/*
=======================================
获取 TESS-OCR 结果文本
=======================================
*/
CR_API ansi_t*
tessocr_get_utf8 (
__CR_IN__ tessocr_t tessocr
)
{
TessBaseAPI* tess;
tess = (TessBaseAPI*)tessocr;
return (tess->GetUTF8Text());
}
string ocr_tesseract(Mat im) {
// Pass it to Tesseract API
TessBaseAPI tess;
tess.Init(NULL, "eng", OEM_DEFAULT);
tess.SetPageSegMode(PSM_SINGLE_BLOCK);
tess.SetImage((uchar*)im.data, im.cols, im.rows, 1, im.cols);
// Get the text
char* out = tess.GetUTF8Text();
string ret = (string)out;
return ret;
}
//----------------------------------------------------------------------------------
void OCRit(Mat inputimg, vector<vector<Point>>points, char data[][60], Mat &outputimg, char lang[]){
TessBaseAPI tess;
tess.Init(NULL, lang, OEM_DEFAULT);
cout << "\n\n";
for (unsigned int c = 0; c < points.size(); c++){
Mat imag = inputimg(Rect(points[c][0], points[c][1]));
Mat img;
cvtColor(imag, img, COLOR_BGR2GRAY);//use img to do ocr now
tess.SetImage((uchar*)img.data, img.size().width, img.size().height, img.channels(), img.step1());
char* out = tess.GetUTF8Text();
cout << c + 1 << " -- " << out << "\n";
strcpy(data[c],out);
//removed to prevent alteration of original pan
//rectangle(outputimg, points[c][0], points[c][1],1,4,0);
}
}
int main()
{
Mat findImage = imread("sudo.jpg", IMREAD_GRAYSCALE); //이 이미지
int tempsudo[81] = { 0 };
int sudoku[9][9] = { 0 };
Mat cloneImage = findImage.clone();
threshold(findImage, findImage, 200, 255, THRESH_BINARY);
//adaptiveThreshold(findImage, findImage, 255, ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 21, 2);
imshow("findImage", findImage);
waitKey();
Mat srcImage2 = findImage.clone();
Mat dstImage(srcImage2.size(), CV_8UC3);
vector<vector<Point> > beforeContoursforRectangle;//스도쿠 이미지만 빼기위한 경계선
vector<vector<Point> > AfterContoursforSmallRectangle; //스도쿠에서 작은 네모만 빼기위한경계선
vector<vector<Point> > configurBackground;
vector<Vec4i> hierarchy; //외곽선용
vector<Vec4i> hierarchy2; //81개칸용
vector<Vec4i> hierarchy3; //배경 검사용
vector<vector<Point>> cutSize;//외곽선용
vector<vector<Point>> cutSize2;//81개칸용
vector<vector<Point>> cutSize3; //배경 검사용
int mode = RETR_TREE;
int method = CHAIN_APPROX_NONE;
Rect r;
findContours(findImage, beforeContoursforRectangle, hierarchy, mode, method); //윤곽석 검출
cout << "beforeContoursforRectangle.size()=" << beforeContoursforRectangle.size() << endl; //윤곽선네모 개수
cout << findImage.size() << endl; //이미지 크기
int countMax = beforeContoursforRectangle[0].size(); //최대크기를 찾기위한 변수선언
for (int k = 0; k < beforeContoursforRectangle.size(); k++)
{
if (beforeContoursforRectangle[k].size()>countMax)
countMax = beforeContoursforRectangle[k].size();
}
for (int k = 0; k < beforeContoursforRectangle.size(); k++)
{
if (beforeContoursforRectangle[k].size()>(countMax*0.6))//스토쿠 판만 빼오기
