* fix #184, fix #174, fix#158: the kv load etc file, no respones bug

* fix #194, move resources/model to model,  move etc to resources/text
* fix #191, new chinese gray train.

CMakeLists.txt

@@ -6,19 +6,12 @@ set(CMAKE_CXX_STANDARD 11)
 set(CMAKE_CXX_STANDARD_REQUIRED ON)
 
 if (CMAKE_SYSTEM_NAME MATCHES "Darwin")
-  set(CMAKE_PREFIX_PATH ${CMAKE_PREFIX_PATH} "/usr/local/opt/opencv3")
+    set(CMAKE_PREFIX_PATH ${CMAKE_PREFIX_PATH} "/usr/local/opt/opencv-3.1.0")
 endif ()
 
 # OpenVC3 required
 find_package(OpenCV 3.1.0 REQUIRED)
 
-# optional OpenMP
-find_package(OpenMP)
-if (OPENMP_FOUND)
-    set (CMAKE_C_FLAGS "${CMAKE_C_FLAGS} ${OpenMP_C_FLAGS}")
-    set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${OpenMP_CXX_FLAGS}")
-endif()
-
 # where to find header files
 include_directories(.)
 include_directories(include)
@@ -41,12 +34,10 @@ set(SOURCE_FILES
         src/core/params.cpp
 
         src/train/ann_train.cpp
+        src/train/annCh_train.cpp
         src/train/svm_train.cpp
         src/train/train.cpp
-
-        src/preprocess/deface.cpp
-        src/preprocess/gdts.cpp
-        src/preprocess/mc_data.cpp
+        src/train/create_data.cpp
 
         src/util/util.cpp
         src/util/program_options.cpp
@@ -57,12 +48,17 @@ set(SOURCE_FILES
 add_library(easypr STATIC ${SOURCE_FILES})
 
 if (CMAKE_SYSTEM_NAME MATCHES "Darwin")
-  set(EXECUTABLE_NAME "demo_darwin_amd64")
+    set(EXECUTABLE_NAME "demo")
 elseif (CMAKE_SYSTEM_NAME MATCHES "Linux")
-  set(EXECUTABLE_NAME "demo_linux_amd64")
+    set(EXECUTABLE_NAME "demo")
 endif ()
 
+# set to be releas mode
+# set(CMAKE_BUILD_TYPE Release)
+
 # test cases
 add_executable(${EXECUTABLE_NAME} test/main.cpp)
 # link opencv libs
-target_link_libraries(${EXECUTABLE_NAME} easypr thirdparty ${OpenCV_LIBS})
+target_link_libraries(${EXECUTABLE_NAME} easypr thirdparty ${OpenCV_LIBS})
+# MESSAGE(${CMAKE_BINARY_DIR}/../)
+SET_TARGET_PROPERTIES(${EXECUTABLE_NAME} PROPERTIES RUNTIME_OUTPUT_DIRECTORY  "${CMAKE_BINARY_DIR}/../")

README.md

@@ -148,12 +148,12 @@ EasyPR的resources/image/general_test文件夹下的图片数据遵循[GDSL协
 | src |  所有源文件
 | include | 所有头文件
 | test | 测试程序
-| etc | 中文字符映射表
-| resources/model | 机器学习的模型
+| model | 机器学习的模型
+| resources/text | 中文字符映射表
 | resources/train | 训练数据与说明
 | resources/image | 测试用的图片
 | resources/doc | 相关文档
-| tmp | 需要自建，训练数据读取目录
+| tmp | 训练数据读取目录，需要自建
 
 以下表格是resources/image目录中子目录的解释:
 
@@ -161,7 +161,7 @@ EasyPR的resources/image/general_test文件夹下的图片数据遵循[GDSL协
 |------|----------
 | general_test | GDTS（通用数据测试集）
 | native_test | NDTS（本地数据测试集）
-| tmp | Debug模式下EasyPR输出中间图片的目录
+| tmp | Debug模式下EasyPR输出中间图片的目录，需要自建
 
