mirror of
https://gitlab.freedesktop.org/gstreamer/gstreamer.git
synced 2024-10-03 17:22:29 +00:00
1ff585233a
This element refactors functionality from gstonnxinference element, namely separating out the ONNX inference from the subsequent analysis. The new element runs an ONNX model on each video frame, and then attaches a TensorMeta meta with the output tensor data. This tensor data will then be consumed by downstream elements such as gstobjectdetector. At the moment, a provisional TensorMeta is used just in the ONNX plugin, but in future this will upgraded to a GStreamer API for other plugins to consume. Part-of: <https://gitlab.freedesktop.org/gstreamer/gstreamer/-/merge_requests/4916>
69 lines
2.4 KiB
C++
69 lines
2.4 KiB
C++
/*
|
|
* GStreamer gstreamer-onnxclient
|
|
* Copyright (C) 2021 Collabora Ltd
|
|
*
|
|
* gstonnxclient.h
|
|
*
|
|
* This library is free software; you can redistribute it and/or
|
|
* modify it under the terms of the GNU Library General Public
|
|
* License as published by the Free Software Foundation; either
|
|
* version 2 of the License, or (at your option) any later version.
|
|
*
|
|
* This library is distributed in the hope that it will be useful,
|
|
* but WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
|
|
* Library General Public License for more details.
|
|
*
|
|
* You should have received a copy of the GNU Library General Public
|
|
* License along with this library; if not, write to the
|
|
* Free Software Foundation, Inc., 51 Franklin St, Fifth Floor,
|
|
* Boston, MA 02110-1301, USA.
|
|
*/
|
|
#ifndef __GST_ONNX_CLIENT_H__
|
|
#define __GST_ONNX_CLIENT_H__
|
|
|
|
#include <gst/gst.h>
|
|
#include <onnxruntime_cxx_api.h>
|
|
#include <gst/video/video.h>
|
|
#include "gstml.h"
|
|
#include "gstonnxenums.h"
|
|
#include "tensor/gsttensormeta.h"
|
|
|
|
namespace GstOnnxNamespace {
|
|
|
|
class GstOnnxClient {
|
|
public:
|
|
GstOnnxClient(void);
|
|
~GstOnnxClient(void);
|
|
bool createSession(std::string modelFile, GstOnnxOptimizationLevel optim,
|
|
GstOnnxExecutionProvider provider);
|
|
bool hasSession(void);
|
|
void setInputImageFormat(GstMlInputImageFormat format);
|
|
GstMlInputImageFormat getInputImageFormat(void);
|
|
std::vector < Ort::Value > run (uint8_t * img_data, GstVideoInfo vinfo);
|
|
std::vector < const char *> genOutputNamesRaw(void);
|
|
bool isFixedInputImageSize(void);
|
|
int32_t getWidth(void);
|
|
int32_t getHeight(void);
|
|
GstTensorMeta* copy_tensors_to_meta(std::vector < Ort::Value > &outputs,GstBuffer* buffer);
|
|
void parseDimensions(GstVideoInfo vinfo);
|
|
private:
|
|
bool doRun(uint8_t * img_data, GstVideoInfo vinfo, std::vector < Ort::Value > &modelOutput);
|
|
Ort::Env env;
|
|
Ort::Session * session;
|
|
int32_t width;
|
|
int32_t height;
|
|
int32_t channels;
|
|
uint8_t *dest;
|
|
GstOnnxExecutionProvider m_provider;
|
|
std::vector < Ort::Value > modelOutput;
|
|
std::vector < std::string > labels;
|
|
std::vector < const char *> outputNamesRaw;
|
|
std::vector < Ort::AllocatedStringPtr > outputNames;
|
|
std::vector < GQuark > outputIds;
|
|
GstMlInputImageFormat inputImageFormat;
|
|
bool fixedInputImageSize;
|
|
};
|
|
}
|
|
|
|
#endif /* __GST_ONNX_CLIENT_H__ */
|