mediapipe-rs/mediapipe/modules/face_detection/face_detection_full_range_image.pbtxt
2022-06-11 12:25:48 -07:00

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# 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"
}