 以下表格是src目录中子目录的解释:
 

include/easypr/config.h

@@ -26,13 +26,16 @@ namespace easypr {
     PR_DETECT_CMSER = 0x04,  /**Character detect type, using mser  */
   };
 
-static const char* kDefaultSvmPath = "resources/model/svm_hist.xml";
-static const char* kLBPSvmPath = "resources/model/svm_lbp.xml";
-static const char* kHistSvmPath = "resources/model/svm_hist.xml";
+static const char* kDefaultSvmPath = "model/svm_hist.xml";
+static const char* kLBPSvmPath = "model/svm_lbp.xml";
+static const char* kHistSvmPath = "model/svm_hist.xml";
 
-static const char* kDefaultAnnPath = "resources/model/ann.xml";
-static const char* kChineseAnnPath = "resources/model/ann_chinese.xml";
-static const char* kGrayAnnPath = "resources/model/annCh.xml";
+static const char* kDefaultAnnPath = "model/ann.xml";
+static const char* kChineseAnnPath = "model/ann_chinese.xml";
+static const char* kGrayAnnPath = "model/annCh.xml";
+
+//This is important to for key transform to chinese
+static const char* kChineseMappingPath = "model/province_mapping";
 
 typedef enum {
   kForward = 1, // correspond to "has plate"

include/easypr/core/chars_identify.h

@@ -33,15 +33,24 @@ public:
 
   void LoadModel(std::string path);
   void LoadChineseModel(std::string path);
-  void LoadGrayModel(std::string path);
+  void LoadGrayChANN(std::string path);
+  void LoadChineseMapping(std::string path);
 
 private:
   CharsIdentify();
   annCallback extractFeature;
   static CharsIdentify* instance_;
+
+  // binary character classifer
   cv::Ptr<cv::ml::ANN_MLP> ann_;
+
+  // binary character classifer, only for chinese
   cv::Ptr<cv::ml::ANN_MLP> annChinese_;
+
+  // gray classifer, only for chinese
   cv::Ptr<cv::ml::ANN_MLP> annGray_;
+
+  // used for chinese mapping
   std::shared_ptr<Kv> kv_;
 };
 }

include/easypr/core/plate_recognize.h

@@ -39,6 +39,10 @@ namespace easypr {
     void LoadANN(std::string path);
     void LoadChineseANN(std::string path);
 
+    //v1.6 added
+    void LoadGrayChANN(std::string path);
+    void LoadChineseMapping(std::string path);
+
   private:
     // show the detect and recognition result image
     bool m_showResult;

resources/text/province_mapping

@@ -0,0 +1,31 @@
+zh_cuan    川
+zh_gan1    甘
+zh_hei     黑
+zh_jin     津
+zh_liao    辽
+zh_min     闽
+zh_qiong   琼
+zh_sx      晋
+zh_xin     新
+zh_yue     粤
+zh_zhe     浙
+zh_e       鄂
+zh_gui     贵
+zh_hu      沪
+zh_jing    京
+zh_lu      鲁
+zh_ning    宁
+zh_shan    陕
+zh_wan     皖
+zh_yu      豫
+zh_yun     云
+zh_gan     赣
+zh_gui1    桂
+zh_ji      冀
+zh_jl      吉
+zh_meng    蒙
+zh_qing    青
+zh_su      苏
+zh_xiang   湘
+zh_yu1     渝
+zh_zang    藏

resources/text/thanks

@@ -3,5 +3,5 @@
 (贡献包括有益建议，代码调优，数据提供等等,排名按时间顺序)：
 taotao1233，邱锦山，唐大侠，jsxyhelu，如果有一天(zhoushiwei)，
 学习奋斗，袁承志，圣城小石匠，goldriver，Micooz，梦里时光，
-Rain Wang，ahccoms，星夜落尘，海豚嘎嘎
+Rain Wang，ahccoms，星夜落尘，海豚嘎嘎, Free大神等等
 还有很多的同学对本项目也给予了鼓励与支持，在此也一并表示真诚的谢意！

