diff --git a/src/core/chars_segment.cpp b/src/core/chars_segment.cpp
index 5265585..c40d38e 100644
--- a/src/core/chars_segment.cpp
+++ b/src/core/chars_segment.cpp
@@ -7,8 +7,8 @@
 
 namespace easypr {
 
-const float DEFAULT_BLUEPERCEMT = 0.3f;//定义蓝色百分比
-const float DEFAULT_WHITEPERCEMT = 0.1f;//定义白色百分比
+const float DEFAULT_BLUEPERCEMT = 0.3f;//瀹氫箟钃濊壊鐧惧垎姣�
+const float DEFAULT_WHITEPERCEMT = 0.1f;//瀹氫箟鐧借壊鐧惧垎姣�
 
 CCharsSegment::CCharsSegment() {
   m_LiuDingSize = DEFAULT_LIUDING_SIZE;
@@ -19,75 +19,75 @@ CCharsSegment::CCharsSegment() {
   m_WhitePercent = DEFAULT_WHITEPERCEMT;
 
   m_debug = DEFAULT_DEBUG;
-}//设置几个类的成员变量，进行初始化
+}//璁剧疆鍑犱釜绫荤殑鎴愬憳鍙橀噺锛岃繘琛屽垵濮嬪寲
 
 
 bool CCharsSegment::verifyCharSizes(Mat r) {
   // Char sizes 45x90
-    //接收一个OpenCV的Mat对象作为参数，将其赋值给r
-  float aspect = 45.0f / 90.0f;//预期的字符宽高比
+    //鎺ユ敹涓�涓狾penCV鐨凪at瀵硅薄浣滀负鍙傛暟锛屽皢鍏惰祴鍊肩粰r
+  float aspect = 45.0f / 90.0f;//棰勬湡鐨勫瓧绗﹀楂樻瘮
   float charAspect = (float)r.cols / (float)r.rows;
-  //输入图像的宽高比，通过计算输入图像的列数和行数得出。
-  float error = 0.7f;//允许的宽高比误差
-  float minHeight = 10.f;//字符最小高度
-  float maxHeight = 35.f;//字符最大高度
+  //杈撳叆鍥惧儚鐨勫楂樻瘮锛岄�氳繃璁＄畻杈撳叆鍥惧儚鐨勫垪鏁板拰琛屾暟寰楀嚭銆�
+  float error = 0.7f;//鍏佽鐨勫楂樻瘮璇樊
+  float minHeight = 10.f;//瀛楃鏈�灏忛珮搴�
+  float maxHeight = 35.f;//瀛楃鏈�澶ч珮搴�
   // We have a different aspect ratio for number 1, and it can be ~0.2
-  float minAspect = 0.05f//最小允许宽高比
+  float minAspect = 0.05f//鏈�灏忓厑璁稿楂樻瘮
   float maxAspect = aspect + aspect * error
-  //最大允许宽高比，由预期的宽高比加上其误差得出
+  //鏈�澶у厑璁稿楂樻瘮锛岀敱棰勬湡鐨勫楂樻瘮鍔犱笂鍏惰宸緱鍑�
   // area of pixels
   int area = cv::countNonZero(r);
-  // 输入图像的非零像素数
+  // 杈撳叆鍥惧儚鐨勯潪闆跺儚绱犳暟
   int bbArea = r.cols * r.rows;
   //% of pixel in area
-  //输入图像的总面积，通过乘以其列数和行数得出
+  //杈撳叆鍥惧儚鐨勬�婚潰绉紝閫氳繃涔樹互鍏跺垪鏁板拰琛屾暟寰楀嚭
   int percPixels = area / bbArea;
-  //非零像素数在总面积中的比例
+  //闈為浂鍍忕礌鏁板湪鎬婚潰绉腑鐨勬瘮渚�
   if (percPixels <= 1 && charAspect > minAspect && charAspect < maxAspect &&
       r.rows >= minHeight && r.rows < maxHeight)
     return true;
   else
     return false;
-}//判断输入图像是否可以被视为一个字符，满足特定的字符尺寸和形状要求
+}//鍒ゆ柇杈撳叆鍥惧儚鏄惁鍙互琚涓轰竴涓瓧绗︼紝婊¤冻鐗瑰畾鐨勫瓧绗﹀昂瀵稿拰褰㈢姸瑕佹眰
 
 
 Mat CCharsSegment::preprocessChar(Mat in) {
   // Remap image
-  //接收一个Mat对象作为输入，它对输入的图像进行一些预处理操作。
+  //鎺ユ敹涓�涓狹at瀵硅薄浣滀负杈撳叆锛屽畠瀵硅緭鍏ョ殑鍥惧儚杩涜涓�浜涢澶勭悊鎿嶄綔銆�
   int h = in.rows;
   int w = in.cols;
-  //获取输入图像的高度和宽度
+  //鑾峰彇杈撳叆鍥惧儚鐨勯珮搴﹀拰瀹藉害
   int charSize = CHAR_SIZE;
 
   Mat transformMat = Mat::eye(2, 3, CV_32F);
-  //定义一个2x3的单位矩阵作为变换矩阵，这个矩阵用于图像的几何变换。
+  //瀹氫箟涓�涓�2x3鐨勫崟浣嶇煩闃典綔涓哄彉鎹㈢煩闃碉紝杩欎釜鐭╅樀鐢ㄤ簬鍥惧儚鐨勫嚑浣曞彉鎹€��
   int m = max(w, h);
 
   transformMat.at<float>(0, 2) = float(m / 2 - w / 2);
   transformMat.at<float>(1, 2) = float(m / 2 - h / 2);
-  //根据输入图像的最大尺寸，调整变换矩阵的中央值，
-  // 以便将图像中心置于新图像的中心。
+  //鏍规嵁杈撳叆鍥惧儚鐨勬渶澶у昂瀵革紝璋冩暣鍙樻崲鐭╅樀鐨勪腑澶�硷紝
+  // 浠ヤ究灏嗗浘鍍忎腑蹇冪疆浜庢柊鍥惧儚鐨勪腑蹇冦��
   Mat warpImage(m, m, in.type());
   warpAffine(in, warpImage, transformMat, warpImage.size(), INTER_LINEAR,
              BORDER_CONSTANT, Scalar(0));
   
   Mat out;
-  //warpAffine函数应用仿射变换，生成新的变换后的图像。
+  //warpAffine鍑芥暟搴旂敤浠垮皠鍙樻崲锛岀敓鎴愭柊鐨勫彉鎹㈠悗鐨勫浘鍍忋��
   resize(warpImage, out, Size(charSize, charSize));
-  //resize函数调整新图像的尺寸至预设的字符大小。
+  //resize鍑芥暟璋冩暣鏂板浘鍍忕殑灏哄鑷抽璁剧殑瀛楃澶у皬銆�
   return out;
 }
 
