52 lines
2.1 KiB
C++
52 lines
2.1 KiB
C++
#pragma once
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#include <fstream>
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#include <iostream>
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#include <opencv2/opencv.hpp>
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#include "include/cuda_utils.h"
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#include "include/logging.h"
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#include "include/model.h"
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#include "include/postprocess.h"
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#include "include/preprocess.h"
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#include "include/utils.h"
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namespace trt_yolov8 {
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using namespace nvinfer1;
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class trt_yolov8_pose_detector
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{
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private:
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/* data */
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void serialize_engine(std::string& wts_name, std::string& engine_name, int& is_p, std::string& sub_type, float& gd,
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float& gw, int& max_channels);
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void deserialize_engine(std::string& engine_name, IRuntime** runtime, ICudaEngine** engine,
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IExecutionContext** context);
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void prepare_buffer(ICudaEngine* engine, float** input_buffer_device, float** output_buffer_device,
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float** output_buffer_host, float** decode_ptr_host, float** decode_ptr_device,
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std::string cuda_post_process);
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void infer(IExecutionContext& context, cudaStream_t& stream, void** buffers, float* output, int batchsize,
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float* decode_ptr_host, float* decode_ptr_device, int model_bboxes, std::string cuda_post_process);
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Logger gLogger;
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const int kOutputSize = kMaxNumOutputBbox * (sizeof(Detection) - sizeof(float) * 32) / sizeof(float) + 1;
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cudaStream_t stream;
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int model_bboxes;
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// Deserialize the engine from file
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nvinfer1::IRuntime* runtime = nullptr;
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nvinfer1::ICudaEngine* engine = nullptr;
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nvinfer1::IExecutionContext* context = nullptr;
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std::string cuda_post_process = "c";
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public:
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trt_yolov8_pose_detector(std::string model_path = "");
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~trt_yolov8_pose_detector();
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// detect
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void detect(std::vector<cv::Mat> images, std::vector<std::vector<Detection>>& detections);
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// serialize wts to plan file for pose estimate
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// sub_type: [ n/s/m/l/x/n2/s2/m2/l2/x2/n6/s6/m6/l6/x6 ]
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bool wts_2_engine(std::string wts_name, std::string engine_name, std::string sub_type);
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};
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} |