C++|C++ OpenCV dnn tf模型图像分类@2020@平台部署@图像算法@DL C++OpenCVdnntf模型图像分类@2020

https://blog.csdn.net/PecoHe/article/details/88417995

#include #include #include #include #include #includeusing namespace std; using namespace cv; using namespace cv::dnn; String label_file = "./../../../model_files/inception_v5/imagenet_comp_graph_label_strings.txt"; String tf_pbfile = "./../../../model_files/inception_v5/tensorflow_inception_graph.pb"; vector read_class_names(String model_label_file); //input size const int w = 224; const int h = 224; int main(int argc, char**argv) { Mat input_image = imread("zebra.jpg"); if (input_image.empty()) { cout << "read image failed!" << endl; return -1; } //show input image namedWindow("input_image", WINDOW_AUTOSIZE); imshow("input_image", input_image); //BGR-->RGB cvtColor(input_image, input_image, COLOR_BGR2RGB); //read labels vector labels = read_class_names(label_file); //load cnn model Net cnn_net = readNetFromTensorflow(tf_pbfile); if (cnn_net.empty()) { cout << "load net failed!" << endl; return -1; } //show layers names vector layer_names = cnn_net.getLayerNames(); for (int i = 0; i < layer_names.size(); i++) { int id = cnn_net.getLayerId(layer_names[i]); auto layer = cnn_net.getLayer(id); cout << "layerIndex:" << id << " " << "type:" << layer->type.c_str() << " " << "name:" << layer->name.c_str() << endl; } //get input of the net Mat input_blob = blobFromImage(input_image, 1.0f, Size(h, w), Scalar(), true, false); input_blob -= 117.0; Mat prob; //set input cnn_net.setInput(input_blob, "input"); //forward the net until "softmax2" prob = cnn_net.forward("softmax2"); Mat probMat = prob.reshape(1, 1); Point classNumber; double classProb; minMaxLoc(probMat, NULL, &classProb, NULL, &classNumber); int classidx = classNumber.x; cout << "classification:" << labels.at(classidx).c_str() << endl << "score:" << fixed << setprecision(2) << classProb; //show result cvtColor(input_image, input_image, COLOR_RGB2BGR); putText(input_image, "result:"+labels.at(classidx), Point(20, 20), FONT_HERSHEY_COMPLEX, 1.0, Scalar(0, 255, 0), 2, 8); putText(input_image, "score:"+to_string(classProb), Point(20, 50), FONT_HERSHEY_COMPLEX, 1.0, Scalar(0, 255, 0), 2, 8); imshow("result", input_image); waitKey(0); return 0; }vector read_class_names(String model_label_file) { vector class_names; ifstream fp(model_label_file); if (!fp.is_open()) { cout << "open label file failed!" << endl; exit(-1); } string name; while (!fp.eof()) { getline(fp, name); if (name.length()) class_names.push_back(name); } fp.close(); return class_names; }

【C++|C++ OpenCV dnn tf模型图像分类@2020@平台部署@图像算法@DL】