support for opencv 4.5.0

CMakeLists.txt

@@ -10,7 +10,7 @@ if (CMAKE_SYSTEM_NAME MATCHES "Darwin")
 endif ()
 
 # OpenVC3 required
-find_package(OpenCV 3.2.0 REQUIRED)
+find_package(OpenCV 4.5.0 REQUIRED)
 
 # where to find header files
 include_directories(.)

include/easypr/config.h

@@ -1,7 +1,7 @@
 #ifndef EASYPR_CONFIG_H_
 #define EASYPR_CONFIG_H_
 
-#define CV_VERSION_THREE_ZERO
+#define CV_VERSION_TWO
 
 namespace easypr {
 
@@ -133,14 +133,14 @@ private:\
 // Load model. compatitable withe 3.0, 3.1 and 3.2
 #ifdef CV_VERSION_THREE_TWO
   #define LOAD_SVM_MODEL(model, path) \
-    model = ml::SVM::load(path);
+    model = Algorithm::load<SVM>(path);
   #define LOAD_ANN_MODEL(model, path) \
-    model = ml::ANN_MLP::load(path);
+    model = Algorithm::load<ANN_MLP>(path);
 #else
   #define LOAD_SVM_MODEL(model, path) \
-    model = ml::SVM::load<ml::SVM>(path);
+    model = Algorithm::load<ml::SVM>(path);
   #define LOAD_ANN_MODEL(model, path) \
-    model = ml::ANN_MLP::load<ml::ANN_MLP>(path);
+    model = Algorithm::load<ml::ANN_MLP>(path);
 #endif
 
 }

src/core/core_func.cpp

@@ -4,6 +4,7 @@
 #include "easypr/config.h"
 #include "easypr/core/params.h"
 #include "thirdparty/mser/mser2.hpp"
+#include <opencv2/highgui/highgui_c.h>
 #include <ctime>
 
 namespace easypr {

src/core/feature.cpp

@@ -33,12 +33,12 @@ Mat getHistogram(Mat in) {
 
 void getHistogramFeatures(const Mat& image, Mat& features) {
   Mat grayImage;
-  cvtColor(image, grayImage, CV_RGB2GRAY);
+  cvtColor(image, grayImage, COLOR_RGB2GRAY);
 
   //grayImage = histeq(grayImage);
 
   Mat img_threshold;
-  threshold(grayImage, img_threshold, 0, 255, CV_THRESH_OTSU + CV_THRESH_BINARY);
+  threshold(grayImage, img_threshold, 0, 255, cv::THRESH_OTSU + cv::THRESH_BINARY);
   //Mat img_threshold = grayImage.clone();
   //spatial_ostu(img_threshold, 8, 2, getPlateType(image, false));
 
@@ -50,7 +50,7 @@ void getColorFeatures(const Mat& src, Mat& features) {
   Mat src_hsv;
 
   //grayImage = histeq(grayImage);
-  cvtColor(src, src_hsv, CV_BGR2HSV);
+  cvtColor(src, src_hsv, COLOR_BGR2HSV);
   int channels = src_hsv.channels();
   int nRows = src_hsv.rows;
 
@@ -108,7 +108,7 @@ void getSIFTFeatures(const Mat& image, Mat& features) {
 //HOG Features
 void getHOGFeatures(const Mat& image, Mat& features) {
   //HOG descripter
-  HOGDescriptor hog(cvSize(128, 64), cvSize(16, 16), cvSize(8, 8), cvSize(8, 8), 3); //these parameters work well
+  HOGDescriptor hog(cv::Size(128, 64), cv::Size(16, 16), cv::Size(8, 8), cv::Size(8, 8), 3); //these parameters work well
 	std::vector<float> descriptor;
 
   // resize input image to (128,64) for compute
@@ -133,7 +133,7 @@ void getHSVHistFeatures(const Mat& image, Mat& features) {
 void getLBPFeatures(const Mat& image, Mat& features) {
 
   Mat grayImage;
-  cvtColor(image, grayImage, CV_RGB2GRAY);
+  cvtColor(image, grayImage, COLOR_RGB2GRAY);
 
   Mat lbpimage;
   lbpimage = libfacerec::olbp(grayImage);
@@ -377,7 +377,7 @@ void getGrayPlusProject(const Mat& grayChar, Mat& features)
   }
   SHOW_IMAGE(grayChar, 0);
   Mat binaryChar;
-  threshold(grayChar, binaryChar, 0, 255, CV_THRESH_OTSU + CV_THRESH_BINARY);
+  threshold(grayChar, binaryChar, 0, 255, cv::THRESH_OTSU + cv::THRESH_BINARY);
   SHOW_IMAGE(binaryChar, 0);
   Mat projectFeature = charProjectFeatures(binaryChar, 32);
 
