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Make imgproc.hpp independent from C API

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This commit is contained in:
Andrey Kamaev
2013-04-06 18:16:51 +04:00
parent 7ac0d86992
commit 288a0634c2
95 changed files with 1400 additions and 1300 deletions
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4
samples/cpp/3calibration.cpp
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@@ -271,7 +271,7 @@ int main( int argc, char** argv )
{
vector<Point2f> ptvec;
imageSize = view.size();
cvtColor(view, viewGray, CV_BGR2GRAY);
cvtColor(view, viewGray, COLOR_BGR2GRAY);
bool found = findChessboardCorners( view, boardSize, ptvec, CV_CALIB_CB_ADAPTIVE_THRESH );
drawChessboardCorners( view, boardSize, Mat(ptvec), found );
@@ -359,7 +359,7 @@ int main( int argc, char** argv )
continue;
Mat rview = canvas.colRange(k2*imageSize.width, (k2+1)*imageSize.width);
remap(view, rview, map1[k1], map2[k1], CV_INTER_LINEAR);
remap(view, rview, map1[k1], map2[k1], INTER_LINEAR);
}
printf("%s %s %s\n", imageList[i*3].c_str(), imageList[i*3+1].c_str(), imageList[i*3+2].c_str());
resize( canvas, small_canvas, Size(1500, 1500/3) );

2
samples/cpp/build3dmodel.cpp
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@@ -509,7 +509,7 @@ static void build3dmodel( const Ptr<FeatureDetector>& detector,
for( size_t i = 0; i < nimages; i++ )
{
Mat img = imread(imageList[i], 1), gray;
cvtColor(img, gray, CV_BGR2GRAY);
cvtColor(img, gray, COLOR_BGR2GRAY);
vector<KeyPoint> keypoints;
detector->detect(gray, keypoints);

2
samples/cpp/calibration.cpp
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@@ -462,7 +462,7 @@ int main( int argc, char** argv )
flip( view, view, 0 );
vector<Point2f> pointbuf;
cvtColor(view, viewGray, CV_BGR2GRAY);
cvtColor(view, viewGray, COLOR_BGR2GRAY);
bool found;
switch( pattern )

2
samples/cpp/chamfer.cpp
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@@ -41,7 +41,7 @@ int main( int argc, const char** argv )
return -1;
}
Mat cimg;
cvtColor(img, cimg, CV_GRAY2BGR);
cvtColor(img, cimg, COLOR_GRAY2BGR);
// if the image and the template are not edge maps but normal grayscale images,
// you might want to uncomment the lines below to produce the maps. You can also

2
samples/cpp/detection_based_tracker_sample.cpp
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@@ -144,7 +144,7 @@ static int test_FaceDetector(int argc, char *argv[])
LOGD("\n\nSTEP n=%d from prev step %f ms\n", n, t_ms);
m=images[n-1];
CV_Assert(! m.empty());
cvtColor(m, gray, CV_BGR2GRAY);
cvtColor(m, gray, COLOR_BGR2GRAY);
fd.process(gray);

