88 lines
3.2 KiB
Plaintext
88 lines
3.2 KiB
Plaintext
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# MediaPipe graph to extract geometry from face detection for multiple faces.
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#
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# It is required that "geometry_pipeline_metadata_detection.binarypb" is
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# available at
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# "mediapipe/modules/face_geometry/data/geometry_pipeline_metadata_detection.binarypb"
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# path during execution.
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#
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# EXAMPLE:
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# node {
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# calculator: "FaceGeometryFromDetection"
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# input_stream: "IMAGE_SIZE:image_size"
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# input_stream: "MULTI_FACE_DETECTION:multi_face_detection"
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# input_side_packet: "ENVIRONMENT:environment"
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# output_stream: "MULTI_FACE_GEOMETRY:multi_face_geometry"
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# }
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type: "FaceGeometryFromDetection"
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# The size of the input frame. The first element of the pair is the frame width;
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# the other one is the frame height.
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#
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# The face landmarks should have been detected on a frame with the same
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# ratio. If used as-is, the resulting face geometry visualization should be
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# happening on a frame with the same ratio as well.
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#
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# (std::pair<int, int>)
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input_stream: "IMAGE_SIZE:image_size"
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# Collection of detected/predicted faces, each represented as a detection.
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# (std::vector<DETECTION>)
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input_stream: "MULTI_FACE_DETECTION:multi_face_detection"
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# Environment that describes the current virtual scene.
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# (face_geometry::Environment)
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input_side_packet: "ENVIRONMENT:environment"
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# A list of geometry data for each detected face.
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# (std::vector<face_geometry::FaceGeometry>)
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#
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# NOTE: the triangular topology of the face meshes is only useful when derived
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# from the 468 face landmarks, not from the 6 face detection landmarks
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# (keypoints). The former don't cover the entire face and this mesh is
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# defined here only to comply with the API. It should be considered as
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# a placeholder and/or for debugging purposes.
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#
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# Use the face geometry derived from the face detection landmarks
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# (keypoints) for the face pose transformation matrix, not the mesh.
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output_stream: "MULTI_FACE_GEOMETRY:multi_face_geometry"
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# Begin iterating over a vector of the face detections.
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node {
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calculator: "BeginLoopDetectionCalculator"
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input_stream: "ITERABLE:multi_face_detection"
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output_stream: "ITEM:face_detection"
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output_stream: "BATCH_END:detection_timestamp"
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}
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# Extracts face detection keypoints as a normalized landmarks.
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node {
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calculator: "DetectionToLandmarksCalculator"
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input_stream: "DETECTION:face_detection"
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output_stream: "LANDMARKS:face_landmarks"
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}
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# End iterating over a vector of the face detections and receive a vector of
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# face landmark lists as a result.
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node {
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calculator: "EndLoopNormalizedLandmarkListVectorCalculator"
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input_stream: "ITEM:face_landmarks"
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input_stream: "BATCH_END:detection_timestamp"
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output_stream: "ITERABLE:multi_face_landmarks"
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}
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# Extracts face geometry for multiple faces from a vector of face detection
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# landmark lists.
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node {
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calculator: "FaceGeometryPipelineCalculator"
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input_side_packet: "ENVIRONMENT:environment"
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input_stream: "IMAGE_SIZE:image_size"
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input_stream: "MULTI_FACE_LANDMARKS:multi_face_landmarks"
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output_stream: "MULTI_FACE_GEOMETRY:multi_face_geometry"
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options: {
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[mediapipe.FaceGeometryPipelineCalculatorOptions.ext] {
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metadata_path: "mediapipe/modules/face_geometry/data/geometry_pipeline_metadata_detection.binarypb"
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}
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}
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}
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