# MediaPipe graph to calculate face region of interest (ROI) from landmarks
# detected by "FaceLandmarkCpu" or "FaceLandmarkGpu".
#
# NOTE: this graph is subject to change and should not be used directly.

type: "FaceLandmarkLandmarksToRoi"

# Normalized landmarks. (NormalizedLandmarkList)
input_stream: "LANDMARKS:landmarks"
# Frame size (width & height). (std::pair<int, int>)
input_stream: "IMAGE_SIZE:image_size"
# ROI according to landmarks. (NormalizedRect)
output_stream: "ROI:roi"

# Converts face landmarks to a detection that tightly encloses all landmarks.
node {
  calculator: "LandmarksToDetectionCalculator"
  input_stream: "NORM_LANDMARKS:landmarks"
  output_stream: "DETECTION:face_detection"
}

# Converts the face detection into a rectangle (normalized by image size)
# that encloses the face and is rotated such that the line connecting left side
# of the left eye and right side of the right eye is aligned with the X-axis of
# the rectangle.
node {
  calculator: "DetectionsToRectsCalculator"
  input_stream: "DETECTION:face_detection"
  input_stream: "IMAGE_SIZE:image_size"
  output_stream: "NORM_RECT:face_rect_from_landmarks"
  options: {
    [mediapipe.DetectionsToRectsCalculatorOptions.ext] {
      rotation_vector_start_keypoint_index: 33  # Left side of left eye.
      rotation_vector_end_keypoint_index: 263  # Right side of right eye.
      rotation_vector_target_angle_degrees: 0
    }
  }
}

# Expands the face rectangle so that in the next video image it's likely to
# still contain the face even with some motion.
node {
  calculator: "RectTransformationCalculator"
  input_stream: "NORM_RECT:face_rect_from_landmarks"
  input_stream: "IMAGE_SIZE:image_size"
  output_stream: "roi"
  options: {
    [mediapipe.RectTransformationCalculatorOptions.ext] {
      scale_x: 1.5
      scale_y: 1.5
      square_long: true
    }
  }
}