yolov5 C++环境搭建

安装依赖包pip install onnx模型转化python export.py --weights yolov5s.pt --include onnxopencv版本要求4.5以上安装部署器opencv 4.8.0opencv编译下载git clone https://github.com/opencv/opencv.gitcd opencv git checkout 4.8.0 mkdir build cd build cmake -D CMAKE_BUILD_TYPERelease \ -D CMAKE_INSTALL_PREFIX/usr/local \ -D OPENCV_GENERATE_PKGCONFIGON \ -D BUILD_EXAMPLESOFF \ -D BUILD_TESTSOFF \ -D BUILD_PERF_TESTSOFF \ .. make -j$(nproc) sudo make install代码CMakeLists.txtcmake_minimum_required(VERSION 3.10) project(yolov5_cpp) set(CMAKE_CXX_STANDARD 11) set(OpenCV_DIR /usr/local/lib/cmake/opencv4) find_package(OpenCV REQUIRED) include_directories(${OpenCV_INCLUDE_DIRS}) add_executable(yolo main.cpp) target_link_libraries(yolo ${OpenCV_LIBS})main.cpp#include opencv2/opencv.hpp #include vector #include string using namespace cv; using namespace cv::dnn; using namespace std; const float CONF_THRESHOLD 0.25f; const float NMS_THRESHOLD 0.45f; // 去重框关键 vectorstring class_names { person, bicycle, car, motorcycle, airplane, bus, train, truck, boat, traffic light, fire hydrant, stop sign, parking meter, bench, bird, cat, dog, horse, sheep, cow, elephant, bear, zebra, giraffe, backpack, umbrella, handbag, tie, suitcase, frisbee, skis, snowboard, sports ball, kite, baseball bat, baseball glove, skateboard, surfboard, tennis racket, bottle, wine glass, cup, fork, knife, spoon, bowl, banana, apple, sandwich, orange, broccoli, carrot, hot dog, pizza, donut, cake, chair, couch, potted plant, bed, dining table, toilet, tv, laptop, mouse, remote, keyboard, cell phone, microwave, oven, toaster, sink, refrigerator, book, clock, vase, scissors, teddy bear, hair drier, toothbrush }; int main() { string model_path yolov5s.onnx; Net net readNet(model_path); Mat img imread(bus.jpg); int h img.rows; int w img.cols; Mat blob blobFromImage(img, 1 / 255.0, Size(640, 640), Scalar(), true, false); net.setInput(blob); Mat pred; net.forward(pred, net.getUnconnectedOutLayersNames()[0]); vectorRect boxes; vectorfloat confs; vectorint classIds; float* data (float*)pred.data; for (int i 0; i 25200; i) { float conf data[4]; if (conf CONF_THRESHOLD) { data 85; continue; } Mat scores(1, class_names.size(), CV_32FC1, data 5); double maxScore; Point maxClassPoint; minMaxLoc(scores, 0, maxScore, 0, maxClassPoint); int classId maxClassPoint.x; float x data[0]; float y data[1]; float ww data[2]; float hh data[3]; int x1 (x - ww / 2) * w / 640; int y1 (y - hh / 2) * h / 640; int w2 ww * w / 640; int h2 hh * h / 640; boxes.push_back(Rect(x1, y1, w2, h2)); confs.push_back(conf); classIds.push_back(classId); data 85; } // ✅ NMS 去重框关键 vectorint indices; NMSBoxes(boxes, confs, CONF_THRESHOLD, NMS_THRESHOLD, indices); // ✅ 最终干净画框 for (int idx : indices) { Rect box boxes[idx]; int cid classIds[idx]; float cf confs[idx]; rectangle(img, box, Scalar(0, 255, 0), 2); string label class_names[cid] to_string(cf).substr(0, 4); putText(img, label, Point(box.x, box.y - 10), FONT_HERSHEY_SIMPLEX, 0.5, Scalar(0, 255, 0), 2); } imshow(YOLOv5 C 干净版, img); waitKey(0); return 0; }编译运行mkdir build cd build cmake .. make ./yolo把图片和onnx都放到build的文件夹里与可执行文件yolo一个目录。