@@ -442,20 +442,20 @@ void getGrayPlusLBP(const Mat& grayChar, Mat& features)
 
 void getLBPplusHistFeatures(const Mat& image, Mat& features) {
   Mat grayImage;
-  cvtColor(image, grayImage, CV_RGB2GRAY);
+  cvtColor(image, grayImage, COLOR_RGB2GRAY);
 
   Mat lbpimage;
   lbpimage = libfacerec::olbp(grayImage);
   Mat lbp_hist = libfacerec::spatial_histogram(lbpimage, 64, 8, 4);
   //features = lbp_hist.reshape(1, 1);
 
   Mat greyImage;
-  cvtColor(image, greyImage, CV_RGB2GRAY);
+  cvtColor(image, greyImage, COLOR_RGB2GRAY);
 
   //grayImage = histeq(grayImage);
   Mat img_threshold;
   threshold(greyImage, img_threshold, 0, 255,
-    CV_THRESH_OTSU + CV_THRESH_BINARY);
+    cv::THRESH_OTSU + cv::THRESH_BINARY);
   Mat histomFeatures = getHistogram(img_threshold);
 
   hconcat(lbp_hist.reshape(1, 1), histomFeatures.reshape(1, 1), features);

src/core/plate_locate.cpp

@@ -2,6 +2,7 @@
 #include "easypr/core/core_func.h"
 #include "easypr/util/util.h"
 #include "easypr/core/params.h"
+#include<opencv2/imgproc/types_c.h>
 
 using namespace std;
 
@@ -120,7 +121,7 @@ int CPlateLocate::colorSearch(const Mat &src, const Color r, Mat &out,
 
   Mat src_threshold;
   threshold(match_grey, src_threshold, 0, 255,
-            CV_THRESH_OTSU + CV_THRESH_BINARY);
+            cv::THRESH_OTSU + cv::THRESH_BINARY);
 
   Mat element = getStructuringElement(
       MORPH_RECT, Size(color_morph_width, color_morph_height));
@@ -313,7 +314,7 @@ int CPlateLocate::sobelOper(const Mat &in, Mat &out, int blurSize, int morphW,
 
   Mat mat_gray;
   if (mat_blur.channels() == 3)
-    cvtColor(mat_blur, mat_gray, CV_RGB2GRAY);
+    cvtColor(mat_blur, mat_gray, COLOR_RGB2GRAY);
   else
     mat_gray = mat_blur;
 
@@ -333,7 +334,7 @@ int CPlateLocate::sobelOper(const Mat &in, Mat &out, int blurSize, int morphW,
 
   Mat mat_threshold;
   double otsu_thresh_val =
-      threshold(grad, mat_threshold, 0, 255, CV_THRESH_OTSU + CV_THRESH_BINARY);
+      threshold(grad, mat_threshold, 0, 255, cv::THRESH_OTSU + cv::THRESH_BINARY);
 
 
   Mat element = getStructuringElement(MORPH_RECT, Size(morphW, morphH));
@@ -346,7 +347,7 @@ int CPlateLocate::sobelOper(const Mat &in, Mat &out, int blurSize, int morphW,
 
 void deleteNotArea(Mat &inmat, Color color = UNKNOWN) {
   Mat input_grey;
-  cvtColor(inmat, input_grey, CV_BGR2GRAY);
+  cvtColor(inmat, input_grey, COLOR_BGR2GRAY);
 
   int w = inmat.cols;
   int h = inmat.rows;
@@ -368,7 +369,7 @@ void deleteNotArea(Mat &inmat, Color color = UNKNOWN) {
     Mat tmp = input_grey(Rect_<double>(w * 0.15, h * 0.15, w * 0.7, h * 0.7));
     int threadHoldV = ThresholdOtsu(tmp);
 
-    threshold(input_grey, img_threshold, threadHoldV, 255, CV_THRESH_BINARY);
+    threshold(input_grey, img_threshold, threadHoldV, 255, cv::THRESH_BINARY);
     // threshold(input_grey, img_threshold, 5, 255, CV_THRESH_OTSU +
     // CV_THRESH_BINARY);
 
