60 lines
2.1 KiB
Plaintext
60 lines
2.1 KiB
Plaintext
# MediaPipe graph that performs hand detection 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/handdetectiongpu and
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# mediapipe/examples/ios/handdetectiongpu.
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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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# Throttles the images flowing downstream for flow control. It passes through
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# the very first incoming image unaltered, and waits for PalmDetectionGpu
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# downstream in the graph to finish its tasks before it passes through another
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# image. All images that come in while waiting are dropped, limiting the number
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# of in-flight images in PalmDetectionGpu to 1. This prevents the nodes in
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# PalmDetectionGpu from queuing up incoming images and data excessively, which
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# leads to increased latency and memory usage, unwanted in real-time mobile
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# applications. It also eliminates unnecessarily computation, e.g., the output
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# produced by a node in the subgraph may get dropped downstream if the
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# subsequent nodes are still busy processing previous inputs.
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node {
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calculator: "FlowLimiterCalculator"
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input_stream: "input_video"
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input_stream: "FINISHED:output_video"
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input_stream_info: {
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tag_index: "FINISHED"
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back_edge: true
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}
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output_stream: "throttled_input_video"
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}
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# Detects palms.
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node {
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calculator: "PalmDetectionGpu"
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input_stream: "IMAGE:throttled_input_video"
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output_stream: "DETECTIONS:palm_detections"
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}
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# Converts detections to drawing primitives for annotation overlay.
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node {
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calculator: "DetectionsToRenderDataCalculator"
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input_stream: "DETECTIONS:palm_detections"
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output_stream: "RENDER_DATA:detection_render_data"
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node_options: {
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[type.googleapis.com/mediapipe.DetectionsToRenderDataCalculatorOptions] {
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thickness: 4.0
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color { r: 0 g: 255 b: 0 }
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}
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}
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}
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# Draws annotations and overlays them on top of the input images.
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node {
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calculator: "AnnotationOverlayCalculator"
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input_stream: "IMAGE_GPU:throttled_input_video"
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input_stream: "detection_render_data"
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output_stream: "IMAGE_GPU:output_video"
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}
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