时间序列识别代码调试版本1-白红宇

时间序列识别代码调试版本1

阅读量：5957 次

发布时间：2019-06-19

本文共 2441 字，大约阅读时间需要 8 分钟。

#include 
     
      //#include 
      
       #include 
       
        #include 
        
         #include 
         
          #include 
          
           //#include 
           
            //#include 
            
             //#include 
             
              //#include 
              
               #include 
               
                #include 
                
                 #include 
                 
                  using namespace std;using namespace cv;//FeatureEvaluatorint main(){ /************************************************************************************ 参数设置 *************************************************************************************/ //some parameters: int positive_num = 1000; int negative_num = 9000; vector
                  
                    v_positive_img; vector
                   
                     v_negative_img; //先考虑训练0 int test_char = 0; //正例、负例 string all_class_path = "C:\\Users\\cong\\Desktop\\研一实战\\项目\\图像中时间数字识别\\OCR\\result\\"; string img_txt; for (int i = 0; i < 10; i++) { //数字转字符 stringstream ss; ss << i; string test_char_str = ss.str(); img_txt = all_class_path + "result" + test_char_str + ".txt"; string path; ifstream finPos(img_txt); if (test_char == i) { //vector
                    
                      channels; //用来装一幅图的N个通道；还没初始化 getline(finPos, path); //应该把文件中的图片个数也记录下来，由于该次的数据集，0~9个数一样，因此，可以考虑先不这么做 int img_num = 0; //把path，第一行字符变成数字，还没有完成 for (int j = 0; j
                     
                       channels; //用来装一幅图的N个通道；还没初始化 getline(finPos, path); //应该把文件中的图片个数也记录下来，由于该次的数据集，0~9个数一样，因此，可以考虑先不这么做 int img_num = 0; //把path，第一行字符变成数字，还没有完成 for (int j = 0; j
                      
                        myRect; //float scaleFactor; //Size minSize; //Size maxSize; //float threshold; //int slidingStep; //vector
                       
                         values; //myICFDetector.detect(img_test, myRect, scaleFactor, 10, 50, threshold, slidingStep, values); /* C++: void ICFDetector::detect(const Mat& image, vector
                        
                         & objects, float scaleFactor, Size minSize, Size maxSize, float threshold, int slidingStep, std::vector
                         
                          & values) C++: detect(const Mat& img, std::vector
                          
                           & objects, float minScaleFactor, float maxScaleFactor, float factorStep, float threshold, int slidingStep, std::vector
                           
                            & values) Parameters: image – image for detection objects – output array of bounding boxes scaleFactor – scale between layers in detection pyramid minSize – min size of objects in pixels maxSize – max size of objects in pixels minScaleFactor – min factor by which the image will be resized maxScaleFactor – max factor by which the image will be resized factorStep – scaling factor is incremented each pyramid layer according to this parameter slidingStep – sliding window step values – output vector with values of positive samples */ return 0;}