46 lines
1.4 KiB
Plaintext
46 lines
1.4 KiB
Plaintext
# MediaPipe graph that performs object detection and tracking with TensorFlow
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# Lite on CPU.
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# Used in the examples in
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# mediapipie/examples/desktop/object_tracking/
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# Images on CPU coming into and out of the graph.
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input_stream: "input_video"
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output_stream: "output_video"
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# Resamples the images by specific frame rate. This calculator is used to
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# control the frequecy of subsequent calculators/subgraphs, e.g. less power
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# consumption for expensive process.
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node {
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calculator: "PacketResamplerCalculator"
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input_stream: "DATA:input_video"
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output_stream: "DATA:throttled_input_video"
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node_options: {
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[type.googleapis.com/mediapipe.PacketResamplerCalculatorOptions] {
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frame_rate: 3
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}
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}
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}
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# Subgraph that detections objects (see object_detection_cpu.pbtxt).
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node {
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calculator: "ObjectDetectionSubgraphCpu"
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input_stream: "IMAGE:throttled_input_video"
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output_stream: "DETECTIONS:output_detections"
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}
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# Subgraph that tracks objects (see object_tracking_cpu.pbtxt).
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node {
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calculator: "ObjectTrackingSubgraphCpu"
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input_stream: "VIDEO:input_video"
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input_stream: "DETECTIONS:output_detections"
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output_stream: "DETECTIONS:tracked_detections"
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}
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# Subgraph that renders annotations and overlays them on top of input images (see renderer_cpu.pbtxt).
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node {
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calculator: "RendererSubgraphCpu"
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input_stream: "IMAGE:input_video"
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input_stream: "DETECTIONS:tracked_detections"
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output_stream: "IMAGE:output_video"
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}
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