{
cutSize.push_back(beforeContoursforRectangle[k]);
}
}
/*
//테스트용
Mat testtImage;
for (int k = 0; k < cutSize.size(); k++)
{
//
cvtColor(findImage, testtImage, COLOR_GRAY2BGR);
r = boundingRect(cutSize[k]);//영역 사각형으로 감쌈
Rect ROI2(r.x, r.y, r.width, r.height);
drawContours(testtImage, cutSize, k, Scalar(255, 0, 0), 4); //경계선 그림
cout << r.size() << endl;
rectangle(testtImage, ROI2, Scalar(128, 255, 255), 2);//네모로 크림
circle(testtImage, cutSize[k][0], 5, Scalar(123, 123, 123), -1);
imshow("testtImage", testtImage);
waitKey();
}
*/
vector<vector<Point>> cuttingArea;
int pushArea = -1;
int smaller = cutSize[0].size();
for (int k = 1; k < cutSize.size(); k++)
{
if (cutSize[k].size() < smaller)
{
smaller = cutSize[k].size(); //제일 작은거 가져옴 sort(cutsize.begin(),cutsize.end())가안되서 이방법 씀
pushArea = k;
}
}
cuttingArea.push_back(cutSize[pushArea]);
r = boundingRect(cuttingArea[0]);
Rect ROI(r.x, r.y, r.width, r.height); //자를곳을 골라서 영역 표시
cout << "bigSize.size()=" << cutSize.size() << endl;
int eraseSpot = -1;
int again = 0;
int mode2 = RETR_LIST;
int mode3 = RETR_LIST;
int method2 = CHAIN_APPROX_NONE;
int method3 = CHAIN_APPROX_NONE;
Mat roi = cloneImage(ROI); //해당 영역만 가지고옴
Mat newImage = repeat(roi, 1, 1);
Mat contourImage = newImage.clone(); //배경에 음영있는것들 검출
for (int a = 0; a < contourImage.rows; a++)
{
for (int b = 0; b < contourImage.cols; b++)
{
float te = contourImage.at<uchar>(a, b);
if (te >= 160 && te < 190)
contourImage.at<uchar>(a, b) = 250;
}
}
threshold(contourImage, contourImage, 230, 255, THRESH_BINARY);
imshow("contourImage", contourImage);
waitKey();
vector<int> configureRectSizeStorage; //빈칸과 숫자칸 저장
vector<int> configureRect; //빈칸숫자칸의 최대 최소값을 알기위해 만듬
vector<Rect> countRect;
findContours(contourImage, configurBackground, hierarchy3, mode3, method3);
for (int k = 0; k < configurBackground.size(); k++)
{
cutSize3.push_back(configurBackground[k]); //그 경계선위치들을 넣음
}
Mat configureBackgroundImage(contourImage.size(), CV_8UC1);
for (int k = 0; k < cutSize3.size(); k++)
{
//
cvtColor(contourImage, configureBackgroundImage, COLOR_GRAY2BGR);
r = boundingRect(cutSize3[k]);//영역 사각형으로 감쌈
Rect ROI2(r.x, r.y, r.width, r.height);
drawContours(configureBackgroundImage, cutSize3, k, Scalar(255, 0, 0), 4); //경계선 그림
//cout << r.size() << endl;
rectangle(configureBackgroundImage, ROI2, Scalar(128, 255, 255), 2);//네모로 크림
if ((r.width*r.height)>(configureBackgroundImage.rows*configureBackgroundImage.cols) - 20000)
{ //최대영역은 받지 않음
//imshow("resultImage", resultImage);
//waitKey();
goto here234;
}
configureRectSizeStorage.push_back(r.width*r.height); //sorting하기 위해 정리
here234:{}
circle(configureBackgroundImage, cutSize3[k][0], 5, Scalar(123, 123, 123), -1);
//imshow("resultImage", configureBackgroundImage);
//waitKey();
}
