# MediaPipe graph to detect faces. (GPU/CPU input, and inference is executed on
# GPU.)
#
# It is required that "face_detection_full_range_sparse.tflite" is available at
# "mediapipe/modules/face_detection/face_detection_full_range_sparse.tflite"
# path during execution.

type: "FaceDetectionFullRangeImage"

# Image. (Image)
input_stream: "IMAGE:image"

# The throttled input image. (Image)
output_stream: "IMAGE:throttled_image"
# Detected faces. (std::vector<Detection>)
# NOTE: there will not be an output packet in the DETECTIONS stream for this
# particular timestamp if none of faces detected. However, the MediaPipe
# framework will internally inform the downstream calculators of the absence of
# this packet so that they don't wait for it unnecessarily.
output_stream: "DETECTIONS:detections"

node {
  calculator: "FlowLimiterCalculator"
  input_stream: "image"
  input_stream: "FINISHED:detections"
  input_stream_info: {
    tag_index: "FINISHED"
    back_edge: true
  }
  output_stream: "throttled_image"
  options: {
    [mediapipe.FlowLimiterCalculatorOptions.ext] {
      max_in_flight: 1
      max_in_queue: 1
    }
  }
}

# Transforms the input image into a 128x128 tensor while keeping the aspect
# ratio (what is expected by the corresponding face detection model), resulting
# in potential letterboxing in the transformed image.
node: {
  calculator: "ImageToTensorCalculator"
  input_stream: "IMAGE:throttled_image"
  output_stream: "TENSORS:input_tensors"
  output_stream: "MATRIX:transform_matrix"
  options: {
    [mediapipe.ImageToTensorCalculatorOptions.ext] {
      output_tensor_width: 192
      output_tensor_height: 192
      keep_aspect_ratio: true
      output_tensor_float_range {
        min: -1.0
        max: 1.0
      }
      border_mode: BORDER_ZERO
      gpu_origin: CONVENTIONAL
    }
  }
}

# Runs a TensorFlow Lite model on GPU that takes an image tensor and outputs a
# vector of tensors representing, for instance, detection boxes/keypoints and
# scores.
# TODO: Use GraphOptions to modify the delegate field to be
# `delegate { xnnpack {} }` for the CPU only use cases.
node {
  calculator: "InferenceCalculator"
  input_stream: "TENSORS:input_tensors"
  output_stream: "TENSORS:detection_tensors"
  options: {
    [mediapipe.InferenceCalculatorOptions.ext] {
      model_path: "mediapipe/modules/face_detection/face_detection_full_range_sparse.tflite"
      #
      delegate: { gpu { use_advanced_gpu_api: true } }
    }
  }
}

# Performs tensor post processing to generate face detections.
node {
  calculator: "FaceDetectionFullRangeCommon"
  input_stream: "TENSORS:detection_tensors"
  input_stream: "MATRIX:transform_matrix"
  output_stream: "DETECTIONS:detections"
}