, 1.0]) for non-maximu-suppression to be considered
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// duplicate detetions.
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optional float min_suppression_threshold = 3 [default = 0.5];
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// Maximum number of faces to detect in the image.
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optional int32 num_faces = 4 [default = 1];
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}
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2
mediapipe/tasks/testdata/vision/BUILD
vendored
2
mediapipe/tasks/testdata/vision/BUILD
vendored
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@ -39,6 +39,7 @@ mediapipe_files(srcs = [
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"deeplabv3.tflite",
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"face_detection_full_range.tflite",
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"face_detection_full_range_sparse.tflite",
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"face_detection_short_range.tflite",
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"face_landmark.tflite",
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"fist.jpg",
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"fist.png",
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@ -137,6 +138,7 @@ filegroup(
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"deeplabv3.tflite",
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"face_detection_full_range.tflite",
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"face_detection_full_range_sparse.tflite",
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"face_detection_short_range.tflite",
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"face_landmark.tflite",
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"hand_landmark_full.tflite",
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"hand_landmark_lite.tflite",
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@ -1,12 +1,12 @@
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# proto-file: mediapipe/framework/formats/detection.proto
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# proto-message: Detection
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location_data {
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format: RELATIVE_BOUNDING_BOX
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relative_bounding_box {
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xmin: 0.35494408
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ymin: 0.1059662
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width: 0.28768203
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height: 0.23037356
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format: BOUNDING_BOX
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bounding_box {
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xmin: 283
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ymin: 115
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width: 234
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height: 234
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}
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relative_keypoints {
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x: 0.44416338
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@ -25,7 +25,7 @@ location_data {
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y: 0.2719954
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}
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relative_keypoints {
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x: 0.37245658
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x: 0.36063305
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y: 0.20143759
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}
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relative_keypoints {
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12
third_party/external_files.bzl
vendored
12
third_party/external_files.bzl
vendored
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@ -252,8 +252,8 @@ def external_files():
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http_file(
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name = "com_google_mediapipe_face_detection_short_range_tflite",
|
||||
sha256 = "3bc182eb9f33925d9e58b5c8d59308a760f4adea8f282370e428c51212c26633",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/face_detection_short_range.tflite?generation=1661875748538815"],
|
||||
sha256 = "bbff11cebd1eb27a1e004cae0b0e63ec8c551cbf34a4451148b4908b8db3eca8",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/face_detection_short_range.tflite?generation=1677044301978921"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
|
|
@ -264,8 +264,8 @@ def external_files():
|
|||
|
||||
http_file(
|
||||
name = "com_google_mediapipe_face_landmark_with_attention_tflite",
|
||||
sha256 = "883b7411747bac657c30c462d305d312e9dec6adbf8b85e2f5d8d722fca9455d",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/face_landmark_with_attention.tflite?generation=1661875751615925"],
|
||||
sha256 = "e06a804e0144f9929eda782122916b35d60c697c3c9344013ca2bbe76a6ce2b4",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/face_landmark_with_attention.tflite?generation=1676415468821650"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
|
|
@ -714,8 +714,8 @@ def external_files():
|
|||
|
||||
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"],
|
||||
sha256 = "ace755f0fd0ba3b2d75e4f8bb1b08d2f65975fd5570898004540dfef735c1c3d",
|
||||
urls = ["https://storage.googleapis.com/mediapipe-assets/portrait_expected_detection.pbtxt?generation=1677044311581104"],
|
||||
)
|
||||
|
||||
http_file(
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user