sort(configureRectSizeStorage.begin(), configureRectSizeStorage.end());
int tSpot = -1;
int tagain = 0;
for (int k = 0; k < configureRectSizeStorage.size(); k++)
{
if (k == configureRectSizeStorage.size() - 1)
break;
if ((configureRectSizeStorage[k + 1] - configureRectSizeStorage[k]) >500)
{
tSpot = k; //500이 차이나면 따로 넣을곳 정리
break;
}
}
for (int k = tSpot + 1; k < configureRectSizeStorage.size(); k++)
{
if (tSpot == -1)
configureRect.push_back(configureRectSizeStorage[tagain++]); //그냥 집어 넣음
else
configureRect.push_back(configureRectSizeStorage[k]); //81개 네모 영역만 집어넣음
}
int minRectSize2 = configureRect.front(); //최소 네모 사이즈
int maxRectSize2 = configureRect[configureRect.size() - 1]; //최대 네모 사이즈
Mat lastConfigure;
for (int k = 0; k < cutSize3.size(); k++)
{
cvtColor(contourImage, lastConfigure, COLOR_GRAY2BGR);
//imshow("testImage", testImage);
r = boundingRect(cutSize3[k]);
Rect ROI2(r.x, r.y, r.width, r.height);
//cout << r.size() << endl;
rectangle(lastConfigure, ROI2, Scalar(128, 255, 255), 2);//그림
if ((minRectSize2 <= (r.width*r.height)) && ((r.width*r.height) <= maxRectSize2))
countRect.push_back(ROI2); //해당 영역만 비교 하기 위해 넣어줌
//imshow("lastConfigure", lastConfigure);
//waitKey();
}
vector<int>params; //압축양식사용
params.push_back(IMWRITE_JPEG_QUALITY);
params.push_back(9);
imwrite("sudoOnly.jpg", newImage, params);
Mat sudokuImage = imread("sudoOnly.jpg", IMREAD_GRAYSCALE);
Mat realImage = imread("sudoOnly.jpg", IMREAD_GRAYSCALE);
Mat testSudo = sudokuImage.clone(); //나중에 확인할거
Size size(5, 5);
Mat rectKernel = getStructuringElement(MORPH_RECT, size);
Mat elipseKernel = getStructuringElement(MORPH_ELLIPSE, size);
Mat crossKernel = getStructuringElement(MORPH_CROSS, size);
if (countRect.size() != 81)
{
cout << "안되지롱" << endl;
waitKey();
goto jumpThreshold;
}
threshold(sudokuImage, sudokuImage, 230, 255, THRESH_BINARY); //영상 이진화
imshow("teswtsteswtse", sudokuImage);
waitKey();
goto jumpAdaptiveThreshold;
//morphologyEx(sudokuImage, sudokuImage, MORPH_CLOSE, rectKernel, Point(-1, -1), 1);
jumpThreshold:
//threshold(sudokuImage, sudokuImage, 200, 255, THRESH_BINARY);
//threshold(sudokuImage, sudokuImage, 200, 255, THRESH_OTSU+THRESH_BINARY); //영상 이진화
adaptiveThreshold(sudokuImage, sudokuImage, 255, ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY, 21, 1);
//morphologyEx(sudokuImage, sudokuImage, MORPH_GRADIENT, crossKernel, Point(-1, -1), 1);
erode(sudokuImage, sudokuImage, crossKernel, Point(-1, -1), 1);
dilate(sudokuImage, sudokuImage, elipseKernel, Point(-1, -1), 1);
jumpAdaptiveThreshold:
imshow("sudokuImage", sudokuImage);
waitKey();
Mat testImage = realImage.clone();//스도쿠 된것만 복사시킴
Mat resultImage(testImage.size(), CV_8UC3);
Mat testSudoImage(realImage.size(), CV_8UC3);
vector<int> rectSizeStorage; //빈칸과 숫자칸 저장
vector<int> realRect; //빈칸숫자칸의 최대 최소값을 알기위해 만듬