@@ -380,15 +381,15 @@ void deleteNotArea(Mat &inmat, Color color = UNKNOWN) {
     int threadHoldV = ThresholdOtsu(tmp);
 
     threshold(input_grey, img_threshold, threadHoldV, 255,
-              CV_THRESH_BINARY_INV);
+              cv::THRESH_BINARY_INV);
 
     utils::imwrite("resources/image/tmp/inputgray2.jpg", img_threshold);
 
     // threshold(input_grey, img_threshold, 10, 255, CV_THRESH_OTSU +
     // CV_THRESH_BINARY_INV);
   } else
     threshold(input_grey, img_threshold, 10, 255,
-              CV_THRESH_OTSU + CV_THRESH_BINARY);
+              cv::THRESH_OTSU + cv::THRESH_BINARY);
 
   //img_threshold = input_grey.clone();
   //spatial_ostu(img_threshold, 8, 2, plateType);

src/train/annCh_train.cpp

@@ -71,7 +71,7 @@ namespace easypr {
   ann_->setLayerSizes(layers);
   ann_->setActivationFunction(cv::ml::ANN_MLP::SIGMOID_SYM, 1, 1);
   ann_->setTrainMethod(cv::ml::ANN_MLP::TrainingMethods::BACKPROP);
-  ann_->setTermCriteria(cvTermCriteria(CV_TERMCRIT_ITER, 30000, 0.0001));
+  ann_->setTermCriteria(TermCriteria(cv::TermCriteria::MAX_ITER, 30000, 0.0001));
   ann_->setBackpropWeightScale(0.1);
   ann_->setBackpropMomentumScale(0.1);
 

src/train/ann_train.cpp

@@ -74,7 +74,7 @@ void AnnTrain::train() {
   ann_->setLayerSizes(layers);
   ann_->setActivationFunction(cv::ml::ANN_MLP::SIGMOID_SYM, 1, 1);
   ann_->setTrainMethod(cv::ml::ANN_MLP::TrainingMethods::BACKPROP);
-  ann_->setTermCriteria(cvTermCriteria(CV_TERMCRIT_ITER, 30000, 0.0001));
+  ann_->setTermCriteria(TermCriteria(cv::TermCriteria::MAX_ITER, 30000, 0.0001));
   ann_->setBackpropWeightScale(0.1);
   ann_->setBackpropMomentumScale(0.1);
 

src/train/svm_train.cpp

@@ -30,7 +30,7 @@ void SvmTrain::train() {
   svm_->setC(1);
   svm_->setNu(0.1);
   svm_->setP(0.1);
-  svm_->setTermCriteria(cvTermCriteria(CV_TERMCRIT_ITER, 20000, 0.0001));
+  svm_->setTermCriteria(TermCriteria(cv::TermCriteria::MAX_ITER, 20000, 0.0001));
 
   this->prepare();
 

thirdparty/CMakeLists.txt

@@ -2,7 +2,7 @@ cmake_minimum_required(VERSION 3.1.0)
 project(thirdparty)
 