 
 //! choose the bese threshold method for chinese
 void CCharsSegment::judgeChinese(Mat in, Mat& out, Color plateType)
-{ //接收一个Mat对象作为输入，并对其进行阈值处理以识别中文字符
+{ //鎺ユ敹涓�涓狹at瀵硅薄浣滀负杈撳叆锛屽苟瀵瑰叾杩涜闃堝�煎鐞嗕互璇嗗埆涓枃瀛楃
   Mat auxRoi = in;
-  //表示输入图像的一个子区域，其中可能包含要识别的中文字符
+  //琛ㄧず杈撳叆鍥惧儚鐨勪竴涓瓙鍖哄煙锛屽叾涓彲鑳藉寘鍚璇嗗埆鐨勪腑鏂囧瓧绗�
   float valOstu = -1.f, valAdap = -1.f;
   Mat roiOstu, roiAdap;
-  //为Otsu阈值法和自适应阈值法分别定义了一个变量valOstu和valAdap，
-  // 用于存储阈值
+  //涓篛tsu闃堝�兼硶鍜岃嚜閫傚簲闃堝�兼硶鍒嗗埆瀹氫箟浜嗕竴涓彉閲弙alOstu鍜寁alAdap锛�
+  // 鐢ㄤ簬瀛樺偍闃堝��
   bool isChinese = true;
   if (1) {
     if (BLUE == plateType) {
@@ -102,23 +102,23 @@ void CCharsSegment::judgeChinese(Mat in, Mat& out, Color plateType)
     else {
       threshold(auxRoi, roiOstu, 0, 255, CV_THRESH_OTSU + CV_THRESH_BINARY);
     }
-    //根据输入的颜色类型，使用不同的阈值处理方法对auxRoi进行阈值处理
-    // 生成二值化的图像roiOstu
+    //鏍规嵁杈撳叆鐨勯鑹茬被鍨嬶紝浣跨敤涓嶅悓鐨勯槇鍊煎鐞嗘柟娉曞auxRoi杩涜闃堝�煎鐞�
+    // 鐢熸垚浜屽�煎寲鐨勫浘鍍弐oiOstu
     roiOstu = preprocessChar(roiOstu);
-    //对二值化的图像进行字符识别预处理
-    //调用preprocessChar(roiOstu)方法对图像进行进一步处理
+    //瀵逛簩鍊煎寲鐨勫浘鍍忚繘琛屽瓧绗﹁瘑鍒澶勭悊
+    //璋冪敤preprocessChar(roiOstu)鏂规硶瀵瑰浘鍍忚繘琛岃繘涓�姝ュ鐞�
     if (0) {
       imshow("roiOstu", roiOstu);
       waitKey(0);
       destroyWindow("roiOstu");
     }
     auto character = CharsIdentify::instance()->identifyChinese(roiOstu, valOstu, isChinese);
-    //对预处理后的图像进行字符识别，并返回识别的结果和阈值。
+    //瀵归澶勭悊鍚庣殑鍥惧儚杩涜瀛楃璇嗗埆锛屽苟杩斿洖璇嗗埆鐨勭粨鏋滃拰闃堝�笺��
   }
   if (1) {
     if (BLUE == plateType) {
       adaptiveThreshold(auxRoi, roiAdap, 255, ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 3, 0);
-      //调用图像处理函数对图像进行自适应阈值处理。
+      //璋冪敤鍥惧儚澶勭悊鍑芥暟瀵瑰浘鍍忚繘琛岃嚜閫傚簲闃堝�煎鐞嗐��
     }
     else if (YELLOW == plateType) {
       adaptiveThreshold(auxRoi, roiAdap, 255, ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY_INV, 3, 0);
@@ -130,7 +130,7 @@ void CCharsSegment::judgeChinese(Mat in, Mat& out, Color plateType)
       adaptiveThreshold(auxRoi, roiAdap, 255, ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 3, 0);
     }
     roiAdap = preprocessChar(roiAdap);
-    //对二值化后的图像进行预处理字符操作。
+    //瀵逛簩鍊煎寲鍚庣殑鍥惧儚杩涜棰勫鐞嗗瓧绗︽搷浣溿��
     auto character = CharsIdentify::instance()->identifyChinese(roiAdap, valAdap, isChinese);
   }
 
@@ -146,20 +146,20 @@ void CCharsSegment::judgeChinese(Mat in, Mat& out, Color plateType)
 }
 
 void CCharsSegment::judgeChineseGray(Mat in, Mat& out, Color plateType) {
-  out = in;//复制输入图像
+  out = in;//澶嶅埗杈撳叆鍥惧儚
 }
 
 bool slideChineseWindow(Mat& image, Rect mr, Mat& newRoi, Color plateType, float slideLengthRatio, bool useAdapThreshold) {
   std::vector<CCharacter> charCandidateVec;
-  //用于存储候选的中文字符。
+  //鐢ㄤ簬瀛樺偍鍊欓�夌殑涓枃瀛楃銆�
   Rect maxrect = mr;
   Point tlPoint = mr.tl();
-  //获取mr的左上角点，并赋值给tlPoint
-  bool isChinese = true;//标记图像中是否含有中文字符
+  //鑾峰彇mr鐨勫乏涓婅鐐癸紝骞惰祴鍊肩粰tlPoint
+  bool isChinese = true;//鏍囪鍥惧儚涓槸鍚﹀惈鏈変腑鏂囧瓧绗�
   int slideLength = int(slideLengthRatio * maxrect.width);
-  int slideStep = 1;//控制滑动窗口的步长
-  int fromX = 0;//指定从哪个位置开始滑动窗口
-  fromX = tlPoint.x;//实际的起始位置是左上角的x坐标
+  int slideStep = 1;//鎺у埗婊戝姩绐楀彛鐨勬闀�
+  int fromX = 0;//鎸囧畾浠庡摢涓綅缃紑濮嬫粦鍔ㄧ獥鍙�
+  fromX = tlPoint.x;//瀹為檯鐨勮捣濮嬩綅缃槸宸︿笂瑙掔殑x鍧愭爣
 
   for (int slideX = -slideLength; slideX < slideLength; slideX += slideStep) {
     float x_slide = 0;
@@ -167,21 +167,21 @@ bool slideChineseWindow(Mat& image, Rect mr, Mat& newRoi, Color plateType, float
     x_slide = float(fromX + slideX);
 
     float y_slide = (float)tlPoint.y;
-    //用来计算滑动窗口的位置。
+    //鐢ㄦ潵璁＄畻婊戝姩绐楀彛鐨勪綅缃��
     Point2f p_slide(x_slide, y_slide);
 