vector<Rect> sudokuRect; //칸마다 잘라진 영역 저장된곳
vector<Rect> temp;
threshold(testImage, testImage, 200, 255, THRESH_OTSU + THRESH_BINARY);
//waitKey();
findContours(sudokuImage, AfterContoursforSmallRectangle, hierarchy2, mode2, method2);
//스도쿠 원형만 자른곳에서 다시 경계선 그림
for (int k = 0; k < AfterContoursforSmallRectangle.size(); k++)
{
cutSize2.push_back(AfterContoursforSmallRectangle[k]); //그 경계선위치들을 넣음
}
for (int k = 0; k < cutSize2.size(); k++)
{
//
cvtColor(testImage, resultImage, COLOR_GRAY2BGR);
r = boundingRect(cutSize2[k]);//영역 사각형으로 감쌈
Rect ROI2(r.x, r.y, r.width, r.height);
drawContours(resultImage, cutSize2, k, Scalar(255, 0, 0), 4); //경계선 그림
//cout << r.size() << endl;
rectangle(resultImage, ROI2, Scalar(128, 255, 255), 2);//네모로 크림
if ((r.width*r.height)>(resultImage.rows*resultImage.cols) - 20000)
{ //최대영역은 받지 않음
//imshow("resultImage", resultImage);
//waitKey();
goto here;
}
rectSizeStorage.push_back(r.width*r.height); //sorting하기 위해 정리
here:{}
circle(resultImage, cutSize2[k][0], 5, Scalar(123, 123, 123), -1);
//imshow("resultImage", resultImage);
//waitKey();
}
sort(rectSizeStorage.begin(), rectSizeStorage.end());
eraseSpot = -1;
again = 0;
for (int k = 0; k < rectSizeStorage.size(); k++)
{
if (k == rectSizeStorage.size() - 1)
break;
if ((rectSizeStorage[k + 1] - rectSizeStorage[k]) >500)
{
eraseSpot = k; //500이 차이나면 따로 넣을곳 정리
}
}
for (int k = eraseSpot + 1; k < rectSizeStorage.size(); k++)
{
if (eraseSpot == -1)
realRect.push_back(rectSizeStorage[again++]); //그냥 집어 넣음
else
realRect.push_back(rectSizeStorage[k]); //81개 네모 영역만 집어넣음
}
//소팅이 이미 되서 들어가므로 할 필요 없음
int minRectSize = realRect.front(); //최소 네모 사이즈
int maxRectSize = realRect[realRect.size() - 1]; //최대 네모 사이즈
for (int k = 0; k < cutSize2.size(); k++)
{
cvtColor(testImage, resultImage, COLOR_GRAY2BGR);
//imshow("testImage", testImage);
r = boundingRect(cutSize2[k]);
Rect ROI2(r.x, r.y, r.width, r.height);
//cout << r.size() << endl;
rectangle(resultImage, ROI2, Scalar(128, 255, 255), 2);//그림
if ((minRectSize <= (r.width*r.height)) && ((r.width*r.height) <= maxRectSize))
temp.push_back(ROI2); //해당 영역만 비교 하기 위해 넣어줌
// imshow("resultImage2", resultImage);
//waitKey();
}
for (int k = temp.size() - 1; k >= 0; k--)
sudokuRect.push_back(temp[k]); //반대로 시작하므로 처음1칸부터 비교하기위해 역으로 넣음
temp.clear();
vector<int> testSortingOk;
//각 줄이 순서대로 소팅이 안되있으므로 각 줄마다 왼쪽부터 오른쪽으로 되게 바꿈
for (int i = 0; i < 81; i += 9)
{
int ty = sudokuRect[i].y;
int ti = i;
testSortingOk.clear();
for (int j = i; j < ti + 9; j++)
{
testSortingOk.push_back(sudokuRect[j].x);
}
sort(testSortingOk.begin(), testSortingOk.end());
int k = 0;
for (int j = i; j < ti + 9; j++)
{
if (testSortingOk[k] == sudokuRect[j].x)
temp.push_back(sudokuRect[j]);
else
{
for (int t = i; t <= ti + 9; t++)
{
if (testSortingOk[k] == sudokuRect[t].x)