result/accuracy.txt

@@ -3248,3 +3248,18 @@ Recall:85.1281%, Precise:80.5653%, Fscore:82.7839%.
 Recall:85.1281%, Precise:80.5653%, Fscore:82.7839%.
 0-error:70.6122%,  1-error:82.8571%,  Chinese-precise:86.5306%  
 总共时间: 150秒,  平均执行时间:0.585938秒
+2017-04-30 16:38:57
+总图片数:256,  Plates count:297,  未定位车牌:23,  检出率:92.2559%  
+Recall:85.1281%, Precise:80.5653%, Fscore:82.7839%.
+0-error:70.6122%,  1-error:82.8571%,  Chinese-precise:86.5306%  
+总共时间: 157秒,  平均执行时间:0.613281秒
+2017-04-30 17:14:08
+总图片数:256,  Plates count:297,  未定位车牌:23,  检出率:92.2559%  
+Recall:85.1281%, Precise:80.5653%, Fscore:82.7839%.
+0-error:70.6122%,  1-error:82.8571%,  Chinese-precise:86.5306%  
+总共时间: 166秒,  平均执行时间:0.648438秒
+2017-04-30 17:29:47
+总图片数:256,  Plates count:297,  未定位车牌:23,  检出率:92.2559%  
+Recall:85.1281%, Precise:80.5653%, Fscore:82.7839%.
+0-error:70.6122%,  1-error:82.8571%,  Chinese-precise:86.5306%  
+总共时间: 159秒,  平均执行时间:0.621094秒

src/core/chars_identify.cpp

@@ -22,8 +22,9 @@ CharsIdentify::CharsIdentify() {
   LOAD_ANN_MODEL(ann_, kDefaultAnnPath);
   LOAD_ANN_MODEL(annChinese_, kChineseAnnPath);
   LOAD_ANN_MODEL(annGray_, kGrayAnnPath);
+
   kv_ = std::shared_ptr<Kv>(new Kv);
-  kv_->load("etc/province_mapping");
+  kv_->load(kChineseMappingPath);
 
   extractFeature = getGrayPlusProject;
 }
@@ -44,7 +45,7 @@ void CharsIdentify::LoadChineseModel(std::string path) {
   }
 }
 
-void CharsIdentify::LoadGrayModel(std::string path) {
+void CharsIdentify::LoadGrayChANN(std::string path) {
   if (path != std::string(kGrayAnnPath)) {
     if (!annGray_->empty())
       annGray_->clear();
@@ -52,6 +53,11 @@ void CharsIdentify::LoadGrayModel(std::string path) {
   }
 }
 
+void CharsIdentify::LoadChineseMapping(std::string path) {
+  kv_->clear();
+  kv_->load(path);
+}
+
 void CharsIdentify::classify(cv::Mat featureRows, std::vector<int>& out_maxIndexs,
                              std::vector<float>& out_maxVals, std::vector<bool> isChineseVec){
   int rowNum = featureRows.rows;

src/core/plate_recognize.cpp

@@ -83,6 +83,14 @@ void CPlateRecognize::LoadChineseANN(std::string path) {
   CharsIdentify::instance()->LoadChineseModel(path);
 }
 
+void CPlateRecognize::LoadGrayChANN(std::string path) {
+  CharsIdentify::instance()->LoadGrayChANN(path);
+}
+
+void CPlateRecognize::LoadChineseMapping(std::string path) {
+  CharsIdentify::instance()->LoadChineseMapping(path);
+}
+
 // deprected
 int CPlateRecognize::plateRecognize(const Mat& src, std::vector<std::string> &licenseVec) {
   vector<CPlate> plates;

src/train/annCh_train.cpp

@@ -17,7 +17,7 @@ namespace easypr {
   ann_ = cv::ml::ANN_MLP::create();
   type = 1;
   kv_ = std::shared_ptr<Kv>(new Kv);
-  kv_->load("etc/province_mapping");
+  kv_->load("resources/text/province_mapping");
   extractFeature = getGrayPlusProject;
 }