# MediaPipe graph to detect faces. (CPU input, and inference is executed on
# CPU.)
#
# 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.
#
# EXAMPLE:
#   node {
#     calculator: "FaceDetectionFullRangeCpu"
#     input_stream: "IMAGE:image"
#     output_stream: "DETECTIONS:face_detections"
#   }

type: "FaceDetectionFullRangeCpu"

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

# Converts the input CPU image (ImageFrame) to the multi-backend image type
# (Image).
node: {
  calculator: "ToImageCalculator"
  input_stream: "IMAGE_CPU:image"
  output_stream: "IMAGE:multi_backend_image"
}

# Transforms the input image into a 192x192 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:multi_backend_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
    }
  }
}

# Runs a TensorFlow Lite model on CPU that takes an image tensor and outputs a
# vector of tensors representing, for instance, detection boxes/keypoints and
# scores.
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 {
        xnnpack {}
      }
    }
  }
}

# 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"
}