{
temp.push_back(sudokuRect[t]);
break;
}
}
}
k++;
}
}
sudokuRect.clear();
erode(resultImage, resultImage, crossKernel, Point(-1, -1), 1);
dilate(resultImage, resultImage, elipseKernel, Point(-1, -1), 1);
for (int k = 0; k < temp.size(); k++)
sudokuRect.push_back(temp[k]);
for (int k = 0; k < sudokuRect.size(); k++)
{
rectangle(resultImage, sudokuRect[k], Scalar(128, 255, 255), 2);//그림
imshow("testSudoImage34", resultImage);
waitKey();
}
const char *path = "/tessdate";
TessBaseAPI tess; //tesseract 선언
//TessBaseAPI *api = new TessBaseAPI();
tess.Init(NULL, "eng", tesseract::OEM_DEFAULT); //한국어로 인식 기본 숫자 되어있음
/*
if (api->Init(NULL, "eng"))
{
fprintf(stderr, "could not initailze teseract\n");
exit(1);
}
*/
string tessRecogNum[81][1]; //글자로 인식해오므로 넣을곳 만들어줌
int sudoTestte[81]; //스도쿠 번호 넣을곳을 만들어줌
int d = 0;
for (int i = 0; i<sudokuRect.size(); i++)
{
cvtColor(testSudo, testSudoImage, COLOR_GRAY2BGR);
rectangle(testSudoImage, sudokuRect[i], Scalar(128, 255, 255), 2);//그림
Mat cutImage = testSudo(sudokuRect[i]);
// imshow("cutImage", cutImage);
Mat tempImage = repeat(cutImage, 1, 1);
Mat numberImage = tempImage.clone();//스도쿠 된것만 복사시킴
//imshow("numberImage", numberImage);
imwrite("numberImage.jpg", numberImage, params);
Mat resultNImage(tempImage.size(), CV_8UC3);
waitKey();
int height = tempImage.size().height;
int width = tempImage.size().width;
int continueNum = 0; //0이 계속되는 수 선언
int testPixel = (height*width); //최대 픽셀 받아옴
//그 칸이 빈칸일 경우 골라서 0을 넣음
/*
for (int a = 0; a < tempImage.rows; a++)
{
for (int b = 0; b < tempImage.cols; b++)
{
float te = tempImage.at<uchar>(a, b);
if (continueNum >= testPixel)
break;
if (te >= 190 && te <= 200)
tempImage.at<uchar>(a, b) = 255;
if (te > 200)
continueNum++;
}
if (continueNum >= (testPixel - 10))
break;
}
*/
if (continueNum >= testPixel){
sudoTestte[d++] = atoi("0");
tessRecogNum[i][0] = '0';
continue;
}
//imshow("tempImage", tempImage);
//waitKey();
tess.SetImage((uchar*)tempImage.data, tempImage.size().width, tempImage.size().height, tempImage.channels(), tempImage.step1()); //이미지의 데이터 넓이 높이와 채널을 받아옴
//Pix *image = pixRead("numberImage.jpg");
//api->SetImage(image);
//
tess.Recognize(0); //인식 시킴
const char * out = tess.GetUTF8Text(); //그걸 utf8text로 인식시킴
//const char * out = api.GetUTF8Text();
tessRecogNum[i][0] = out;
if (atoi(out) > 9 || atoi(out) < 0)
sudoTestte[d++] = 0;
else
sudoTestte[d++] = atoi(out);
//printf("%s", out);
//cout << endl;
imshow("testSudoImage", testSudoImage);
//waitKey();
}
cout << endl;
for (int i = 0; i < 81; i++)
{
if (i % 9 == 0 && i>1)
cout << endl;
cout << sudoTestte[i] << " ";
}
waitKey();
return 0;
}
int main(int argc, char* argv[]) {
const char* name_main = "Plate Recognition";
const char* name_edge = "Edge Window";
#if defined(__DMDEBUG)
const char* name_mask = "Mask Window";
