93 lines
2.5 KiB
Plaintext
93 lines
2.5 KiB
Plaintext
# MediaPipe graph that build feature descriptors index for specific target.
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# max_queue_size limits the number of packets enqueued on any input stream
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# by throttling inputs to the graph. This makes the graph only process one
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# frame per time.
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max_queue_size: 1
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# Decodes an input video file into images and a video header.
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node {
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calculator: "LocalFilePatternContentsCalculator"
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input_side_packet: "FILE_DIRECTORY:file_directory"
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input_side_packet: "FILE_SUFFIX:file_suffix"
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output_stream: "CONTENTS:encoded_image"
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}
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node {
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calculator: "OpenCvEncodedImageToImageFrameCalculator"
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input_stream: "encoded_image"
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output_stream: "image_frame"
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}
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node: {
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calculator: "ImageTransformationCalculator"
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input_stream: "IMAGE:image_frame"
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output_stream: "IMAGE:scaled_image_frame"
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node_options: {
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[type.googleapis.com/mediapipe.ImageTransformationCalculatorOptions] {
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output_width: 320
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output_height: 320
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scale_mode: FILL_AND_CROP
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}
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}
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}
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node {
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calculator: "ImagePropertiesCalculator"
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input_stream: "IMAGE:scaled_image_frame"
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output_stream: "SIZE:input_video_size"
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}
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node {
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calculator: "FeatureDetectorCalculator"
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input_stream: "IMAGE:scaled_image_frame"
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output_stream: "FEATURES:features"
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output_stream: "LANDMARKS:landmarks"
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output_stream: "PATCHES:patches"
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node_options: {
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[type.googleapis.com/mediapipe.FeatureDetectorCalculatorOptions] {
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max_features: 400
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}
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}
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}
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# input tensors: 200*32*32*1 float
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# output tensors: 200*40 float, only first keypoint.size()*40 is knift features,
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# rest is padded by zero.
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node {
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calculator: "TfLiteInferenceCalculator"
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input_stream: "TENSORS:patches"
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output_stream: "TENSORS:knift_feature_tensors"
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input_stream_handler {
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input_stream_handler: "DefaultInputStreamHandler"
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}
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node_options: {
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[type.googleapis.com/mediapipe.TfLiteInferenceCalculatorOptions] {
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model_path: "mediapipe/models/knift_float_400.tflite"
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}
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}
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}
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node {
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calculator: "TfLiteTensorsToFloatsCalculator"
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input_stream: "TENSORS:knift_feature_tensors"
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output_stream: "FLOATS:knift_feature_floats"
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}
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node {
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calculator: "BoxDetectorCalculator"
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input_side_packet: "OUTPUT_INDEX_FILENAME:output_index_filename"
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input_stream: "FEATURES:features"
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input_stream: "IMAGE_SIZE:input_video_size"
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input_stream: "DESCRIPTORS:knift_feature_floats"
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node_options: {
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[type.googleapis.com/mediapipe.BoxDetectorCalculatorOptions] {
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detector_options {
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index_type: OPENCV_BF
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detect_every_n_frame: 1
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}
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}
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}
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}
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