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https://gitlab.freedesktop.org/gstreamer/gstreamer.git
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f71eb29497
This MR provides a transform element that leverage ONNX runtime to run AI inference on a broad range of neural network toolkits, running on either CPU or GPU. ONNX supports 16 different providers at the moment, so with ONNX we immediately get support for Nvidia, AMD, Xilinx and many others. For the first release, this plugin adds a gstonnxobjectdetector element to detect objects in video frames. Meta data generated by the model is attached to the video buffer as a custom GstObjectDetectorMeta meta. Part-of: <https://gitlab.freedesktop.org/gstreamer/gst-plugins-bad/-/merge_requests/1997>
117 lines
4.1 KiB
C++
117 lines
4.1 KiB
C++
/*
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* GStreamer gstreamer-onnxclient
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* Copyright (C) 2021 Collabora Ltd
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*
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* gstonnxclient.h
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*
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* This library is free software; you can redistribute it and/or
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* modify it under the terms of the GNU Library General Public
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* License as published by the Free Software Foundation; either
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* version 2 of the License, or (at your option) any later version.
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*
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* This library is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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* Library General Public License for more details.
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*
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* You should have received a copy of the GNU Library General Public
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* License along with this library; if not, write to the
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* Free Software Foundation, Inc., 51 Franklin St, Fifth Floor,
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* Boston, MA 02110-1301, USA.
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*/
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#ifndef __GST_ONNX_CLIENT_H__
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#define __GST_ONNX_CLIENT_H__
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#include <gst/gst.h>
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#include <onnxruntime_cxx_api.h>
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#include <gst/video/video.h>
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#include "gstonnxelement.h"
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#include <string>
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#include <vector>
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namespace GstOnnxNamespace {
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enum GstMlOutputNodeFunction {
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GST_ML_OUTPUT_NODE_FUNCTION_DETECTION,
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GST_ML_OUTPUT_NODE_FUNCTION_BOUNDING_BOX,
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GST_ML_OUTPUT_NODE_FUNCTION_SCORE,
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GST_ML_OUTPUT_NODE_FUNCTION_CLASS,
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GST_ML_OUTPUT_NODE_NUMBER_OF,
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};
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const gint GST_ML_NODE_INDEX_DISABLED = -1;
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struct GstMlOutputNodeInfo {
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GstMlOutputNodeInfo(void);
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gint index;
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ONNXTensorElementDataType type;
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};
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struct GstMlBoundingBox {
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GstMlBoundingBox(std::string lbl,
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float score,
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float _x0,
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float _y0,
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float _width,
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float _height):label(lbl),
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score(score), x0(_x0), y0(_y0), width(_width), height(_height) {
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}
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GstMlBoundingBox():GstMlBoundingBox("", 0.0f, 0.0f, 0.0f, 0.0f, 0.0f) {
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}
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std::string label;
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float score;
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float x0;
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float y0;
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float width;
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float height;
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};
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class GstOnnxClient {
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public:
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GstOnnxClient(void);
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~GstOnnxClient(void);
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bool createSession(std::string modelFile, GstOnnxOptimizationLevel optim,
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GstOnnxExecutionProvider provider);
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bool hasSession(void);
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void setInputImageFormat(GstMlModelInputImageFormat format);
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GstMlModelInputImageFormat getInputImageFormat(void);
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void setOutputNodeIndex(GstMlOutputNodeFunction nodeType, gint index);
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gint getOutputNodeIndex(GstMlOutputNodeFunction nodeType);
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void setOutputNodeType(GstMlOutputNodeFunction nodeType,
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ONNXTensorElementDataType type);
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ONNXTensorElementDataType getOutputNodeType(GstMlOutputNodeFunction type);
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std::string getOutputNodeName(GstMlOutputNodeFunction nodeType);
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std::vector < GstMlBoundingBox > run(uint8_t * img_data,
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GstVideoMeta * vmeta,
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std::string labelPath,
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float scoreThreshold);
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std::vector < GstMlBoundingBox > &getBoundingBoxes(void);
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std::vector < const char *>getOutputNodeNames(void);
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bool isFixedInputImageSize(void);
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int32_t getWidth(void);
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int32_t getHeight(void);
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private:
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void parseDimensions(GstVideoMeta * vmeta);
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template < typename T > std::vector < GstMlBoundingBox >
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doRun(uint8_t * img_data, GstVideoMeta * vmeta, std::string labelPath,
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float scoreThreshold);
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std::vector < std::string > ReadLabels(const std::string & labelsFile);
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Ort::Env & getEnv(void);
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Ort::Session * session;
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int32_t width;
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int32_t height;
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int32_t channels;
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uint8_t *dest;
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GstOnnxExecutionProvider m_provider;
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std::vector < Ort::Value > modelOutput;
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std::vector < std::string > labels;
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// !! indexed by function
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GstMlOutputNodeInfo outputNodeInfo[GST_ML_OUTPUT_NODE_NUMBER_OF];
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// !! indexed by array index
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size_t outputNodeIndexToFunction[GST_ML_OUTPUT_NODE_NUMBER_OF];
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std::vector < const char *>outputNames;
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GstMlModelInputImageFormat inputImageFormat;
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bool fixedInputImageSize;
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};
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}
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#endif /* __GST_ONNX_CLIENT_H__ */
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