OpenCV3.3深度神经网络DNN模块 实例5：FCN模型实现图像分割

1 #include <opencv2/opencv.hpp> 2 #include <opencv2/dnn.hpp> 3 #include <iostream> 4 5 using namespace cv; 6 using namespace cv::dnn; 7 using namespace std; 8 9 const size_t width = 300; 10 const size_t height = 300; 11 String labelFile = "D:/opencv3.3/opencv/sources/samples/data/dnn/pascalclasses.txt"; 12 String modelFile = "D:/opencv3.3/opencv/sources/samples/data/dnn/fcn8sheavypascalaffemodel"; 13 String model_text_file = "D:/opencv3.3/opencv/sources/samples/data/dnn/fcn8sheavypascal.prototxt"; 14 15 vector<Vec3b> readColors(); 16 int main(int argc, char** argv) 22 namedWindow("input image", CV_WINDOW_AUTOSIZE); 23 imshow("input image", frame); 24 resize(frame, frame, Size(500, 500));//改变尺寸 25 vector<Vec3b> colors = readColors(); 26 // 27 // init net 初始化网络 28 Net net = readNetFrCaffe(model_text_file, modelFile); 29 Mat blobImage = blobFrImage(frame); 30 31 // use net 使用网络 32 float time = getTickCount(); 33 net.setInput(blobImage, "data"); 34 Mat score = net.forward("score"); 35 float tt = getTickCount() time; 36 printf("time consume: %.2f ms \n", (tt / getTickFrequency()) * 1000); 37 38 // segmentation and display 分割并显示 39 const int rows = score.size[2]; 40 const int cols = score.size[3]; 41 const int chns = score.size[1]; 42 Mat maxCl(rows, cols, CV_8UC1); 43 Mat maxVal(rows, cols, CV_32FC1); 44 45 // setup LUT LUT查找 46 for (int c = 0; c < chns; c++) 56 } 57 } 58 } 59 60 // look up colors 找到对应颜色 61 Mat result = Mat::zeros(rows, cols, CV_8UC3); 62 for (int row = 0; row < rows; row++) 68 } 69 Mat dst; 70 imshow("FCNdemo1", result); 71 addWeighted(frame, 0.3, result, 0.7, 0, dst);//增加宽度 72 imshow("FCNdemo", dst); 73 74 waitKey(0); 75 return 0; 76 } 77 78 vector<Vec3b> readColors() 85 string line; 86 while (!fp.eof()) 102 } 103 return colors; 104 }

pascal可实现分割的种类和显示颜色（BGR）可见pascalclasses.txt文件

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