81 lines
2.5 KiB
Plaintext
81 lines
2.5 KiB
Plaintext
# MediaPipe graph to detect faces. (CPU input, and inference is executed on
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# CPU.)
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#
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# It is required that "face_detection_full_range_sparse.tflite" is available at
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# "mediapipe/modules/face_detection/face_detection_full_range_sparse.tflite"
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# path during execution.
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#
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# EXAMPLE:
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# node {
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# calculator: "FaceDetectionFullRangeCpu"
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# input_stream: "IMAGE:image"
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# output_stream: "DETECTIONS:face_detections"
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# }
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type: "FaceDetectionFullRangeCpu"
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# CPU image. (ImageFrame)
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input_stream: "IMAGE:image"
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# Detected faces. (std::vector<Detection>)
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# NOTE: there will not be an output packet in the DETECTIONS stream for this
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# particular timestamp if none of faces detected. However, the MediaPipe
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# framework will internally inform the downstream calculators of the absence of
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# this packet so that they don't wait for it unnecessarily.
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output_stream: "DETECTIONS:detections"
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# Converts the input CPU image (ImageFrame) to the multi-backend image type
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# (Image).
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node: {
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calculator: "ToImageCalculator"
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input_stream: "IMAGE_CPU:image"
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output_stream: "IMAGE:multi_backend_image"
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}
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# Transforms the input image into a 192x192 tensor while keeping the aspect
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# ratio (what is expected by the corresponding face detection model), resulting
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# in potential letterboxing in the transformed image.
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node: {
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calculator: "ImageToTensorCalculator"
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input_stream: "IMAGE:multi_backend_image"
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output_stream: "TENSORS:input_tensors"
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output_stream: "MATRIX:transform_matrix"
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options: {
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[mediapipe.ImageToTensorCalculatorOptions.ext] {
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output_tensor_width: 192
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output_tensor_height: 192
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keep_aspect_ratio: true
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output_tensor_float_range {
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min: -1.0
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max: 1.0
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}
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border_mode: BORDER_ZERO
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}
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}
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}
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# Runs a TensorFlow Lite model on CPU that takes an image tensor and outputs a
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# vector of tensors representing, for instance, detection boxes/keypoints and
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# scores.
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node {
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calculator: "InferenceCalculator"
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input_stream: "TENSORS:input_tensors"
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output_stream: "TENSORS:detection_tensors"
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options: {
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[mediapipe.InferenceCalculatorOptions.ext] {
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model_path: "mediapipe/modules/face_detection/face_detection_full_range_sparse.tflite"
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delegate {
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xnnpack {}
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}
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}
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}
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}
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# Performs tensor post processing to generate face detections.
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node {
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calculator: "FaceDetectionFullRangeCommon"
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input_stream: "TENSORS:detection_tensors"
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input_stream: "MATRIX:transform_matrix"
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output_stream: "DETECTIONS:detections"
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}
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