 # OpenVC3 required
-find_package(OpenCV 3.1.0 REQUIRED)
+find_package(OpenCV 4.5.0 REQUIRED)
 
 # where to find header files
 include_directories(${OpenCV_INCLUDE_DIRS})

thirdparty/LBP/helper.cpp

@@ -89,9 +89,9 @@ bool libfacerec::isSymmetric(InputArray src, double eps) {
 Mat libfacerec::argsort(InputArray _src, bool ascending) {
     Mat src = _src.getMat();
     if (src.rows != 1 && src.cols != 1) {
-        CV_Error(CV_StsBadArg, "cv::argsort only sorts 1D matrices.");
+        CV_Error(Error::StsBadArg, "cv::argsort only sorts 1D matrices.");
     }
-    int flags = CV_SORT_EVERY_ROW+(ascending ? CV_SORT_ASCENDING : CV_SORT_DESCENDING);
+    int flags = cv::SORT_EVERY_ROW+(ascending ? cv::SORT_ASCENDING : cv::SORT_DESCENDING);
     Mat sorted_indices;
     cv::sortIdx(src.reshape(1,1),sorted_indices,flags);
     return sorted_indices;
@@ -142,7 +142,7 @@ Mat libfacerec::histc(InputArray _src, int minVal, int maxVal, bool normed) {
         return histc_(src, minVal, maxVal, normed);
         break;
     default:
-        CV_Error(CV_StsUnmatchedFormats, "This type is not implemented yet."); break;
+        CV_Error(cv::Error::StsUnmatchedFormats, "This type is not implemented yet."); break;
     }
     return Mat();
 }
@@ -154,7 +154,7 @@ Mat libfacerec::histc(InputArray _src, int minVal, int maxVal, bool normed) {
 void libfacerec::sortMatrixColumnsByIndices(InputArray _src, InputArray _indices, OutputArray _dst) {
     if(_indices.getMat().type() != CV_32SC1) {
     	string error_message = format("cv::sortRowsByIndices only works on integer indices! Expected: %d. Given: %d.", CV_32SC1, _indices.getMat().type());
-    	CV_Error(CV_StsBadArg, error_message);
+    	CV_Error(Error::StsBadArg , error_message);
     }
     Mat src = _src.getMat();
     vector<int> indices = _indices.getMat();
@@ -179,7 +179,7 @@ Mat libfacerec::sortMatrixColumnsByIndices(InputArray src, InputArray indices) {
 void libfacerec::sortMatrixRowsByIndices(InputArray _src, InputArray _indices, OutputArray _dst) {
     if(_indices.getMat().type() != CV_32SC1) {
     	string error_message = format("cv::sortRowsByIndices only works on integer indices! Expected: %d. Given: %d.", CV_32SC1, _indices.getMat().type());
-    	CV_Error(CV_StsBadArg, error_message);
+    	CV_Error(Error::StsBadArg, error_message);
     }
     Mat src = _src.getMat();
     vector<int> indices = _indices.getMat();
@@ -204,7 +204,7 @@ Mat libfacerec::sortMatrixRowsByIndices(InputArray src, InputArray indices) {
 Mat libfacerec::asRowMatrix(InputArrayOfArrays src, int rtype, double alpha, double beta) {
     // make sure the input data is a vector of matrices or vector of vector
     if(src.kind() != _InputArray::STD_VECTOR_MAT && src.kind() != _InputArray::STD_VECTOR_VECTOR) {
-        CV_Error(CV_StsBadArg, "The data is expected as InputArray::STD_VECTOR_MAT (a std::vector<Mat>) or _InputArray::STD_VECTOR_VECTOR (a std::vector< vector<...> >).");
+        CV_Error(Error::StsBadArg , "The data is expected as InputArray::STD_VECTOR_MAT (a std::vector<Mat>) or _InputArray::STD_VECTOR_VECTOR (a std::vector< vector<...> >).");
     }
     // number of samples
     size_t n = src.total();
@@ -220,7 +220,7 @@ Mat libfacerec::asRowMatrix(InputArrayOfArrays src, int rtype, double alpha, dou
         // make sure data can be reshaped, throw exception if not!
         if(src.getMat(i).total() != d) {
             string error_message = format("Wrong number of elements in matrix #%d! Expected %d was %d.", i, d, src.getMat(i).total());
-            CV_Error(CV_StsBadArg, error_message);
+            CV_Error(Error::StsBadArg , error_message);
         }
         // get a hold of the current row
         Mat xi = data.row(i);
@@ -240,7 +240,7 @@ Mat libfacerec::asRowMatrix(InputArrayOfArrays src, int rtype, double alpha, dou
 Mat libfacerec::asColumnMatrix(InputArrayOfArrays src, int rtype, double alpha, double beta) {
     // make sure the input data is a vector of matrices or vector of vector
     if(src.kind() != _InputArray::STD_VECTOR_MAT && src.kind() != _InputArray::STD_VECTOR_VECTOR) {
-        CV_Error(CV_StsBadArg, "The data is expected as InputArray::STD_VECTOR_MAT (a std::vector<Mat>) or _InputArray::STD_VECTOR_VECTOR (a std::vector< vector<...> >).");
+        CV_Error(Error::StsBadArg , "The data is expected as InputArray::STD_VECTOR_MAT (a std::vector<Mat>) or _InputArray::STD_VECTOR_VECTOR (a std::vector< vector<...> >).");
     }
     int n = (int) src.total();
     // return empty matrix if no data given
@@ -255,7 +255,7 @@ Mat libfacerec::asColumnMatrix(InputArrayOfArrays src, int rtype, double alpha,
         // make sure data can be reshaped, throw exception if not!
         if(src.getMat(i).total() != d) {
             string error_message = format("Wrong number of elements in matrix #%d! Expected %d was %d.", i, d, src.getMat(i).total());
-            CV_Error(CV_StsBadArg, error_message);
+            CV_Error(Error::StsBadArg , error_message);
         }
         // get a hold of the current row
         Mat yi = data.col(i);