42
samples/cpp/distrans.cpp
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@@ -7,10 +7,10 @@
using namespace std;
using namespace cv;
int maskSize0 = CV_DIST_MASK_5;
int maskSize0 = DIST_MASK_5;
int voronoiType = -1;
int edgeThresh = 100;
int distType0 = CV_DIST_L1;
int distType0 = DIST_L1;
// The output and temporary images
Mat gray;
@@ -31,8 +31,8 @@ static void onTrackbar( int, void* )
Scalar(255,0,255)
};
int maskSize = voronoiType >= 0 ? CV_DIST_MASK_5 : maskSize0;
int distType = voronoiType >= 0 ? CV_DIST_L2 : distType0;
int maskSize = voronoiType >= 0 ? DIST_MASK_5 : maskSize0;
int distType = voronoiType >= 0 ? DIST_L2 : distType0;
Mat edge = gray >= edgeThresh, dist, labels, dist8u;
@@ -140,17 +140,17 @@ int main( int argc, const char** argv )
voronoiType = -1;
if( c == 'c' || c == 'C' )
distType0 = CV_DIST_C;
distType0 = DIST_C;
else if( c == '1' )
distType0 = CV_DIST_L1;
distType0 = DIST_L1;
else if( c == '2' )
distType0 = CV_DIST_L2;
distType0 = DIST_L2;
else if( c == '3' )
maskSize0 = CV_DIST_MASK_3;
maskSize0 = DIST_MASK_3;
else if( c == '5' )
maskSize0 = CV_DIST_MASK_5;
maskSize0 = DIST_MASK_5;
else if( c == '0' )
maskSize0 = CV_DIST_MASK_PRECISE;
maskSize0 = DIST_MASK_PRECISE;
else if( c == 'v' )
voronoiType = 0;
else if( c == 'p' )
@@ -162,18 +162,18 @@ int main( int argc, const char** argv )
else if( voronoiType == 1 )
{
voronoiType = -1;
maskSize0 = CV_DIST_MASK_3;
distType0 = CV_DIST_C;
maskSize0 = DIST_MASK_3;
distType0 = DIST_C;
}
else if( distType0 == CV_DIST_C )
distType0 = CV_DIST_L1;
else if( distType0 == CV_DIST_L1 )
distType0 = CV_DIST_L2;
else if( maskSize0 == CV_DIST_MASK_3 )
maskSize0 = CV_DIST_MASK_5;
else if( maskSize0 == CV_DIST_MASK_5 )
maskSize0 = CV_DIST_MASK_PRECISE;
else if( maskSize0 == CV_DIST_MASK_PRECISE )
else if( distType0 == DIST_C )
distType0 = DIST_L1;
else if( distType0 == DIST_L1 )
distType0 = DIST_L2;
else if( maskSize0 == DIST_MASK_3 )
maskSize0 = DIST_MASK_5;
else if( maskSize0 == DIST_MASK_5 )
maskSize0 = DIST_MASK_PRECISE;
else if( maskSize0 == DIST_MASK_PRECISE )
voronoiType = 0;
}
}

2
samples/cpp/edge.cpp
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@@ -50,7 +50,7 @@ int main( int argc, const char** argv )
return -1;
}
cedge.create(image.size(), image.type());
cvtColor(image, gray, CV_BGR2GRAY);
cvtColor(image, gray, COLOR_BGR2GRAY);
// Create a window
namedWindow("Edge map", 1);

10
samples/cpp/ffilldemo.cpp
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@@ -41,7 +41,7 @@ static void onMouse( int event, int x, int y, int, void* )
int lo = ffillMode == 0 ? 0 : loDiff;
int up = ffillMode == 0 ? 0 : upDiff;
int flags = connectivity + (newMaskVal << 8) +
(ffillMode == 1 ? CV_FLOODFILL_FIXED_RANGE : 0);
(ffillMode == 1 ? FLOODFILL_FIXED_RANGE : 0);
int b = (unsigned)theRNG() & 255;
int g = (unsigned)theRNG() & 255;
int r = (unsigned)theRNG() & 255;
@@ -53,7 +53,7 @@ static void onMouse( int event, int x, int y, int, void* )
if( useMask )
{
threshold(mask, mask, 1, 128, CV_THRESH_BINARY);
threshold(mask, mask, 1, 128, THRESH_BINARY);
area = floodFill(dst, mask, seed, newVal, &ccomp, Scalar(lo, lo, lo),
Scalar(up, up, up), flags);
imshow( "mask", mask );
@@ -81,7 +81,7 @@ int main( int argc, char** argv )
}
help();
image0.copyTo(image);
cvtColor(image0, gray, CV_BGR2GRAY);
cvtColor(image0, gray, COLOR_BGR2GRAY);
mask.create(image0.rows+2, image0.cols+2, CV_8UC1);
namedWindow( "image", 0 );
@@ -106,7 +106,7 @@ int main( int argc, char** argv )
if( isColor )
{
cout << "Grayscale mode is set\n";
cvtColor(image0, gray, CV_BGR2GRAY);
cvtColor(image0, gray, COLOR_BGR2GRAY);
mask = Scalar::all(0);
isColor = false;
}
@@ -135,7 +135,7 @@ int main( int argc, char** argv )
case 'r':
cout << "Original image is restored\n";
image0.copyTo(image);
cvtColor(image, gray, CV_BGR2GRAY);
cvtColor(image, gray, COLOR_BGR2GRAY);
mask = Scalar::all(0);
break;
case 's':