#endif
const char* name_bwframe = "BW Window";
const char* name_crop = "CROP Window";
const char* name_ctrl = "Control Window";
unsigned int i;
Mat frame;
Mat bwframe;
Mat edge;
TessBaseAPI *OCR = new TessBaseAPI();
if(OCR->Init(NULL, "eng")) {
cout << "Could not initialize tesseract OCR\n";
return -1;
}
if( argc != 2) {
cout << "You must specify a file to load\n";
return -1;
}
VideoCapture cap(argv[1]);
if(!cap.isOpened()) {
cout << "Cannot open file " << argv[1] << endl;
return -1;
}
namedWindow(name_main, 0);
namedWindow(name_edge, 0);
#if defined(__DMDEBUG)
namedWindow(name_mask, 0);
#endif
namedWindow(name_bwframe, 0);
namedWindow(name_ctrl, 0);
//#if defined(__DMDEBUG)
namedWindow(name_crop, 0);
namedWindow("AAA", 0);
//#endif
createTrackbar( "Contour perimeter", name_ctrl, &high_switch_value, 100, switch_callback_h, NULL );
createTrackbar( "Min area", name_ctrl, &minimum_area, 100000, NULL, NULL);
createTrackbar( "Max area", name_ctrl, &maximum_area, 100000, NULL, NULL);
createTrackbar( "Threshold", name_ctrl, &threshold_val, 255, NULL, NULL);
//createTrackbar( "thr size", name_ctrl, &athr_size, 255, athr_callback, &athr_size);
createTrackbar( "Plate Thr", name_ctrl, &threshold2_val, 255, NULL, NULL);
//createTrackbar( "PThr size", name_ctrl, &athr2_size, 255, athr_callback, &athr2_size);
waitKey();
for(;;) {
//try {
cap >> frame;
//} catch(int e) {
// frame = imread(argv[1], 3);
//}
cvtColor(frame, bwframe, CV_RGB2GRAY);
imshow(name_bwframe, bwframe);
// extract V channel from HSV image
Mat vframe(frame.rows, frame.cols, CV_8UC1);
Mat tvframe(frame.rows, frame.cols, CV_8UC3);
cvtColor(frame, tvframe, CV_RGB2HSV);
int from_to[] = { 2,0 };
mixChannels( &tvframe, 1, &vframe,1, from_to, 1);
// maximize contrast
// https://github.com/oesmith/OpenANPR/blob/master/anpr/preprocess.py
Mat el=getStructuringElement(MORPH_ELLIPSE, Size(3,3), Point(1,1));
Mat bh(vframe.rows, vframe.cols, CV_8UC1);
Mat th(vframe.rows, vframe.cols, CV_8UC1);
Mat s1(vframe.rows, vframe.cols, CV_8UC1);
morphologyEx(vframe, th, MORPH_TOPHAT, el, Point(1,1), 1);
morphologyEx(vframe, bh, MORPH_BLACKHAT, el, Point(1,1), 1);
add(vframe, th, s1);
subtract(s1,bh, vframe);
// Smooth image to remove rumor
GaussianBlur(vframe, vframe, Size(5,5), 5, 5, BORDER_DEFAULT);
imshow("AAA", vframe);
// apply your filter
Canny(bwframe, edge, threshold_val, 255);
//Canny(vframe, edge, threshold_val, 255);
//threshold( bwframe, edge, threshold_val, 255, CV_THRESH_BINARY );
//threshold( vframe, edge, threshold_val, 255, CV_THRESH_BINARY );
//adaptiveThreshold(bwframe, edge, threshold_val,
// CV_ADAPTIVE_THRESH_GAUSSIAN_C, CV_THRESH_BINARY, athr_size, 5);
// OR CV_ADAPTIVE_THRES_MEAN_C
//adaptiveThreshold(vframe, edge, threshold_val, CV_ADAPTIVE_THRESH_GAUSSIAN_C, CV_THRESH_BINARY_INV, athr_size, 9);