     //cv::circle(image, p_slide, 2, Scalar(255), 1);
 
     int chineseWidth = int(maxrect.width);
     int chineseHeight = int(maxrect.height);
-    //宽度和高度
+    //瀹藉害鍜岄珮搴�
     Rect rect(Point2f(x_slide, y_slide), Size(chineseWidth, chineseHeight));
 
     if (rect.tl().x < 0 || rect.tl().y < 0 || rect.br().x >= image.cols || rect.br().y >= image.rows)
       continue;
-    //检查新定义的矩形区域是否在图像的边界内。如果超出了边界，就跳过这次循环。
+    //妫�鏌ユ柊瀹氫箟鐨勭煩褰㈠尯鍩熸槸鍚﹀湪鍥惧儚鐨勮竟鐣屽唴銆傚鏋滆秴鍑轰簡杈圭晫锛屽氨璺宠繃杩欐寰幆銆�
     Mat auxRoi = image(rect);
-    //原始图像中提取出这个矩形区域的子图像auxRoi
+    //鍘熷鍥惧儚涓彁鍙栧嚭杩欎釜鐭╁舰鍖哄煙鐨勫瓙鍥惧儚auxRoi
     Mat roiOstu, roiAdap;
     if (1) {
       if (BLUE == plateType) {
@@ -196,15 +196,15 @@ bool slideChineseWindow(Mat& image, Rect mr, Mat& newRoi, Color plateType, float
       else {
         threshold(auxRoi, roiOstu, 0, 255, CV_THRESH_OTSU + CV_THRESH_BINARY);
       }
-      //根据预设的颜色，使用不同的阈值处理方法对提取出的子图像进行阈值处理。
-      // 处理后的图像分别保存到roiOstu和roiAdap。
+      //鏍规嵁棰勮鐨勯鑹诧紝浣跨敤涓嶅悓鐨勯槇鍊煎鐞嗘柟娉曞鎻愬彇鍑虹殑瀛愬浘鍍忚繘琛岄槇鍊煎鐞嗐��
+      // 澶勭悊鍚庣殑鍥惧儚鍒嗗埆淇濆瓨鍒皉oiOstu鍜宺oiAdap銆�
       roiOstu = preprocessChar(roiOstu, kChineseSize);
 
       CCharacter charCandidateOstu; 
-      charCandidateOstu.setCharacterPos(rect); // 设置字符的位置信息
-      charCandidateOstu.setCharacterMat(roiOstu);// 设置字符的图像信息
-      charCandidateOstu.setIsChinese(isChinese);// 设置字符是否为中文字符的信息 
-      charCandidateVec.push_back(charCandidateOstu);// 将字符信息添加到字符候选向量中以备后续处理使用。
+      charCandidateOstu.setCharacterPos(rect); // 璁剧疆瀛楃鐨勪綅缃俊鎭�
+      charCandidateOstu.setCharacterMat(roiOstu);// 璁剧疆瀛楃鐨勫浘鍍忎俊鎭�
+      charCandidateOstu.setIsChinese(isChinese);// 璁剧疆瀛楃鏄惁涓轰腑鏂囧瓧绗︾殑淇℃伅 
+      charCandidateVec.push_back(charCandidateOstu);// 灏嗗瓧绗︿俊鎭坊鍔犲埌瀛楃鍊欓�夊悜閲忎腑浠ュ鍚庣画澶勭悊浣跨敤銆�
     }
     if (useAdapThreshold) {
       if (BLUE == plateType) {
@@ -220,7 +220,7 @@ bool slideChineseWindow(Mat& image, Rect mr, Mat& newRoi, Color plateType, float
         adaptiveThreshold(auxRoi, roiAdap, 255, ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 3, 0);
       }
       roiAdap = preprocessChar(roiAdap, kChineseSize);
-      //对图像进行阈值处理以获得二值化的图像。处理后的图像保存在roiAdap中。
+      //瀵瑰浘鍍忚繘琛岄槇鍊煎鐞嗕互鑾峰緱浜屽�煎寲鐨勫浘鍍忋�傚鐞嗗悗鐨勫浘鍍忎繚瀛樺湪roiAdap涓��
       CCharacter charCandidateAdap;
       charCandidateAdap.setCharacterPos(rect);
       charCandidateAdap.setCharacterMat(roiAdap);
@@ -234,8 +234,8 @@ bool slideChineseWindow(Mat& image, Rect mr, Mat& newRoi, Color plateType, float
 
   double overlapThresh = 0.1;
   NMStoCharacter(charCandidateVec, overlapThresh);
-  //使用了非极大值抑制（NMS）算法，它通过计算每个字符候选区域与其它所有字符候选区域的交并比
-  // 将交并比低于某个阈值的字符候选区域去除
+  //浣跨敤浜嗛潪鏋佸ぇ鍊兼姂鍒讹紙NMS锛夌畻娉曪紝瀹冮�氳繃璁＄畻姣忎釜瀛楃鍊欓�夊尯鍩熶笌鍏跺畠鎵�鏈夊瓧绗﹀�欓�夊尯鍩熺殑浜ゅ苟姣�
+  // 灏嗕氦骞舵瘮浣庝簬鏌愪釜闃堝�肩殑瀛楃鍊欓�夊尯鍩熷幓闄�
   if (charCandidateVec.size() >= 1) {
     std::sort(charCandidateVec.begin(), charCandidateVec.end(),
               [](const CCharacter& r1, const CCharacter& r2) {
@@ -245,60 +245,60 @@ bool slideChineseWindow(Mat& image, Rect mr, Mat& newRoi, Color plateType, float
     newRoi = charCandidateVec.at(0).getCharacterMat();
     return true;
   }
-  //如果生成的字符候选向量中至少有一个元素，
-  // 则将得分最高的字符候选区域的图像提取出来，并返回true；否则返回false。
+  //濡傛灉鐢熸垚鐨勫瓧绗﹀�欓�夊悜閲忎腑鑷冲皯鏈変竴涓厓绱狅紝
+  // 鍒欏皢寰楀垎鏈�楂樼殑瀛楃鍊欓�夊尯鍩熺殑鍥惧儚鎻愬彇鍑烘潵锛屽苟杩斿洖true锛涘惁鍒欒繑鍥瀎alse銆�
   return false;
 }
 
 bool slideChineseGrayWindow(const Mat& image, Rect& mr, Mat& newRoi, Color plateType, float slideLengthRatio) {
   std::vector<CCharacter> charCandidateVec;
-  // 定义一个向量来保存字符候选
+  // 瀹氫箟涓�涓悜閲忔潵淇濆瓨瀛楃鍊欓��
   Rect maxrect = mr;
   Point tlPoint = mr.tl();
-  // 获取给定的最大矩形区域的左上角点和宽度
+  // 鑾峰彇缁欏畾鐨勬渶澶х煩褰㈠尯鍩熺殑宸︿笂瑙掔偣鍜屽搴�
   bool isChinese = true;
-  // 默认假设它是中文字符
+  // 榛樿鍋囪瀹冩槸涓枃瀛楃
   int slideLength = int(slideLengthRatio * maxrect.width);
   int slideStep = 1;
   int fromX = 0;
   fromX = tlPoint.x;
-  // 根据最大矩形的宽度计算滑动窗口的长度和步长
+  // 鏍规嵁鏈�澶х煩褰㈢殑瀹藉害璁＄畻婊戝姩绐楀彛鐨勯暱搴﹀拰姝ラ暱
   for (int slideX = -slideLength; slideX < slideLength; slideX += slideStep) {
-    // 在指定的范围内进行滑动窗口操作
+    // 鍦ㄦ寚瀹氱殑鑼冨洿鍐呰繘琛屾粦鍔ㄧ獥鍙ｆ搷浣�
     float x_slide = 0;
     x_slide = float(fromX + slideX);
 
