Train_RFID_Linux/code/inference/inference.h

89 lines
3.0 KiB
C++

#ifndef _INFERENCE_H_
#define _INFERENCE_H_
#include <algorithm>
#include <chrono>
#include <cstdint>
#include <fstream>
#include <functional>
#include <iostream>
#include <numeric>
#include <vector>
#include <sys/time.h>
#include <sys/types.h>
#include <time.h>
#include <unistd.h>
#include <NvInfer.h>
#include <NvInferPlugin.h>
#include <NvOnnxParser.h>
#include <NvCaffeParser.h>
#include <cuda.h>
#include <cuda_runtime.h>
#include <cuda_runtime_api.h>
#include "cuda_utils.h"
#include "logging.h"
using namespace nvinfer1;
using namespace nvcaffeparser1;
using namespace std;
#define ENABLE_CUDA_PREPROCESS
class Inference
{
public:
Inference();
~Inference();
inline unsigned int getElementSize(nvinfer1::DataType t);
inline int64_t volume(const nvinfer1::Dims& d);
ICudaEngine* build_engine_onnx(Logger gLogger, unsigned int maxBatchSize, unsigned int maxWorkSpaceSize, IBuilder* builder, IBuilderConfig* config, std::string& source_onnx);
ICudaEngine* build_engine_caffe(Logger gLogger, unsigned int maxBatchSize, unsigned int maxWorkSpaceSize, IBuilder* builder, IBuilderConfig* config,
const std::string& strCaffeModelFile, const std::string& strCaffeDeployFile, const std::vector<std::string>& vecOutputs);
void ONNXToModel(Logger gLogger, unsigned int maxBatchSize, unsigned int maxWorkSpaceSize, IHostMemory** modelStream, std::string& onnx_model_name);
void CaffeToModel(Logger gLogger, unsigned int maxBatchSize, unsigned int maxWorkSpaceSize, IHostMemory** modelStream, std::string& caffe_model_name, std::string& caffe_deploy_name, std::vector<std::string>& outputs);
void doInference(IExecutionContext& context, cudaStream_t& stream, void **buffers, unsigned int inputIndex, float* input, int inputSize,
unsigned int ouputIndex, float* output, int outputSize, int batchSize);
void doInferenceV2(IExecutionContext& context, cudaStream_t& stream, void **buffers, unsigned int ouputIndex, float* output, int outputSize, int batchSize);
void doInferenceV3(IExecutionContext& context, cudaStream_t& stream, void **buffers, unsigned int inputIndex, float* input, int inputSize,
unsigned int ouputIndex, float* output, int outputSize, int batchSize);
void doInferenceV4(IExecutionContext& context, cudaStream_t& stream, void **buffers, unsigned int ouputIndex, float* output, int outputSize, int batchSize);
float* pfBuffers_[2];
float* pfInputData_ = nullptr;
float* pfOutputData_ = nullptr;
uint8_t* pu8ImgHost_ = nullptr; //相关内存分配
uint8_t* pu8ImgDevice_ = nullptr;
unsigned int uiInputIndex_ = 0, uiOutputIndex_ = 0;
cudaStream_t* pImagePreprocessStream_ = nullptr; //图像预处理CUDA流
cudaStream_t* pInferenceModelStream_ = nullptr; //模型推理CUDA流
Logger* pGLogger_ = nullptr;
IRuntime* pRuntime_ = nullptr;
ICudaEngine* pEngine_ = nullptr;
IExecutionContext* pContext_ = nullptr;
private:
};
#endif //END OF _INFERENCE_H_