int main(int argc, char *argv[]) {
// int rc;
printf("Initializing Plate Detector...\n");
//cout << "OpenCV Automatic Number Plate Recognition\n";
char* filename;
Mat input_image;
//Check if user specify image to process
if(argc >= 2 )
{
filename= argv[1];
//load image in gray level
input_image=imread(filename,1);
}else{
printf("Use:\n\t%s image\n",argv[0]);
return 0;
}
string filename_whithoutExt=getFilename(filename);
cout << "working with file: "<< filename_whithoutExt << "\n";
//Detect posibles plate regions
DetectRegions detectRegions;
detectRegions.setFilename(filename_whithoutExt);
detectRegions.saveRegions=false;
detectRegions.showSteps=false;
vector<Plate> possible_regions= detectRegions.run(input_image);
printf("Plates detected: %zu\n\n", possible_regions.size());
waitKey(0);
//while(1) {
// rc = controller->loop();
// if(rc){
// controller->reconnect();
// }
// controller->step();
//usleep(100000);
//}
return 0;
}
int main ( int argc, char** argv )
{
int result;
char* filename;
Mat input_image;
bool web_mode = false;
bool result_image_mode = false;
bool display_mode = false;
bool show_step = false;
bool ocr_debug_mode = false;
while ((result = getopt(argc, argv, "widhsc")) != (-1)) {
switch (result) {
case 'w': // web mode
web_mode = true;
break;
case 'i': //create result image
result_image_mode = true;
break;
case 'd': // display result image
display_mode = true;
break;
case 's': // DetectRegion.showStep = true
show_step = true;
break;
case 'c': // DetectRegion.showStep = true
ocr_debug_mode = true;
break;
case 'h':
printf("Usage:\n\t%s [-w|-i|-d|-s|-c|-h] image\n", argv[0]);
printf(" -w : Web mode (simple output)\n");
printf(" -i : save Result Image to result folder\n");
printf(" -d : display Result Image to screen\n");
printf(" -s : show step on Detect Plate\n");
printf(" -c : OCR debug mode\n");
printf(" -h : This help\n");
exit(0);
}
}
if (optind >= argc) {
printf("Usage:\n\t%s [-w|-i|-d|-s|-c|-h] image\n", argv[0]);
exit(0);
}
for (;optind < argc; optind++) {
filename = argv[optind];
input_image=imread(filename,1);
}
if (web_mode != true)
cout << "OpenCV Automatic Number Plate Recognition\n";
/*
//Check if user specify image to process
if(argc >= 2 )
{
filename= argv[1];
//load image in gray level
input_image=imread(filename,1);
}else{
printf("Use:\n\t%s image\n",argv[0]);
return 0;
}
*/
string filename_whithoutExt=getFilename(filename);
if (web_mode != true)
cout << "working with file: "<< filename_whithoutExt << "\n";
//Detect posibles plate regions
DetectRegions detectRegions;
detectRegions.setFilename(filename_whithoutExt);
// detectRegions.saveRegions=false;
// detectRegions.showSteps=false;
detectRegions.saveRegions=true;
// detectRegions.showSteps=true;
if (show_step == true)
detectRegions.showSteps=true;
vector<Plate> posible_regions= detectRegions.run( input_image );
//SVM for each plate region to get valid car plates
//Read file storage.