     float y_slide = (float)tlPoint.y;
-    // 计算当前滑动的x和y坐标
+    // 璁＄畻褰撳墠婊戝姩鐨剎鍜寉鍧愭爣
     int chineseWidth = int(maxrect.width);
     int chineseHeight = int(maxrect.height);
-    // 获取中国字符的宽度和高度 
+    // 鑾峰彇涓浗瀛楃鐨勫搴﹀拰楂樺害 
     Rect rect(Point2f(x_slide, y_slide), Size(chineseWidth, chineseHeight));
-    // 根据当前滑动的坐标和中国字符的尺寸创建一个矩形区域
+    // 鏍规嵁褰撳墠婊戝姩鐨勫潗鏍囧拰涓浗瀛楃鐨勫昂瀵稿垱寤轰竴涓煩褰㈠尯鍩�
     if (rect.tl().x < 0 || rect.tl().y < 0 || rect.br().x >= image.cols || rect.br().y >= image.rows)
       continue;
-    // 检查这个矩形是否在图像内，如果不在，则跳过当前的循环迭代  
+    // 妫�鏌ヨ繖涓煩褰㈡槸鍚﹀湪鍥惧儚鍐咃紝濡傛灉涓嶅湪锛屽垯璺宠繃褰撳墠鐨勫惊鐜凯浠�  
     Mat auxRoi = image(rect);
     Mat grayChinese;
     grayChinese.create(kGrayCharHeight, kGrayCharWidth, CV_8UC1);
-    // 创建一个灰度图像，尺寸为预设的中文字符的尺寸和通道数  
+    // 鍒涘缓涓�涓伆搴﹀浘鍍忥紝灏哄涓洪璁剧殑涓枃瀛楃鐨勫昂瀵稿拰閫氶亾鏁�  
     resize(auxRoi, grayChinese, grayChinese.size(), 0, 0, INTER_LINEAR);
-    // 将提取的子图像调整为预设的中文字符的尺寸，并将其保存到灰度图像中
-    // 从图像中提取当前矩形区域的子图像
+    // 灏嗘彁鍙栫殑瀛愬浘鍍忚皟鏁翠负棰勮鐨勪腑鏂囧瓧绗︾殑灏哄锛屽苟灏嗗叾淇濆瓨鍒扮伆搴﹀浘鍍忎腑
+    // 浠庡浘鍍忎腑鎻愬彇褰撳墠鐭╁舰鍖哄煙鐨勫瓙鍥惧儚
     CCharacter charCandidateOstu;
     charCandidateOstu.setCharacterPos(rect);
     charCandidateOstu.setCharacterMat(grayChinese);
     charCandidateOstu.setIsChinese(isChinese);
-    charCandidateVec.push_back(charCandidateOstu);// 将字符候选对象添加到向量中以备后续处理使用  
-    // 创建一个字符候选对象，并设置其位置、图像和其他属性（这里指定为中文字符）  
+    charCandidateVec.push_back(charCandidateOstu);// 灏嗗瓧绗﹀�欓�夊璞℃坊鍔犲埌鍚戦噺涓互澶囧悗缁鐞嗕娇鐢�  
+    // 鍒涘缓涓�涓瓧绗﹀�欓�夊璞★紝骞惰缃叾浣嶇疆銆佸浘鍍忓拰鍏朵粬灞炴�э紙杩欓噷鎸囧畾涓轰腑鏂囧瓧绗︼級  
   }
 
   CharsIdentify::instance()->classifyChineseGray(charCandidateVec);
-  // 对所有的字符候选进行分类（这里假设是中文字符分类）
+  // 瀵规墍鏈夌殑瀛楃鍊欓�夎繘琛屽垎绫伙紙杩欓噷鍋囪鏄腑鏂囧瓧绗﹀垎绫伙級
   double overlapThresh = 0.1;
   NMStoCharacter(charCandidateVec, overlapThresh);
-  // 对所有的字符候选进行非极大值抑制（NMS）以消除多余的字符候选区域，
-  // 这里的阈值设置为0.1（根据实际情况可能需要进行调整）  
+  // 瀵规墍鏈夌殑瀛楃鍊欓�夎繘琛岄潪鏋佸ぇ鍊兼姂鍒讹紙NMS锛変互娑堥櫎澶氫綑鐨勫瓧绗﹀�欓�夊尯鍩燂紝
+  // 杩欓噷鐨勯槇鍊艰缃负0.1锛堟牴鎹疄闄呮儏鍐靛彲鑳介渶瑕佽繘琛岃皟鏁达級  
   if (charCandidateVec.size() >= 1) {
     std::sort(charCandidateVec.begin(), charCandidateVec.end(),
               [](const CCharacter& r1, const CCharacter& r2) {
@@ -309,23 +309,23 @@ bool slideChineseGrayWindow(const Mat& image, Rect& mr, Mat& newRoi, Color plate
     mr = charCandidateVec.at(0).getCharacterPos();
     return true;
   }
-  // 如果字符候选向量中至少有一个元素，则对它们进行排序，
-  // 并提取出得分最高的字符候选区域，将其图像保存到newRoi中，
-  // 并更新mr为最高得分字符候选的位置，然后返回true；否则返回false。
-  // 注意这里使用了一个lambda表达式作为排序函数，
-  // 根据字符候选的得分进行降序排序。
+  // 濡傛灉瀛楃鍊欓�夊悜閲忎腑鑷冲皯鏈変竴涓厓绱狅紝鍒欏瀹冧滑杩涜鎺掑簭锛�
+  // 骞舵彁鍙栧嚭寰楀垎鏈�楂樼殑瀛楃鍊欓�夊尯鍩燂紝灏嗗叾鍥惧儚淇濆瓨鍒皀ewRoi涓紝
+  // 骞舵洿鏂癿r涓烘渶楂樺緱鍒嗗瓧绗﹀�欓�夌殑浣嶇疆锛岀劧鍚庤繑鍥瀟rue锛涘惁鍒欒繑鍥瀎alse銆�
+  // 娉ㄦ剰杩欓噷浣跨敤浜嗕竴涓猯ambda琛ㄨ揪寮忎綔涓烘帓搴忓嚱鏁帮紝
+  // 鏍规嵁瀛楃鍊欓�夌殑寰楀垎杩涜闄嶅簭鎺掑簭銆�
   return false;
 }
 
 
 int CCharsSegment::charsSegment(Mat input, vector<Mat>& resultVec, Color color) {
   if (!input.data) return 0x01;
-
+  //妫�鏌ヨ緭鍏ュ浘鍍忔槸鍚︽湁鏁版嵁
   Color plateType = color;
 
-  Mat input_grey;
+  Mat input_grey; //瀛樺偍鐏板害鍥惧儚銆�
   cvtColor(input, input_grey, CV_BGR2GRAY);
-
+  //灏嗚緭鍏ュ浘鍍忚浆鎹负鐏板害鍥惧儚锛屽苟淇濆瓨鍒癷nput_grey涓��
   if (0) {
     imshow("plate", input_grey);
     waitKey(0);
@@ -336,6 +336,7 @@ int CCharsSegment::charsSegment(Mat input, vector<Mat>& resultVec, Color color)
 
   img_threshold = input_grey.clone();
   spatial_ostu(img_threshold, 8, 2, plateType);
+  //瀵瑰浘鍍忚繘琛孫tsu闃堝�煎垎鍓�
 
