gstreamer/subprojects/gst-plugins-bad/ext/onnx/gstonnxclient.h
Daniel Morin 15e5866e51 onnx: add offset and scale properties
- Offset each datapoint by the value set on offset property.
- Scale each datapoint by the value set on scale property.

Part-of: <https://gitlab.freedesktop.org/gstreamer/gstreamer/-/merge_requests/5761>
2023-12-05 16:54:45 +00:00

98 lines
3.3 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 "tensor/gsttensormeta.h"
typedef enum
{
GST_ONNX_OPTIMIZATION_LEVEL_DISABLE_ALL,
GST_ONNX_OPTIMIZATION_LEVEL_ENABLE_BASIC,
GST_ONNX_OPTIMIZATION_LEVEL_ENABLE_EXTENDED,
GST_ONNX_OPTIMIZATION_LEVEL_ENABLE_ALL,
} GstOnnxOptimizationLevel;
typedef enum
{
GST_ONNX_EXECUTION_PROVIDER_CPU,
GST_ONNX_EXECUTION_PROVIDER_CUDA,
} GstOnnxExecutionProvider;
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);
void setInputImageDatatype(GstTensorType datatype);
GstTensorType getInputImageDatatype(void);
void setInputImageOffset (float offset);
float getInputImageOffset ();
void setInputImageScale (float offset);
float getInputImageScale ();
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:
template < typename T>
void convert_image_remove_alpha (T *dest, GstMlInputImageFormat hwc,
uint8_t **srcPtr, uint32_t srcSamplesPerPixel, uint32_t stride, T offset, T div);
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;
GstTensorType inputDatatype;
size_t inputDatatypeSize;
bool fixedInputImageSize;
float inputTensorOffset;
float inputTensorScale;
};
}
#endif /* __GST_ONNX_CLIENT_H__ */