#pragma once #include #include #include #include "include/cuda_utils.h" #include "include/logging.h" #include "include/model.h" #include "include/postprocess.h" #include "include/preprocess.h" #include "include/utils.h" namespace trt_yolov8 { using namespace nvinfer1; class trt_yolov8_detector { private: void serialize_engine(std::string& wts_name, std::string& engine_name, int& is_p, std::string& sub_type, float& gd, float& gw, int& max_channels); void deserialize_engine(std::string& engine_name, IRuntime** runtime, ICudaEngine** engine, IExecutionContext** context); void prepare_buffer(ICudaEngine* engine, float** input_buffer_device, float** output_buffer_device, float** output_buffer_host, float** decode_ptr_host, float** decode_ptr_device, std::string cuda_post_process); void infer(IExecutionContext& context, cudaStream_t& stream, void** buffers, float* output, int batchsize, float* decode_ptr_host, float* decode_ptr_device, int model_bboxes, std::string cuda_post_process); const int kOutputSize = kMaxNumOutputBbox * sizeof(Detection) / sizeof(float) + 1; Logger gLogger; cudaStream_t stream; int model_bboxes; // Deserialize the engine from file nvinfer1::IRuntime* runtime = nullptr; nvinfer1::ICudaEngine* engine = nullptr; nvinfer1::IExecutionContext* context = nullptr; std::string cuda_post_process = "c"; public: trt_yolov8_detector(std::string model_path = ""); ~trt_yolov8_detector(); // detect void detect(std::vector images, std::vector>& detections); // serialize wts to plan file for target detect // sub_type: [ n/s/m/l/x/n2/s2/m2/l2/x2/n6/s6/m6/l6/x6 ] bool wts_2_engine(std::string wts_name, std::string engine_name, std::string sub_type); }; }