   if (0) {
     imshow("plate", img_threshold);
@@ -346,23 +347,28 @@ int CCharsSegment::charsSegment(Mat input, vector<Mat>& resultVec, Color color)
   // remove liuding and hor lines
   // also judge weather is plate use jump count
   if (!clearLiuDing(img_threshold)) return 0x02;
-
+  //娓呴櫎鍥惧儚涓殑涓�浜涙棤鏁堝尯鍩�
   Mat img_contours;
   img_threshold.copyTo(img_contours);
-
+  //灏唅mg_threshold澶嶅埗鍒癷mg_contours涓��
   vector<vector<Point> > contours;
+  //瀹氫箟涓�涓簩缁村悜閲廲ontours锛岀敤浜庝繚瀛樿疆寤撲俊鎭��
   findContours(img_contours,
                contours,               // a vector of contours
                CV_RETR_EXTERNAL,       // retrieve the external contours
                CV_CHAIN_APPROX_NONE);  // all pixels of each contours
-
+  //浣跨敤OpenCV鐨刦indContours鍑芥暟鏌ユ壘鍥惧儚涓殑杞粨銆�
+  // 杩欓噷鎸囧畾浜嗘绱㈡ā寮忎负澶栭儴杞粨锛屽苟涓旀寚瀹氫簡杞粨鐨勮繎浼兼柟娉曘��
   vector<vector<Point> >::iterator itc = contours.begin();
+  //瀹氫箟涓�涓凯浠ｅ櫒itc锛屽苟鍒濆鍖栦负杞粨鍚戦噺鐨勮捣濮嬩綅缃�
   vector<Rect> vecRect;
-
-  while (itc != contours.end()) {
+  //瀹氫箟涓�涓悜閲弙ecRect锛岀敤浜庝繚瀛樻瘡涓疆寤撶殑杈圭晫妗嗐��
+  while (itc != contours.end()) {//閬嶅巻杞粨鍚戦噺
     Rect mr = boundingRect(Mat(*itc));
+    //瀵逛簬褰撳墠杞粨锛屼娇鐢∣penCV鐨刡oundingRect鍑芥暟璁＄畻鍏惰竟鐣屾锛�
+    // 骞朵繚瀛樺埌鍙橀噺mr涓��
     Mat auxRoi(img_threshold, mr);
-
+    //鏍规嵁褰撳墠杞粨鐨勮竟鐣屾锛屼粠鍥惧儚涓彁鍙栦竴涓瓙鍥惧儚銆�
     if (verifyCharSizes(auxRoi)) vecRect.push_back(mr);
     ++itc;
   }
@@ -371,16 +377,18 @@ int CCharsSegment::charsSegment(Mat input, vector<Mat>& resultVec, Color color)
   if (vecRect.size() == 0) return 0x03;
 
   vector<Rect> sortedRect(vecRect);
+  //鍒涘缓涓�涓柊鐨勫悜閲弒ortedRect锛屽苟灏唙ecRect鐨勫唴瀹瑰鍒跺埌杩欎釜鏂扮殑鍚戦噺涓��
   std::sort(sortedRect.begin(), sortedRect.end(),
             [](const Rect& r1, const Rect& r2) { return r1.x < r2.x; });
-
+  //浣跨敤lambda鍑芥暟灏唖ortedRect鎸夌収x鍧愭爣浠庡皬鍒板ぇ杩涜鎺掑簭銆�
   size_t specIndex = 0;
 
   specIndex = GetSpecificRect(sortedRect);
-
+  //鑾峰彇鐗瑰畾鐨勭煩褰�
   Rect chineseRect;
   if (specIndex < sortedRect.size())
     chineseRect = GetChineseRect(sortedRect[specIndex]);
+    //鑾峰彇鐗瑰畾绱㈠紩鐨勭煩褰㈠苟瀛樺偍鍒癱hineseRect
   else
     return 0x04;
 
@@ -390,11 +398,13 @@ int CCharsSegment::charsSegment(Mat input, vector<Mat>& resultVec, Color color)
     waitKey(0);
     destroyWindow("plate");
   }
+  //缁樺埗鐭╁舰chineseRect鍦ㄥ浘鍍忎笂骞舵樉绀哄嚭鏉�
+  //杩欓儴鍒嗕唬鐮佹案杩滀笉浼氳鎵ц
 
   vector<Rect> newSortedRect;
   newSortedRect.push_back(chineseRect);
   RebuildRect(sortedRect, newSortedRect, specIndex);
-
+  //瀵瑰浘鍍忎腑鐨勭煩褰㈠尯鍩熻繘琛岄噸鏂版瀯寤烘垨澶勭悊鐨勩��
   if (newSortedRect.size() == 0) return 0x05;
 
   bool useSlideWindow = true;
@@ -402,12 +412,14 @@ int CCharsSegment::charsSegment(Mat input, vector<Mat>& resultVec, Color color)
   //bool useAdapThreshold = CParams::instance()->getParam1b();
 
   for (size_t i = 0; i < newSortedRect.size(); i++) {
+      //寰幆閬嶅巻鏂扮殑鎺掑簭鐭╁舰鍚戦噺涓殑姣忎竴涓煩褰€��
     Rect mr = newSortedRect[i];
-
+    //鑾峰彇褰撳墠鐭╁舰鐨勫潗鏍囦俊鎭�
     // Mat auxRoi(img_threshold, mr);
     Mat auxRoi(input_grey, mr);
+    //鏍规嵁缁欏畾鐨勫浘鍍忓拰鐭╁舰鍖哄煙鍒涘缓ROI
     Mat newRoi;
-
+    //绗簩涓槸鐢ㄦ潵瀛樺偍澶勭悊鍚庣殑鍥惧儚鐨勩��
     if (i == 0) {
       if (useSlideWindow) {
         float slideLengthRatio = 0.1f;
@@ -431,15 +443,24 @@ int CCharsSegment::charsSegment(Mat input, vector<Mat>& resultVec, Color color)
       else {
         threshold(auxRoi, newRoi, 0, 255, CV_THRESH_OTSU + CV_THRESH_BINARY);
       }
-
+      //鏍规嵁涓嶅悓鐨勯鑹叉潵鎵ц涓嶅悓鐨勯槇鍊煎鐞嗘搷浣滐紝
+      // 鐒跺悗瀵瑰鐞嗗悗鐨勫浘鍍忚繘琛岄澶�
       newRoi = preprocessChar(newRoi);
     }
 
     if (0) {
       if (i == 0) {
         imshow("input_grey", input_grey);
+        // 浣跨敤imshow鍑芥暟鏄剧ず鍚嶄负"input_grey"鐨勭獥鍙ｏ紝骞跺湪鍏朵腑鏄剧ず鍥惧儚"input_grey"銆�
+        // 鐢ㄤ簬鍒涘缓鍜屾樉绀虹獥鍙ｃ��
+
         waitKey(0);
+        //杩欐槸璋冪敤OpenCV鐨剋aitKey鍑芥暟锛岀瓑寰呯敤鎴锋寜閿��
+        // 璇ュ嚱鏁扮殑鍙傛暟鏄�0锛岃繖鎰忓懗鐫�瀹冨皢鏃犻檺鏈熷湴绛夊緟鐢ㄦ埛鎸夐敭銆�
+        // 涓�鏃︾敤鎴锋寜涓嬮敭锛岃鍑芥暟灏嗚繑鍥炴寜涓嬬殑閿殑ASCII鍊笺��
+
         destroyWindow("input_grey");
+        //杩欎釜鍑芥暟浼氶攢姣佺獥鍙ｅ苟閲婃斁鍏跺唴瀛樸��
       }
       if (i == 0) {
         imshow("newRoi", newRoi);
@@ -449,6 +470,9 @@ int CCharsSegment::charsSegment(Mat input, vector<Mat>& resultVec, Color color)
     }
 
     resultVec.push_back(newRoi);
+    // 灏嗘柊鐨凴oi娣诲姞鍒板悕涓簉esultVec鐨勫悜閲忎腑銆�
+    // 瀛樺偍涓�绯诲垪鍏冪礌銆傝繖閲屽皢鏂扮殑Roi鍥惧儚娣诲姞鍒拌鍚戦噺涓��
+
   }
 
   return 0;
@@ -457,44 +481,53 @@ int CCharsSegment::charsSegment(Mat input, vector<Mat>& resultVec, Color color)
 int CCharsSegment::projectSegment(const Mat& input, Color color, vector<int>& out_indexs) {
   if (!input.data) return 0x01;
 
