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128 lines
4.2 KiB
128 lines
4.2 KiB
/*
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* @Author: error: error: git config user.name & please set dead value or install git && error: git config user.email & please set dead value or install git & please set dead value or install git
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* @Date: 2024-03-29 11:44:17
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* @LastEditors: error: error: git config user.name & please set dead value or install git && error: git config user.email & please set dead value or install git & please set dead value or install git
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* @LastEditTime: 2024-03-29 14:35:20
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* @FilePath: \dev_uniform_merge_55kg\mpp\sample\Custom_Sample\main_app_hi3559a\mpp\ai_track\ai\use_mnn.hpp
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* @Description: 这是默认设置,请设置`customMade`, 打开koroFileHeader查看配置 进行设置: https://github.com/OBKoro1/koro1FileHeader/wiki/%E9%85%8D%E7%BD%AE
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*/
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#ifndef NNIE_LITE_USE_MNN_HPP
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#define NNIE_LITE_USE_MNN_HPP
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#include <unistd.h>
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#include <vector>
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#include <chrono>
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#include <memory>
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#include <iostream>
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#include <string>
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#include <sys/time.h>
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#include <opencv2/core.hpp>
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#include <opencv2/imgproc.hpp>
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#include "gd_alg_type.h"
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#include "MNN/Interpreter.hpp"
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#include "MNN/MNNDefine.h"
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#include "MNN/Tensor.hpp"
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#include "MNN/ImageProcess.hpp"
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#define DEBUG_TMP (0)
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#define D_CPU_BIGCORE (1)
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using namespace std::chrono;
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namespace GUD {
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namespace ALG{
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class ForwardNet {
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public:
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explicit ForwardNet();
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explicit ForwardNet(const gud_siamrpn_config_t conf);
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~ForwardNet();
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int net_init(int model_idx, const char* model_path);
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int net_deinit(int model_idx);
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int clsMnnForward(const float *cmap_data, float* coutput_data, bool dataReady);
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int regMnnForward(const float *rmap_data, float* routput_data, bool dataReady);
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int updateTwoKernels(const float *ckernel_data, const float *rkernel_data);
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int updateTwoMaps(const float *cm_data, const float *rm_data);
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void showTensor(MNN::Tensor *TensorIn, int len, int diff);
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public:
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int Thread2done_;
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int InputDataDone_;
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int clsForwardDone_;
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int regForwardDone_;
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int updataCKDone_;
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int updataRKDone_;
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int updataCMDone_;
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int updataRMDone_;
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private:
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int deviceType_;
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bool initialized_;
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int numThread_;
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int prec_type_;
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int clsMpSize_;
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int regMpSize_;
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int clsOutSize_;
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int regOutSize_;
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std::string clsKernelName = "clskernel";
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std::string clsMapName = "x";
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std::string clsOutputName = "55";
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std::string regKernelNane = "regkernel";
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std::string regMapName = "y";
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std::string regOutputName = "53";
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std::shared_ptr<MNN::Interpreter> net_interpreter_;
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MNN::Session* net_sess_ = nullptr;
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MNN::Tensor* input_tensor = nullptr;
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std::map<std::string, MNN::Tensor*> inputClsTensor;
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std::map<std::string, MNN::Tensor*> inputRegTensor;
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std::map<std::string, MNN::Tensor*> input4Tensors;
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std::vector<int> InputDim;
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//// Edit By YANGXI on 240426 to solve tracker init slow problem
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std::vector<int> clsMap_dims_;
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std::vector<int> regMap_dims_;
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std::vector<int> ck_dims_;
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std::vector<int> rk_dims_;
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std::vector<int> clsOut_dims_;
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std::vector<int> regOut_dims_;
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std::shared_ptr<MNN::Interpreter> net_cls_;
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MNN::ScheduleConfig MNNconfig_cls_;
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char *MnnModel_cls_;
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MNN::Session *session_cls_;
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std::shared_ptr<MNN::Interpreter> net_reg_;
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MNN::ScheduleConfig MNNconfig_reg_;
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char *MnnModel_reg_;
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MNN::Session *session_reg_;
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MNN::Tensor *clsKernelTensor_;
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MNN::Tensor *regKernelTensor_;
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MNN::Tensor *clsMapTensor_;
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MNN::Tensor *regMapTensor_;
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MNN::Tensor *clsOutTensor_;
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MNN::Tensor *regOutTensor_;
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steady_clock::time_point t1_;
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steady_clock::time_point t2_;
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duration<double> time_span_;
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double time_all_ = 0;
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};
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};
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}
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#endif //NNIE_LITE_USE_MNN_HPP
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