機器學習 C++ 的opencv實現SVM圖像二分類的測試 (三)
數據集合下載地址：https://download.csdn.net/download/hgaohr1021/89506900
根據上節得到的svm.xml，測試結果為：
#include <stdio.h>
#include <time.h>
#include <opencv2/opencv.hpp> #include <iostream>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include "opencv2/imgcodecs.hpp"
#include <opencv2/core/utils/logger.hpp>
#include <opencv2/ml/ml.hpp>
#include <io.h>using namespace std;
using namespace cv;
using namespace cv::ml;void getFiles(string path, vector<string>& files);
int main()
{int result = 0;string filePath = "data\\test_image\\0";vector<string> files;getFiles(filePath, files);int number = files.size();cout << number << endl;string modelpath = "svm.xml";cv::Ptr<cv::ml::SVM> svm;svm = cv::Algorithm::load<cv::ml::SVM>(modelpath);/*CvSVM svm;svm.clear();string modelpath = "svm.xml";FileStorage svm_fs(modelpath, FileStorage::READ);if (svm_fs.isOpened()){svm.load(modelpath.c_str());}*/FileStorage svm_fs(modelpath, FileStorage::READ);if (svm_fs.isOpened()){svm->load(modelpath.c_str());}for (int i = 0; i < number; i++){Mat inMat = imread(files[i].c_str());resize(inMat, inMat, cv::Size(60, 256), (0, 0), (0, 0), cv::INTER_LINEAR); //將圖片調整為相同的大小Mat p = inMat.reshape(1, 1);p.convertTo(p, CV_32FC1);int response = (int)svm->predict(p);if (response == 1){result++;}}cout << "識別個數：" << result << endl;cout << "識別率：" << setprecision(2) << fixed << double(result) / (double)(number) << endl;getchar();return 0;
}
void getFiles(string path, vector<string>& files)
{long long hFile = 0;struct _finddata_t fileinfo;string p;if ((hFile = _findfirst(p.assign(path).append("\\*").c_str(), &fileinfo)) != -1){do{if ((fileinfo.attrib & _A_SUBDIR)){if (strcmp(fileinfo.name, ".") != 0 && strcmp(fileinfo.name, "..") != 0)getFiles(p.assign(path).append("\\").append(fileinfo.name), files);}else{files.push_back(p.assign(path).append("\\").append(fileinfo.name));}} while (_findnext(hFile, &fileinfo) == 0);_findclose(hFile);}
}
數據集合下載地址：https://download.csdn.net/download/hgaohr1021/89506900
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