-  Color plateType = color;
-  Mat input_grey;
-  cvtColor(input, input_grey, CV_BGR2GRAY);
-  SHOW_IMAGE(input_grey, 0);
+  Color plateType = color;  // 灏嗚緭鍏ョ殑棰滆壊璧嬪�肩粰plateType
+  Mat input_grey;  // 瀹氫箟涓�涓狹at瀵硅薄鐢ㄤ簬瀛樺偍鐏板害鍥惧儚  
+  cvtColor(input, input_grey, CV_BGR2GRAY);  // 灏嗚緭鍏ュ浘鍍忚浆鎹负鐏板害鍥惧儚  
+  SHOW_IMAGE(input_grey, 0);  // 鏄剧ず鐏板害鍥惧儚  
 
-  Mat img_threshold;
-  img_threshold = input_grey.clone();
-  spatial_ostu(img_threshold, 8, 2, plateType);
-  SHOW_IMAGE(img_threshold, 0);
+  Mat img_threshold;  // 瀹氫箟涓�涓狹at瀵硅薄鐢ㄤ簬瀛樺偍闃堝�煎寲鐨勫浘鍍�  
+  img_threshold = input_grey.clone();  // 灏嗙伆搴﹀浘鍍忓鍒跺埌img_threshold涓�  
+  spatial_ostu(img_threshold, 8, 2, plateType);  // 瀵瑰浘鍍忚繘琛岀┖闂磋嚜閫傚簲闃堝�煎寲澶勭悊锛�
+  SHOW_IMAGE(img_threshold, 0);  // 鏄剧ず闃堝�煎寲鍚庣殑鍥惧儚  
 
   // remove liuding and hor lines
   // also judge weather is plate use jump count
-  if (!clearLiuDing(img_threshold)) return 0x02;
-  SHOW_IMAGE(img_threshold, 0);
-
-  Mat vhist = ProjectedHistogram(img_threshold, VERTICAL, 0);
-  Mat showHist = showHistogram(vhist);
-  SHOW_IMAGE(showHist, 1);
-
-  vector<float> values;
-  vector<int> indexs;
-  int size = vhist.cols;
-  for (int i = 0; i < size; i++) {
-    float val = vhist.at<float>(i);
-    values.push_back(1.f - val);
+ // 杩涜涓�浜涘舰鐘剁殑娓呯悊鍜屽垽鏂槸鍚︿负杞︾墝鐨勮烦璺冭鏁�
+  if (!clearLiuDing(img_threshold)) return 0x02; 
+  // 浣跨敤clearLiuDing鍑芥暟娓呯悊鍥惧儚涓殑澶氫綑閮ㄥ垎锛�
+  SHOW_IMAGE(img_threshold, 0); 
+  // 鏄剧ず娓呯悊鍚庣殑鍥惧儚  
+
+  Mat vhist = ProjectedHistogram(img_threshold, VERTICAL, 0);  
+  // 瀵瑰浘鍍忚繘琛屽瀭鐩寸洿鏂瑰浘鎶曞奖锛岀粨鏋滀繚瀛樺湪vhist涓�  
+  Mat showHist = showHistogram(vhist);  
+  // 鏄剧ず鐩存柟鍥撅紝浣嗘槸姝よ浠ｇ爜鍦ㄥ悗缁殑浠ｇ爜涓苟娌℃湁琚娇鐢�  
+  SHOW_IMAGE(showHist, 1);  // 鏄剧ず鐩存柟鍥�
+
+  vector<float> values;  // 瀹氫箟涓�涓悜閲忕敤浜庡瓨鍌ㄦ瘡涓儚绱犲埌鐩存柟鍥炬渶澶у�肩殑璺濈  
+  vector<int> indexs;  // 瀹氫箟涓�涓悜閲忕敤浜庡瓨鍌ㄩ潪鏈�澶у�肩殑绱㈠紩  
+  int size = vhist.cols;  // 鑾峰彇鐩存柟鍥惧垪鐨勬暟閲忥紝浣滀负鍚庣画寰幆鐨勬鏁�  
+
+  for (int i = 0; i < size; i++) {  // 閬嶅巻姣忎釜鍍忕礌鍦ㄧ洿鏂瑰浘涓殑浣嶇疆  
+      float val = vhist.at<float>(i);  // 鑾峰彇褰撳墠鍍忕礌鍦ㄧ洿鏂瑰浘涓殑鍊�  
+      values.push_back(1.f - val);  
+      // 璁＄畻褰撳墠鍍忕礌鍒扮洿鏂瑰浘鏈�澶у�肩殑璺濈锛屽苟娣诲姞鍒皏alues鍚戦噺涓�  
   }
-  Mat img_test = img_threshold.clone();
-  NMSfor1D<float>(values, indexs);
-
-  out_indexs.resize(size);
-  for (int j = 0; j < size; j++)
-    out_indexs.at(j) = 0;
-  for (int i = 0; i < size; i++) {
-    float val = vhist.at<float>(i);
-    if (indexs.at(i) && val < 0.1f) {
-      out_indexs.at(i) = 1;
+  Mat img_test = img_threshold.clone();  // 澶嶅埗闃堝�煎寲鍚庣殑鍥惧儚鍒颁竴涓柊鐨凪at瀵硅薄涓�  
+  NMSfor1D<float>(values, indexs);  // 瀵箆alues鍚戦噺杩涜闈炴瀬澶у�兼姂鍒讹紙NMS锛�  
+
+  out_indexs.resize(size);  // 閲嶆柊璋冩暣out_indexs鍚戦噺鐨勫昂瀵革紝涓哄悗缁殑璧嬪�煎仛鍑嗗  
+  for (int j = 0; j < size; j++) 
+      out_indexs.at(j) = 0;  // 灏唎ut_indexs鍚戦噺涓殑鎵�鏈夊�煎垵濮嬪寲涓�0  
+
+ for (int i = 0; i < size; i++) {  // 閬嶅巻姣忎釜鍍忕礌鍦ㄧ洿鏂瑰浘涓殑浣嶇疆  
+    float val = vhist.at<float>(i);  // 鑾峰彇褰撳墠鍍忕礌鍦ㄧ洿鏂瑰浘涓殑鍊�  
+    if (indexs.at(i) && val < 0.1f) {  // 濡傛灉褰撳墠鍍忕礌鏄潪鏋佸ぇ鍊间笖鍏跺�煎皬浜�0.1f  
+      out_indexs.at(i) = 1;  // 鍒欏皢out_indexs鍚戦噺涓殑鐩稿簲浣嶇疆璁剧疆涓�1  
       for (int j = 0; j < img_test.rows; j++) {
         img_test.at<char>(j, i) = (char)255;
+        // 灏嗚浣嶇疆鐨勫儚绱犲�艰缃负255锛堢櫧鑹诧級
       }
     }
   }
@@ -506,72 +539,106 @@ int CCharsSegment::projectSegment(const Mat& input, Color color, vector<int>& ou
 bool verifyCharRectSizes(Rect r) {
   // Char sizes 45x90
   float aspect = 45.0f / 90.0f;
+  //瀹氫箟涓�涓彉閲廰spect锛屽叾鍊间负0.5锛岃〃绀哄瓧绗︾殑棰勬湡瀹介珮姣斻��
   float charAspect = (float)r.width / (float)r.height;
+  //璁＄畻杈撳叆鐭╁舰鐨勫楂樻瘮锛屽苟灏嗗叾瀛樺偍鍦ㄥ彉閲廲harAspect涓��
   float error = 0.5f;
+  //琛ㄧず鍏佽鐨勫楂樻瘮璇樊銆�
   float minHeight = kPlateResizeHeight * 0.5f;
+  //琛ㄧず鐭╁舰鐨勬渶灏忛珮搴�
   float maxHeight = kPlateResizeHeight * 1.f;
+  //琛ㄧず鐭╁舰鐨勬渶澶ч珮搴�
   // We have a different aspect ratio for number 1, and it can be ~0.2
   float minAspect = 0.10f; //0.2f;
-
+  //琛ㄧず鍏佽鐨勬渶灏忓楂樻瘮
   float maxAspect = 0.85f; // aspect + aspect * error; //0.8f;
-
+  //琛ㄧず鍏佽鐨勬渶澶у楂樻瘮
   int ch = r.tl().y + r.height / 2;
+  //璁＄畻鐭╁舰鐨勪腑蹇冪偣绾靛潗鏍�
   int min_ch = int(kPlateResizeHeight * 0.3f);
+  //琛ㄧず瀛楃涓績鐐圭殑鏈�灏忕旱鍧愭爣
   int max_ch = int(kPlateResizeHeight * 0.7f);
+  //琛ㄧず瀛楃涓績鐐圭殑鏈�澶х旱鍧愭爣
   if (ch > max_ch || ch < min_ch)
    return false;
-
+  //濡傛灉瀛楃涓績鐐圭殑绾靛潗鏍囪秴鍑哄厑璁哥殑鑼冨洿锛屽垯杩斿洖false銆�
   float h = (float)r.height;
+  //灏嗚緭鍏ョ煩褰㈢殑height杞崲涓烘诞鐐规暟
   if (h > maxHeight || h < minHeight)
     return false;
+  //鐭╁舰鐨刪eight瓒呭嚭鍏佽鐨勮寖鍥达紝鍒欒繑鍥瀎alse銆�
   if (charAspect < minAspect || charAspect > maxAspect)
     return false;
-
+  //濡傛灉鐭╁舰鐨勫楂樻瘮瓒呭嚭鍏佽鐨勮寖鍥达紝鍒欒繑鍥瀎alse銆�
   return true;
 }
 