// find the contours
vector< vector<Point> > contours;
findContours(edge, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
vector<double> areas(contours.size());
for( i = 0; i < contours.size(); i++) {
areas[i] = fabs(contourArea(Mat(contours[i])));
if(areas[i] >= minimum_area && areas[i] <= maximum_area) {
vector<Point> results;
approxPolyDP(Mat(contours[i]), results, arcLength(Mat(contours[i]),1)*perimeter_constant,1);
if (results.size() == 4 && isContourConvex(results)){
// you could also reuse bwframe here
Mat mask = Mat::zeros(bwframe.rows, bwframe.cols, CV_8UC1);
// CV_FILLED fills the connected components found
drawContours(mask, contours, i, Scalar(255,255,255), CV_FILLED);
// draw contours to cover plate external lines
drawContours(bwframe, contours, i, Scalar(255,255,255), 2, 2);
Rect box = boundingRect(Mat(contours[i]));
// let's create a new image now
Mat crop(frame.rows, frame.cols, CV_8UC1);
// set background color to black
//crop.setTo(Scalar(0,0,0));
crop.setTo(Scalar(0));
// and copy the magic apple
bwframe.copyTo(crop, mask);
// normalize so imwrite(...)/imshow(...) shows the mask correctly!
normalize(mask.clone(), mask, 0.0, 255.0, CV_MINMAX, CV_8UC1);
//rectangle(crop, box, Scalar(0,0,255) ,3);
Mat roi(crop, box);
// Image for OCR
Mat ocrimg(roi.rows, roi.cols, CV_8UC1);
ocrimg.setTo(Scalar(255));
roi.copyTo(ocrimg, roi);
int scalefactor = 1000/ocrimg.cols;
//cout << "Scale factor: " << scalefactor << endl;;
resize(ocrimg, ocrimg, Size(0,0), scalefactor, scalefactor, CV_INTER_CUBIC);
threshold(ocrimg, ocrimg, threshold2_val, 255, CV_THRESH_BINARY );
//adaptiveThreshold(ocrimg, ocrimg, threshold2_val,
// CV_ADAPTIVE_THRESH_GAUSSIAN_C, CV_THRESH_BINARY, athr2_size, 5);
//Canny(ocrimg, ocrimg, threshold2_val, 255);
//#if defined(__DMDEBUG)
imshow(name_crop, ocrimg);
//#endif
rectangle(frame, box, Scalar(0,0,255), 3);
rectangle(bwframe, box, Scalar(0,0,255), 3);
#if defined(__DMDEBUG)
imshow(name_mask, mask);
#endif
//OCR->TesseractRect(roi.data, 1, roi.step1(), 0,0,roi.cols, roi.rows);
OCR->SetImage((uchar*)ocrimg.data, ocrimg.size().width, ocrimg.size().height,
ocrimg.channels(), ocrimg.step1());
OCR->Recognize(0);
char* detected_text = OCR->GetUTF8Text();
//cout << "Size text: " << strlen(detected_text) << endl;
if(strlen(detected_text) > 0) {
cout << "License plate number: " << detected_text << endl;
//#if !defined(__DMDEBUG)
//imshow(name_crop, ocrimg);
//#endif
imshow(name_main, frame);
imshow(name_bwframe, bwframe);
imshow(name_edge, edge);
imshow(name_ctrl, ocrimg);
#if defined(__DMDEBUG)
imwrite("antani.jpg", ocrimg);
#endif
waitKey();
//#endif
}
}
}
}
imshow(name_main, frame);
imshow(name_bwframe, bwframe);
imshow(name_edge, edge);
if(waitKey(30) >= 0) break;
}
return 0;
}