add svm_lbp.xml and test new plate judge model.

accuracy.txt

@@ -1652,3 +1652,23 @@ Recall:33.9553%  ,  Precise:62.5128%  ,  Fscore:44.0071%  .
 Recall:33.9553%, Precise:62.5128%, Fscore:44.0071%.
 平均字符差距:3.6,  完全匹配数:2,  完全匹配率:10%  
 总时间:49秒,  平均执行时间:0.98秒
+2016-06-20 08:42:36
+总图片数:200,  未识出图片:6,  定位率:97%  
+Recall:83.2984%, Precise:86.2716%, Fscore:84.7589%.
+平均字符差距:0.845361,  完全匹配数:127,  完全匹配率:65.4639%  
+总时间:200秒,  平均执行时间:1秒
+2016-06-20 08:48:27
+总图片数:200,  未识出图片:7,  定位率:96.5%  
+Recall:88.3398%, Precise:91.9465%, Fscore:90.1071%.
+平均字符差距:0.689119,  完全匹配数:132,  完全匹配率:68.3938%  
+总时间:187秒,  平均执行时间:0.935秒
+2016-06-20 09:40:17
+总图片数:200,  未识出图片:13,  定位率:93.5%  
+Recall:82.0834%, Precise:87.8835%, Fscore:84.8845%.
+平均字符差距:0.983957,  完全匹配数:116,  完全匹配率:62.0321%  
+总时间:203秒,  平均执行时间:1.015秒
+2016-06-20 09:44:25
+总图片数:200,  未识出图片:7,  定位率:96.5%  
+Recall:88.3398%, Precise:91.9465%, Fscore:90.1071%.
+平均字符差距:0.689119,  完全匹配数:132,  完全匹配率:68.3938%  
+总时间:191秒,  平均执行时间:0.955秒

src/core/plate_detect.cpp

@@ -22,8 +22,7 @@ namespace easypr {
     std::vector<CPlate> all_result_Plates;
 
     //如果颜色查找找到n个以上（包含n个）的车牌，就不再进行Sobel查找了。
-    const int color_find_max = m_maxPlates;
-  
+
     if ( !type || type & PR_DETECT_SOBEL)
     {
       m_plateLocate->plateSobelLocate(src, sobel_Plates, index);
@@ -71,6 +70,37 @@ namespace easypr {
     // 使用非极大值抑制来判断车牌
     PlateJudge::instance()->plateJudgeUsingNMS(all_result_Plates, resultVec, m_maxPlates);
 
+    if (0) 
+    {
+      Mat result = src.clone();
+      for (size_t i = 0; i < resultVec.size(); i++)
+      {
+        CPlate plate = resultVec[i];
+
+        Rect_<float> outputRect;
+        calcSafeRect(plate.getPlatePos(), src, outputRect);
+
+        if (1)
+        {
+          cv::rectangle(result, outputRect, Scalar(0, 0, 255));
+        }
+
+        if (0)
+        {
+          std::stringstream ss(std::stringstream::in | std::stringstream::out);
+          ss << "resources/image/tmp/plate_" << i << ".jpg";
+          imwrite(ss.str(), src(outputRect));
+        }
+      }
+
+      if (1) 
+      {
+        imshow("result", result);
+        waitKey(0);
+        destroyWindow("result");
+      }
+    }
+
     return 0;
   }
 

src/core/plate_judge.cpp

@@ -119,8 +119,8 @@ namespace easypr {
         waitKey(0);
       }
 
-      int response = plateSetScore(plate);
-      if (response == 0) {
+      int result = plateSetScore(plate);
+      if (result == 0) {
         plateVec.push_back(plate);
         if (0) {
           imshow("plateMat", inMat);
@@ -139,9 +139,9 @@ namespace easypr {
 
         plate.setPlateMat(tmpDes);
 
-        int responseCascade = plateSetScore(plate);
+        int resultCascade = plateSetScore(plate);
 
-        if (responseCascade == 0) {
+        if (resultCascade == 0) {
           plateVec.push_back(plate);
         }
       }

src/core/plate_locate.cpp

@@ -964,7 +964,7 @@ int CPlateLocate::plateMserLocate(Mat src, vector<CPlate> &candPlates, int index
     //flags.push_back(1);
   }
 
-  vector<RotatedRect> rects_mser_blue;
+  vector<RotatedRect> rects_mser;
   vector<CPlate> plates;
   Mat src_b;
 
@@ -975,24 +975,28 @@ int CPlateLocate::plateMserLocate(Mat src, vector<CPlate> &candPlates, int index
     //double scale_ratio = 1;
     //Mat image = scaleImage(channelImage, Size(scale_size, scale_size), scale_ratio);
     Mat image = channelImage;
-    mserSearch(image, BLUE, src_b, rects_mser_blue, index);
+    mserSearch(image, BLUE, src_b, rects_mser, index);
   }
 
-  for (size_t i = 0; i < rects_mser_blue.size(); ++i)
+  for (size_t i = 0; i < rects_mser.size(); ++i)
   {
+    Rect_<float> outputRect;
+    calcSafeRect(rects_mser[i], src, outputRect);
+
     if (0)
     {
       std::stringstream ss(std::stringstream::in | std::stringstream::out);
       ss << "resources/image/tmp/plate_" << i << ".jpg";
-
-      Rect_<float> outputRect;
-      calcSafeRect(rects_mser_blue[i], src, outputRect);
-
       imwrite(ss.str(), src(outputRect));
     }
-  }
 
+    CPlate plate;
+    plate.setPlateLocateType(CMSER);
+    plate.setPlateMat(src(outputRect));
+    plate.setPlatePos(rects_mser[i]);
 
+    candPlates.push_back(plate);
+  }
 
   //deskew(src, src_b, rects_mser_blue, plates);
 

test/accuracy.hpp

@@ -90,18 +90,19 @@ namespace easypr {
       CPlateRecognize pr;
 
       // 设置Debug模式
-
       pr.setDebug(false);
-
       pr.setLifemode(true);
 
       // 设置要处理的一张图片中最多有多少车牌
-
       pr.setMaxPlates(4);
-
       pr.setDetectType(PR_DETECT_COLOR | PR_DETECT_SOBEL);
       //pr.setDetectType(PR_DETECT_CMSER);
 
+      //CPlateDetect pd;
+      //pd.setDetectType(PR_DETECT_CMSER);
+      //pd.setPDDebug(false);
+      //pd.setPDLifemode(true);
+
       int size = files.size();
 
       if (0 == size) {
@@ -177,6 +178,8 @@ namespace easypr {
         vector<CPlate> plateVec;
         int result = pr.plateRecognize(src, plateVec);
 
+        //pd.plateDetect(src, plateVec);
+
         // get the ground truth and compare it with the detect list;
         map<string, vector<CPlate>>::iterator it;
         vector<CPlate> plateVecGT;

test/plate.hpp

@@ -110,7 +110,9 @@ int test_plate_recognize() {
   CPlateRecognize pr;
   pr.setLifemode(true);
   pr.setDebug(true);
-  pr.setDetectType(easypr::PR_DETECT_CMSER);
+  pr.setMaxPlates(4);
+  pr.setDetectType(PR_DETECT_COLOR | PR_DETECT_SOBEL);
+  //pr.setDetectType(easypr::PR_DETECT_CMSER);
 
   //vector<string> plateVec;
   vector<CPlate> plateVec;