mirror of
https://gitlab.freedesktop.org/gstreamer/gstreamer.git
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b1ac114ca5
This should enable zero-copy when the model has the right type Part-of: <https://gitlab.freedesktop.org/gstreamer/gstreamer/-/merge_requests/5885>
102 lines
3.4 KiB
C++
102 lines
3.4 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 "gstml.h"
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#include "tensor/gsttensormeta.h"
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GST_DEBUG_CATEGORY_EXTERN (onnx_inference_debug);
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typedef enum
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{
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GST_ONNX_OPTIMIZATION_LEVEL_DISABLE_ALL,
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GST_ONNX_OPTIMIZATION_LEVEL_ENABLE_BASIC,
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GST_ONNX_OPTIMIZATION_LEVEL_ENABLE_EXTENDED,
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GST_ONNX_OPTIMIZATION_LEVEL_ENABLE_ALL,
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} GstOnnxOptimizationLevel;
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typedef enum
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{
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GST_ONNX_EXECUTION_PROVIDER_CPU,
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GST_ONNX_EXECUTION_PROVIDER_CUDA,
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} GstOnnxExecutionProvider;
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namespace GstOnnxNamespace {
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class GstOnnxClient {
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public:
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GstOnnxClient(GstElement *debug_parent);
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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(GstMlInputImageFormat format);
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GstMlInputImageFormat getInputImageFormat(void);
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GstTensorType getInputImageDatatype(void);
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void setInputImageOffset (float offset);
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float getInputImageOffset ();
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void setInputImageScale (float offset);
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float getInputImageScale ();
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std::vector < Ort::Value > run (uint8_t * img_data, GstVideoInfo vinfo);
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std::vector < const char *> genOutputNamesRaw(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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int32_t getChannels (void);
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GstTensorMeta *copy_tensors_to_meta (std::vector<Ort::Value> &outputs,
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GstBuffer *buffer);
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void parseDimensions(GstVideoInfo vinfo);
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private:
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GstElement *debug_parent;
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void setInputImageDatatype (GstTensorType datatype);
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template < typename T>
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void convert_image_remove_alpha (T *dest, GstMlInputImageFormat hwc,
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uint8_t **srcPtr, uint32_t srcSamplesPerPixel, uint32_t stride, T offset, T div);
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bool doRun(uint8_t * img_data, GstVideoInfo vinfo, std::vector < Ort::Value > &modelOutput);
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Ort::Env env;
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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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std::vector < const char *> outputNamesRaw;
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std::vector < Ort::AllocatedStringPtr > outputNames;
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std::vector < GQuark > outputIds;
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GstMlInputImageFormat inputImageFormat;
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GstTensorType inputDatatype;
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size_t inputDatatypeSize;
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bool fixedInputImageSize;
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float inputTensorOffset;
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float inputTensorScale;
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};
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}
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#endif /* __GST_ONNX_CLIENT_H__ */
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