FileStorage fs;
fs.open("SVM.xml", FileStorage::READ);
Mat SVM_TrainingData;
Mat SVM_Classes;
fs["TrainingData"] >> SVM_TrainingData;
fs["classes"] >> SVM_Classes;
//Set SVM params
CvSVMParams SVM_params;
SVM_params.svm_type = CvSVM::C_SVC;
SVM_params.kernel_type = CvSVM::LINEAR; //CvSVM::LINEAR;
SVM_params.degree = 0;
SVM_params.gamma = 1;
SVM_params.coef0 = 0;
SVM_params.C = 1;
SVM_params.nu = 0;
SVM_params.p = 0;
SVM_params.term_crit = cvTermCriteria(CV_TERMCRIT_ITER, 1000, 0.01);
//Train SVM
CvSVM svmClassifier(SVM_TrainingData, SVM_Classes, Mat(), Mat(), SVM_params);
//For each possible plate, classify with svm if it's a plate or no
vector<Plate> plates;
for(int i=0; i< posible_regions.size(); i++)
{
Mat img=posible_regions[i].plateImg;
Mat p= img.reshape(1, 1);
p.convertTo(p, CV_32FC1);
int response = (int)svmClassifier.predict( p );
if(response==1)
plates.push_back(posible_regions[i]);
}
if (web_mode != true)
cout << "Num plates detected: " << plates.size() << "\n";
//For each plate detected, recognize it with OCR
OCR ocr("OCR.xml");
ocr.saveSegments=true;
ocr.DEBUG=ocr_debug_mode; // @f
ocr.filename=filename_whithoutExt;
// cout << "---- plates.size() = " << plates.size() << "\n"; // @f
for(int i=0; i< plates.size(); i++){
Plate plate=plates[i];
string plateNumber=ocr.run(&plate);
// cout << "---- platesNumber() = " << plateNumber << "\n"; // @f
string licensePlate= plate.str();
if (web_mode != true) {
cout << "================================================\n";
cout << "License plate number: "<< licensePlate << "\n";
cout << "================================================\n";
} else {
cout << licensePlate << "\n";
}
rectangle(input_image, plate.position, Scalar(0,0,200));
putText(input_image, licensePlate, Point(plate.position.x, plate.position.y), CV_FONT_HERSHEY_SIMPLEX, 1, Scalar(0,0,200),2);
if(false){
imshow("Plate Detected seg", plate.plateImg);
cvWaitKey(0);
}
}
if (result_image_mode == true) {
string wrt_filename = "result/";
wrt_filename += (filename_whithoutExt + ".jpg");
//cout << "--- create image file " << wrt_filename << "\n";
imwrite(wrt_filename, input_image);
}
if (display_mode == true) {
imshow("Plate Detected", input_image);
cvWaitKey(0);
/*
for(;;) {
int c;
c = cvWaitKey(10) & 0xff;
if( (char) c == 27)
break;
}
*/
}
return 0;
}
int main()
{
cout << "OpenCV Automatic Number Plate Recognition\n";
string filename;
Mat input_image;
filename="TP1_computer_vision\\2715DTZ.JPG";
input_image=imread(filename,1);
//Detect posibles plate regions
DetectRegions detectRegions;
detectRegions.setFilename("2715DTZ");
detectRegions.saveRegions=true;
detectRegions.showSteps=false;
vector<Plate> posible_regions= detectRegions.run( input_image );
string filename1 = "result";
//SVM for each plate region to get valid car plates
//Read file storage.
FileStorage fs;
fs.open("TP1_computer_vision\\SVM.XML", FileStorage::READ);
Mat SVM_TrainingData;
Mat SVM_Classes;
fs["TrainingData"] >> SVM_TrainingData;
fs["classes"] >> SVM_Classes;
//Set SVM params
CvSVMParams SVM_params;
SVM_params.svm_type = CvSVM::C_SVC;
SVM_params.kernel_type = CvSVM::LINEAR; //CvSVM::LINEAR;
SVM_params.degree = 0;
SVM_params.gamma = 1;
SVM_params.coef0 = 0;
SVM_params.C = 1;
SVM_params.nu = 0;
SVM_params.p = 0;
SVM_params.term_crit = cvTermCriteria(CV_TERMCRIT_ITER, 1000, 0.01);
//Train SVM
CvSVM svmClassifier(SVM_TrainingData, SVM_Classes, Mat(), Mat(), SVM_params);
//For each possible plate, classify with svm if it's a plate or no
vector<Plate> plates;
for(int i=0; i< (int)posible_regions.size(); i++)
{
Mat img=posible_regions[i].plateImg;
Mat p= img.reshape(1, 1);
p.convertTo(p, CV_32FC1);
int response = (int)svmClassifier.predict( p );
if(response==1){
stringstream ss(stringstream::in | stringstream::out);
ss << ".\\output\\predicted\\" << filename1 <<".JPG";
imwrite(ss.str(), posible_regions[i].plateImg);
plates.push_back(posible_regions[i]);
}}
//imshow("plate",plates);
cout << "Num plates detected: " << plates.size() << "\n\n\n";
//For each plate detected, recognize it with OCR
OCR ocr("TP1_computer_vision\\OCR.XML");
ocr.filename="2715DTZ";
ocr.saveSegments=false;
ocr.DEBUG=false;
for(int i=0; i< (int) plates.size(); i++){
Plate plate=plates[i];
string plateNumber=ocr.run(&plate);
string licensePlate=plate.str();
cout << "================================================\n";
cout << "License plate number: "<< licensePlate << "\n";
cout << "================================================\n";
rectangle(input_image, plate.position, Scalar(0,0,200));
putText(input_image, licensePlate, Point(plate.position.x, plate.position.y), CV_FONT_HERSHEY_SIMPLEX, 1, Scalar(0,0,200),2);
if(false){
imshow("Plate Detected seg", plate.plateImg);
cvWaitKey(0);
}
}
imshow("Plate Detected", input_image);
for(;;)
{
int c;
c = cvWaitKey(10);
if( (char) c == 27)
break;
}
return 0;
}
