# 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_cpu.

# CPU image. (ImageFrame)
input_stream: "input_video"

# CPU image. (ImageFrame)
output_stream: "output_video"

# 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"
}