47 lines
1.4 KiB
Plaintext
47 lines
1.4 KiB
Plaintext
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# MediaPipe graph that performs hands tracking on desktop with TensorFlow
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# Lite on CPU.
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# Used in the example in
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# mediapipe/examples/desktop/hand_tracking:hand_tracking_cpu.
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# CPU image. (ImageFrame)
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input_stream: "input_video"
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# CPU image. (ImageFrame)
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output_stream: "output_video"
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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: "HandLandmarkTrackingCpu"
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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:landmarks"
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output_stream: "HANDEDNESS:handedness"
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output_stream: "PALM_DETECTIONS:multi_palm_detections"
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output_stream: "HAND_ROIS_FROM_LANDMARKS:multi_hand_rects"
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output_stream: "HAND_ROIS_FROM_PALM_DETECTIONS:multi_palm_rects"
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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_cpu.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:multi_palm_detections"
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input_stream: "LANDMARKS:landmarks"
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input_stream: "HANDEDNESS:handedness"
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input_stream: "NORM_RECTS:0:multi_palm_rects"
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input_stream: "NORM_RECTS:1:multi_hand_rects"
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output_stream: "IMAGE:output_video"
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}
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