a little modify

.gitignore

@@ -14,6 +14,7 @@ Thumbs.db
 [Rr]elease/
 [Rr]eleases/
 experiment/
+experi/
 bak/
 x64/
 x86/

src/core/plate_judge.cpp

@@ -77,7 +77,7 @@ int CPlateJudge::plateJudge(const vector<Mat>& inVec,
 	for (int j = 0; j < num; j++)
 	{
 		Mat inMat = inVec[j];
-
+		
 		int response = -1;
 		plateJudge(inMat, response);
 

src/core/plate_locate.cpp

@@ -89,6 +89,7 @@ bool CPlateLocate::verifySizes(RotatedRect mr)
 Mat CPlateLocate::showResultMat(Mat src, Size rect_size, Point2f center, int index)
 {
 	Mat img_crop;
+
 	getRectSubPix(src, rect_size, center, img_crop);
 
 	if(m_debug)
@@ -278,8 +279,25 @@ int CPlateLocate::plateLocate(Mat src, vector<Mat>& resultVec)
 				//Create and rotate image
 				Mat rotmat = getRotationMatrix2D(minRect.center, angle, 1);
 				Mat img_rotated;
+
+				/*if(m_debug)
+				{ 
+					stringstream ss(stringstream::in | stringstream::out);
+					ss << "image/tmp/needRotate" << i << ".jpg";
+					imwrite(ss.str(), result);
+				}*/
+
 				warpAffine(src, img_rotated, rotmat, src.size(), CV_INTER_CUBIC);
 
+				/*if(m_debug)
+				{ 
+					stringstream ss(stringstream::in | stringstream::out);
+					ss << "image/tmp/img_rotated" << i << ".jpg";
+					imwrite(ss.str(), result);
+				}*/
+
+
+				//Mat resultMat(img_rotated, minRect);
 				Mat resultMat;
 				resultMat = showResultMat(img_rotated, rect_size, minRect.center, k++);
 

src/main.cpp

@@ -71,8 +71,9 @@ int main()
 			case 4:
 				// TODO
 				break;
-			case 5:
-				general_test();
+			case 5:				
+				//general_test();
+				generate_gdts();
 				break;
 			case 6:
 				// 开发团队;

src/test/accuracy_test.cpp

@@ -149,13 +149,14 @@ int acurayTest(const string& test_path)
 	cout << "未识别图片:" << count_norecogin << "张,  ";
 
 	float count_recogin = count_all - (count_err + count_norecogin);
-	float count_rate  = count_recogin / count_all * 100;
-	cout << "识别率:" << count_rate << "%  " << endl;
+	float count_rate  = count_recogin / count_all;
+	float count_norate = 1 - count_rate;
+	cout << "未识出率:" << count_norate * 100 << "%  " << endl;
 
 	diff_avg = diff_all / count_recogin;
 	match_rate = match_count/ count_recogin * 100;
 
-	cout << "平均字距:" << diff_avg << "个,  ";
+	cout << "平均字符差距:" << diff_avg << "个,  ";
 	cout << "完全匹配数:" << match_count << "张,  ";
 	cout << "完全匹配率:" << match_rate << "%  " << endl;
 	cout << endl;

src/test/test.cpp

@@ -316,7 +316,7 @@ int test_plate_recognize()
 	cout << "test_plate_recognize" << endl;
 
 	//Mat src = imread("image/plate_locate.jpg");
-	Mat src = imread("image/test.jpg");
+	Mat src = imread("image/experi/¼½FA3215.jpg");
 
 	CPlateRecognize pr;
 	pr.LoadANN("model/ann.xml");

src/util/general_test_prepare.cpp

@@ -11,13 +11,16 @@ using namespace easypr;
 extern const string GENERAL_TEST_PATH;
 
 // TODO 将下面的路径改成你的
-const string your_data_path = "F:/data/easypr-data/tmp-3";
+const string src_path = "F:/data/easypr-data/tmp-5";
+
+// TODO 将下面的路径改成你的
+const string dst_path = "F:/data/easypr-data/tmp-6";
 
 int general_test()
 {
 	////获取该路径下的所有文件
 	vector<string> files;
-	getFiles(your_data_path, files);
+	getFiles(src_path, files);
 
 	CPlateLocate lo;
 	CPlateJudge ju;
@@ -69,7 +72,7 @@ int general_test()
 				if (size == 2)
 				{
 					stringstream ss(stringstream::in | stringstream::out);
-					ss << "F:/data/easypr-data/tmp-4" << "/" << spilt_plate[size-1] << ".jpg";
+					ss << dst_path << "/" << spilt_plate[size-1] << ".jpg";
 					imwrite(ss.str(), src);
 				}
 			}

src/util/generate_gdts.cpp

@@ -118,6 +118,6 @@ Mat imageProcess(Mat img)
 	Rect rect(width*0.01, height*0.01, width*0.99, height*0.99);
 
 	Mat dst = img(rect);
-	GaussianBlur( dst, dst, Size(1, 1), 0, 0, BORDER_DEFAULT );
+	//GaussianBlur( dst, dst, Size(1, 1), 0, 0, BORDER_DEFAULT );
 	return dst;
 }