选中ocr_system项目 右键-->仅用于项目-->仅生成ocr_system, 生成ocr_system.dll,打开cmd cd到Release目录下,就可以看到ocr_system.dll了。
下图中的Debug在编译的时候记得换成Release,不然就会报下图错误列表中的错误。
这样ocr_system.dll 和 ocr_system.exe都生成了就可以为下一步做winform ocr识别做基础了。
ocr_system c++中 main.cpp代码如下:

#include "glog/logging.h" #include "omp.h" #include "opencv2/core.hpp" #include "opencv2/imgcodecs.hpp" #include "opencv2/imgproc.hpp" #include <chrono> #include <iomanip> #include <iostream> #include <ostream> #include <vector> #include <cstring> #include <fstream> #include <numeric> #include <include/config.h> #include <include/ocr_det.h> #include <include/ocr_rec.h> //#include"ocr.h" using namespace std; using namespace cv; using namespace PaddleOCR; /* 1.返回框选字体; 2.返回解析字符串 */ extern "C" __declspec(dllexport) cv::Mat * LoadModel(char* input, int width, int height); __declspec(dllexport) cv::Mat* LoadModel(char* input, int width, int height) { OCRConfig config("D:\Paddle\PaddleOCR\deploy\cpp_infer\tools\config.txt"); config.PrintConfigInfo(); //std::string img_path(argv[2]); //cv::Mat srcimg = cv::imread(img_path, cv::IMREAD_COLOR); cv::Mat srcimg(height, width, CV_8UC3, input); DBDetector det(config.det_model_dir, config.use_gpu, config.gpu_id, config.gpu_mem, config.cpu_math_library_num_threads, config.use_mkldnn, config.max_side_len, config.det_db_thresh, config.det_db_box_thresh, config.det_db_unclip_ratio, config.use_polygon_score,config.visualize, config.use_tensorrt, config.use_fp16); Classifier* cls = nullptr; if (config.use_angle_cls == true) { cls = new Classifier(config.cls_model_dir, config.use_gpu, config.gpu_id, config.gpu_mem, config.cpu_math_library_num_threads, config.use_mkldnn, config.cls_thresh, config.use_tensorrt, config.use_fp16); } CRNNRecognizer rec(config.rec_model_dir, config.use_gpu, config.gpu_id, config.gpu_mem, config.cpu_math_library_num_threads, config.use_mkldnn, config.char_list_file, config.use_tensorrt, config.use_fp16); auto start = std::chrono::system_clock::now(); std::vector<std::vector<std::vector<int>>> boxes; // 检测 cv::Mat ocrImage; ocrImage = det.Run(srcimg, boxes); // 识别 rec.Run(boxes, srcimg, cls); auto end = std::chrono::system_clock::now(); auto duration = std::chrono::duration_cast<std::chrono::microseconds>(end - start); std::cout << "Cost " << double(duration.count()) * std::chrono::microseconds::period::num / std::chrono::microseconds::period::den << "s" << std::endl; cv::Mat gray; cv::cvtColor(srcimg, gray, COLOR_BGR2GRAY); return new cv::Mat(ocrImage); }
先到这里,后面继续更新。