mediapipe-rs/mediapipe/graphs/hand_tracking/hand_tracking_desktop.pbtxt

69 lines
2.2 KiB
Plaintext
Raw Normal View History

2022-03-01 13:04:01 +01:00
# MediaPipe graph that performs hands tracking on desktop with TensorFlow Lite
# on CPU.
# Used in the example in
# mediapipe/examples/desktop/hand_tracking:hand_tracking_tflite.
# max_queue_size limits the number of packets enqueued on any input stream
# by throttling inputs to the graph. This makes the graph only process one
# frame per time.
max_queue_size: 1
# Decodes an input video file into images and a video header.
node {
calculator: "OpenCvVideoDecoderCalculator"
input_side_packet: "INPUT_FILE_PATH:input_video_path"
output_stream: "VIDEO:input_video"
output_stream: "VIDEO_PRESTREAM:input_video_header"
}
# Generates side packet cotaining max number of hands to detect/track.
node {
calculator: "ConstantSidePacketCalculator"
output_side_packet: "PACKET:num_hands"
node_options: {
[type.googleapis.com/mediapipe.ConstantSidePacketCalculatorOptions]: {
packet { int_value: 2 }
}
}
}
# Detects/tracks hand landmarks.
node {
calculator: "HandLandmarkTrackingCpu"
input_stream: "IMAGE:input_video"
input_side_packet: "NUM_HANDS:num_hands"
output_stream: "LANDMARKS:landmarks"
output_stream: "HANDEDNESS:handedness"
output_stream: "PALM_DETECTIONS:multi_palm_detections"
output_stream: "HAND_ROIS_FROM_LANDMARKS:multi_hand_rects"
output_stream: "HAND_ROIS_FROM_PALM_DETECTIONS:multi_palm_rects"
}
# Subgraph that renders annotations and overlays them on top of the input
# images (see hand_renderer_cpu.pbtxt).
node {
calculator: "HandRendererSubgraph"
input_stream: "IMAGE:input_video"
input_stream: "DETECTIONS:multi_palm_detections"
input_stream: "LANDMARKS:landmarks"
input_stream: "HANDEDNESS:handedness"
input_stream: "NORM_RECTS:0:multi_palm_rects"
input_stream: "NORM_RECTS:1:multi_hand_rects"
output_stream: "IMAGE:output_video"
}
# Encodes the annotated images into a video file, adopting properties specified
# in the input video header, e.g., video framerate.
node {
calculator: "OpenCvVideoEncoderCalculator"
input_stream: "VIDEO:output_video"
input_stream: "VIDEO_PRESTREAM:input_video_header"
input_side_packet: "OUTPUT_FILE_PATH:output_video_path"
node_options: {
[type.googleapis.com/mediapipe.OpenCvVideoEncoderCalculatorOptions]: {
codec: "avc1"
video_format: "mp4"
}
}
}