# MediaPipe graph to perform selfie segmentation.

type: "SelfieSegmentationGpuImage"

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

# The throttled input image. (Image)
output_stream: "IMAGE:throttled_image"

# An integer 0 or 1. Use 0 to select a general-purpose model (operating on a
# 256x256 tensor), and 1 to select a model (operating on a 256x144 tensor) more
# optimized for landscape images. If unspecified, functions as set to 0. (int)
input_side_packet: "MODEL_SELECTION:model_selection"

# Segmentation mask. (Image)
output_stream: "SEGMENTATION_MASK:segmentation_mask"

node {
  calculator: "FlowLimiterCalculator"
  input_stream: "image"
  input_stream: "FINISHED:segmentation_mask"
  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
    }
  }
}

# Converts Image to ImageFrame for SelfieSegmentationGpu to consume.
node {
  calculator: "FromImageCalculator"
  input_stream: "IMAGE:throttled_image"
  output_stream: "IMAGE_GPU:raw_gpu_buffer"
  output_stream: "SOURCE_ON_GPU:is_gpu_image"
}

# TODO: Remove the extra flipping once adopting MlImage.
# If the source images are on gpu, flip the data vertically before sending them
# into SelfieSegmentationGpu. This maybe needed because OpenGL represents images
# assuming the image origin is at the bottom-left corner, whereas MediaPipe in
# general assumes the image origin is at the top-left corner.
node: {
  calculator: "ImageTransformationCalculator"
  input_stream: "IMAGE_GPU:raw_gpu_buffer"
  input_stream: "FLIP_VERTICALLY:is_gpu_image"
  output_stream: "IMAGE_GPU:gpu_buffer"
}

node {
  calculator: "SelfieSegmentationGpu"
  input_side_packet: "MODEL_SELECTION:model_selection"
  input_stream: "IMAGE:gpu_buffer"
  output_stream: "SEGMENTATION_MASK:segmentation_mask_gpu_buffer"
}

node {
  calculator: "ToImageCalculator"
  input_stream: "IMAGE_GPU:segmentation_mask_gpu_buffer"
  output_stream: "IMAGE:segmentation_mask"
}