49 lines
1.6 KiB
Plaintext
49 lines
1.6 KiB
Plaintext
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# MediaPipe graph that performs multi-hand tracking with TensorFlow Lite on GPU.
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# Used in the examples in
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# mediapipe/examples/android/src/java/com/mediapipe/apps/handtrackinggpu.
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# GPU image. (GpuBuffer)
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input_stream: "input_video"
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# GPU image. (GpuBuffer)
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output_stream: "output_video"
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# Collection of detected/predicted hands, each represented as a list of
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# landmarks. (std::vector<NormalizedLandmarkList>)
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output_stream: "hand_landmarks"
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# Generates side packet cotaining max number of hands to detect/track.
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node {
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calculator: "ConstantSidePacketCalculator"
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output_side_packet: "PACKET:num_hands"
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node_options: {
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[type.googleapis.com/mediapipe.ConstantSidePacketCalculatorOptions]: {
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packet { int_value: 2 }
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}
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}
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}
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# Detects/tracks hand landmarks.
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node {
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calculator: "HandLandmarkTrackingGpu"
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input_stream: "IMAGE:input_video"
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input_side_packet: "NUM_HANDS:num_hands"
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output_stream: "LANDMARKS:hand_landmarks"
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output_stream: "HANDEDNESS:handedness"
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output_stream: "PALM_DETECTIONS:palm_detections"
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output_stream: "HAND_ROIS_FROM_LANDMARKS:hand_rects_from_landmarks"
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output_stream: "HAND_ROIS_FROM_PALM_DETECTIONS:hand_rects_from_palm_detections"
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}
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# Subgraph that renders annotations and overlays them on top of the input
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# images (see hand_renderer_gpu.pbtxt).
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node {
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calculator: "HandRendererSubgraph"
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input_stream: "IMAGE:input_video"
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input_stream: "DETECTIONS:palm_detections"
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input_stream: "LANDMARKS:hand_landmarks"
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input_stream: "HANDEDNESS:handedness"
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input_stream: "NORM_RECTS:0:hand_rects_from_palm_detections"
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input_stream: "NORM_RECTS:1:hand_rects_from_landmarks"
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output_stream: "IMAGE:output_video"
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}
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