 Mat preprocessCharMat(Mat in, int char_size) {
   // Remap image
-  int h = in.rows;
-  int w = in.cols;
+    // 瀵瑰浘鍍忚繘琛屾槧灏勫彉鎹�  
+    int h = in.rows; // 鑾峰彇杈撳叆鍥惧儚鐨勮鏁�  
+    int w = in.cols; // 鑾峰彇杈撳叆鍥惧儚鐨勫垪鏁�  
 
-  int charSize = char_size;
+    int charSize = char_size; // 灏嗕紶鍏ョ殑瀛楃澶у皬鍙傛暟淇濆瓨涓篶harSize  
 
-  Mat transformMat = Mat::eye(2, 3, CV_32F);
-  int m = max(w, h);
-  transformMat.at<float>(0, 2) = float(m / 2 - w / 2);
-  transformMat.at<float>(1, 2) = float(m / 2 - h / 2);
+    // 鍒涘缓涓�涓�2x3鐨勫崟浣嶇煩闃碉紝浣滀负鍥惧儚鍙樻崲鐨勮浆鎹㈢煩闃�  
+    Mat transformMat = Mat::eye(2, 3, CV_32F);
 
-  Mat warpImage(m, m, in.type());
-  warpAffine(in, warpImage, transformMat, warpImage.size(), INTER_LINEAR,
-             BORDER_CONSTANT, Scalar(0));
+    // 鎵惧嚭杈撳叆鍥惧儚鐨勬渶澶у昂瀵革紙楂樻垨瀹斤級  
+    int m = max(w, h);
 
-  Mat out;
-  cv::resize(warpImage, out, Size(charSize, charSize));
+    // 鏍规嵁鏈�澶у昂瀵革紝璁剧疆杞崲鐭╅樀鐨勬渶鍚庝袱琛岋紙骞崇Щ鍙傛暟锛�  
+    // 杩欐牱鍋氱殑鐩殑鏄皢杈撳叆鍥惧儚鐨勪腑蹇冪Щ鍔ㄥ埌鍙樻崲鍚庣殑鍥惧儚鐨勪腑蹇�  
+    transformMat.at<float>(0, 2) = float(m / 2 - w / 2);
+    transformMat.at<float>(1, 2) = float(m / 2 - h / 2);
 
-  return out;
+    // 鍒涘缓涓�涓笌杈撳叆鍥惧儚鐩稿悓绫诲瀷鍜屽ぇ灏忕殑杈撳嚭鍥惧儚  
+    Mat warpImage(m, m, in.type());
+
+    // 浣跨敤涓婇潰瀹氫箟鐨勮浆鎹㈢煩闃碉紝瀵硅緭鍏ュ浘鍍忔墽琛屼豢灏勫彉鎹紙warpAffine锛�  
+    warpAffine(in, warpImage, transformMat, warpImage.size(), INTER_LINEAR,
+        BORDER_CONSTANT, Scalar(0));
+
+    // 鏍规嵁鎸囧畾鐨勫瓧绗﹀ぇ灏忥紝璋冩暣鍙樻崲鍚庣殑鍥惧儚澶у皬  
+    Mat out;
+    cv::resize(warpImage, out, Size(charSize, charSize));
+
+    // 杩斿洖澶勭悊鍚庣殑鍥惧儚  
+    return out;
 }
 
 Mat clearLiuDingAndBorder(const Mat& grayImage, Color color) {
   SHOW_IMAGE(grayImage, 0);
+  //鏄剧ず杈撳叆鐨勭伆搴﹀浘鍍�
   Mat img_threshold;
+  //瀹氫箟涓�涓狹at瀵硅薄img_threshold锛岀敤浜庡瓨鏀鹃槇鍊煎寲鍚庣殑鍥惧儚銆�
   img_threshold = grayImage.clone();
+  //灏嗚緭鍏ョ殑鐏板害鍥惧儚澶嶅埗鍒癷mg_threshold涓��
   spatial_ostu(img_threshold, 1, 1, color);
+  //瀵瑰浘鍍忚繘琛岀┖闂磋嚜閫傚簲闃堝�煎寲锛坰patial OSTU锛夛紝
+  // 杩欓噷鐨勫弬鏁�1鍜�1鍙兘琛ㄧず鐨勬槸楂樻柉鏍哥殑澶у皬锛岃�宑olor鍒欒〃绀洪鑹茬┖闂淬��
   clearLiuDing(img_threshold);
+  //涓轰簡鍘婚櫎鍒樺畾鍣０
   Rect cropRect;
+  //瀛樻斁瑁佸壀鍖哄煙鐨勫潗鏍囥��
   clearBorder(img_threshold, cropRect);
+  //涓轰簡娓呴櫎鍥惧儚鐨勮竟妗�
   Mat cropedGrayImage;
+  //瀛樻斁瑁佸壀鍚庣殑鐏板害鍥惧儚
   resize(grayImage(cropRect), cropedGrayImage, Size(kPlateResizeWidth, kPlateResizeHeight));
+  //瀵硅鍓悗鐨勭伆搴﹀浘鍍忚繘琛屽ぇ灏忚皟鏁淬��
   SHOW_IMAGE(cropedGrayImage, 0);
+  //鏄剧ず璋冩暣澶у皬鍚庣殑鐏板害鍥惧儚銆�
   return cropedGrayImage;
+  //杩斿洖澶勭悊鍚庣殑鐏板害鍥惧儚銆�
 }
 
 void NMStoCharacterByRatio(std::vector<CCharacter> &inVec, double overlap, const Rect groundRect) {
   // rechange the score
-  for (auto& character : inVec) {
-    double score = character.getCharacterScore();
+  for (auto& character : inVec) {//瀵筰nVec涓殑姣忎釜瀛楃杩涜鎿嶄綔
+    double score = character.getCharacterScore();//鑾峰彇褰撳墠瀛楃鐨勫緱鍒�
     //cout << "score:" << score << endl;
-    Rect rect = character.getCharacterPos();
+    Rect rect = character.getCharacterPos();//鑾峰彇褰撳墠瀛楃鐨勪綅缃俊鎭�
     int w = rect.width;
     int h = rect.height;
     int gw = groundRect.width;
@@ -581,13 +648,14 @@ void NMStoCharacterByRatio(std::vector<CCharacter> &inVec, double overlap, const
 
     int w_diff = abs(w - gw);
     int h_diff = abs(h - gh);
-
+    //璁＄畻褰撳墠瀛楃妗嗕笌鍦伴潰鐪熷疄妗嗙殑IOU锛堜氦骞舵瘮锛�
     //float w_ratio = (float)w / (float)gw;
     //float h_ratio = (float)h / (float)gh;
 
     float w_ratio = 1 - (float)w_diff / (float)gw;
     float h_ratio = 1 - (float)h_diff / (float)gh;
-
+    //鍒嗗埆琛ㄧず瀛楃妗嗙殑瀹藉害鍜岄珮搴︿笌鍦伴潰鐪熷疄妗嗙殑瀹介珮姣斻��
+    // 杩欎袱涓瘮渚嬩細褰卞搷鏈�缁堢殑鏉冮噸寰楀垎銆�
     float a = 0.5f;
     float b = 0.5f;
     //cout << "str:" << character.getCharacterStr() << endl;
@@ -595,17 +663,20 @@ void NMStoCharacterByRatio(std::vector<CCharacter> &inVec, double overlap, const
     if ("1" == character.getCharacterStr()) {
       a = 0.3f; //0.2f;
       b = 0.7f; //0.8f;
+      //濡傛灉瀛楃鏄�'1'锛岄偅涔堜細瀵瑰叾IOU杩涜涓�涓皟鏁淬��
     }
     float c = 0.1f;
     //float weighted_score = a * (float)score + b * w_ratio + c * h_ratio;
     float weighted_score = a * (float)score + b * w_ratio + c * h_ratio;
+    //璁＄畻鏉冮噸寰楀垎
     SHOW_IMAGE(character.getCharacterMat(), 0);
     character.setCharacterScore((double)weighted_score);
+    //璁剧疆鏂扮殑鏉冮噸寰楀垎銆�
     //cout << "weighted_score:" << character.getCharacterScore() << endl;
   }
 
   std::sort(inVec.begin(), inVec.end());
-
+  //瀵箆ector杩涜鎺掑簭锛屼互渚垮悗缁殑NMS鎿嶄綔銆�
   std::vector<CCharacter>::iterator it = inVec.begin();
   for (; it != inVec.end(); ++it) {
     CCharacter charSrc = *it;
@@ -625,20 +696,26 @@ void NMStoCharacterByRatio(std::vector<CCharacter> &inVec, double overlap, const
         ++itc;
       }
     }
-  }
+  }//濡傛灉瀹冧笌鍚庨潰鐨勫瓧绗︾殑IOU澶т簬棰勮鐨勯噸鍙犻槇鍊硷紝閭ｄ箞灏卞皢鍚庨潰鐨勫瓧绗︿粠vector涓垹闄ゃ��
+  //杩欐牱鍙互淇濊瘉鏈�缁坴ector涓瘡涓�涓瓧绗﹂兘涓嶄笌鍏跺畠瀛楃鏈夊ぇ鐨勯噸鍙�
 }
 
 int getNearestIndex(Point center, const vector<Point>& groundCenters) {
   int gc_size = int(groundCenters.size());
+  //鑾峰彇 groundCenters 鍚戦噺鐨勫ぇ灏忥紝骞跺皢鍏惰浆鎹负鏁存暟绫诲瀷骞跺瓨鍌ㄥ湪鍙橀噺 gc_size 涓�
   int index = 0;
+  //鐢ㄤ簬瀛樺偍鏈�鎺ヨ繎 center 鐨勫湴蹇冨潗鏍囩殑绱㈠紩
   int min_length = INT_MAX;
-  for (int p = 0; p < gc_size; p++) {
-    Point gc_point = groundCenters.at(p);
+  //鐢ㄤ簬瀛樺偍涓� center 璺濈鏈�鐭殑鍦板績鍧愭爣鐨勮窛绂荤殑骞虫柟
+  for (int p = 0; p < gc_size; p++) {//閬嶅巻鎵�鏈夊湴蹇冨潗鏍�
+    Point gc_point = groundCenters.at(p);//鑾峰彇绱㈠紩涓� p 鐨勫湴蹇冨潗鏍囷紝骞跺皢鍏跺瓨鍌ㄥ湪鍙橀噺 gc_point 涓��
      int length_square = (gc_point.x - center.x) * (gc_point.x - center.x) +
        (gc_point.y - center.y) * (gc_point.y - center.y);
+     //璁＄畻褰撳墠鍦板績鍧愭爣 gc_point 涓� center 涔嬮棿鐨勮窛绂荤殑骞虫柟銆�
     //int length_square = abs(gc_point.x - center.x);
     if (length_square < min_length) {
       min_length = length_square;
+      //褰撳墠鍦板績鍧愭爣涓� center 鐨勮窛绂荤殑骞虫柟璁剧疆涓烘柊鐨勬渶灏忚窛绂汇��
       index = p;
     }
   }