2
samples/cpp/fitellipse.cpp
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@@ -64,7 +64,7 @@ void processImage(int /*h*/, void*)
vector<vector<Point> > contours;
Mat bimage = image >= sliderPos;
findContours(bimage, contours, CV_RETR_LIST, CV_CHAIN_APPROX_NONE);
findContours(bimage, contours, RETR_LIST, CHAIN_APPROX_NONE);
Mat cimage = Mat::zeros(bimage.size(), CV_8UC3);

4
samples/cpp/houghcircles.cpp
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@@ -27,10 +27,10 @@ int main(int argc, char** argv)
Mat cimg;
medianBlur(img, img, 5);
cvtColor(img, cimg, CV_GRAY2BGR);
cvtColor(img, cimg, COLOR_GRAY2BGR);
vector<Vec3f> circles;
HoughCircles(img, circles, CV_HOUGH_GRADIENT, 1, 10,
HoughCircles(img, circles, HOUGH_GRADIENT, 1, 10,
100, 30, 1, 30 // change the last two parameters
// (min_radius & max_radius) to detect larger circles
);

2
samples/cpp/houghlines.cpp
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@@ -27,7 +27,7 @@ int main(int argc, char** argv)
Mat dst, cdst;
Canny(src, dst, 50, 200, 3);
cvtColor(dst, cdst, CV_GRAY2BGR);
cvtColor(dst, cdst, COLOR_GRAY2BGR);
#if 0
vector<Vec2f> lines;

4
samples/cpp/image.cpp
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@@ -49,7 +49,7 @@ int main( int argc, char** argv )
return -1;
Mat img_yuv;
cvtColor(img, img_yuv, CV_BGR2YCrCb); // convert image to YUV color space. The output image will be created automatically
cvtColor(img, img_yuv, COLOR_BGR2YCrCb); // convert image to YUV color space. The output image will be created automatically
vector<Mat> planes; // Vector is template vector class, similar to STL's vector. It can store matrices too.
split(img_yuv, planes); // split the image into separate color planes
@@ -107,7 +107,7 @@ int main( int argc, char** argv )
// now merge the results back
merge(planes, img_yuv);
// and produce the output RGB image
cvtColor(img_yuv, img, CV_YCrCb2BGR);
cvtColor(img_yuv, img, COLOR_YCrCb2BGR);
// this is counterpart for cvNamedWindow
namedWindow("image with grain", CV_WINDOW_AUTOSIZE);

10
samples/cpp/laplace.cpp
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@@ -17,8 +17,10 @@ static void help()
"./laplace [camera #, default 0]\n" << endl;
}
enum {GAUSSIAN, BLUR, MEDIAN};
int sigma = 3;
int smoothType = CV_GAUSSIAN;
int smoothType = GAUSSIAN;
int main( int argc, char** argv )
{
@@ -63,9 +65,9 @@ int main( int argc, char** argv )
break;
int ksize = (sigma*5)|1;
if(smoothType == CV_GAUSSIAN)
if(smoothType == GAUSSIAN)
GaussianBlur(frame, smoothed, Size(ksize, ksize), sigma, sigma);
else if(smoothType == CV_BLUR)
else if(smoothType == BLUR)
blur(frame, smoothed, Size(ksize, ksize));
else
medianBlur(frame, smoothed, ksize);
@@ -76,7 +78,7 @@ int main( int argc, char** argv )
int c = waitKey(30);
if( c == ' ' )
smoothType = smoothType == CV_GAUSSIAN ? CV_BLUR : smoothType == CV_BLUR ? CV_MEDIAN : CV_GAUSSIAN;
smoothType = smoothType == GAUSSIAN ? BLUR : smoothType == BLUR ? MEDIAN : GAUSSIAN;
if( c == 'q' || c == 'Q' || (c & 255) == 27 )
break;
}

4
samples/cpp/morphology2.cpp
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@@ -37,9 +37,9 @@ static void OpenClose(int, void*)
int an = n > 0 ? n : -n;
Mat element = getStructuringElement(element_shape, Size(an*2+1, an*2+1), Point(an, an) );
if( n < 0 )
morphologyEx(src, dst, CV_MOP_OPEN, element);
morphologyEx(src, dst, MORPH_OPEN, element);
else
morphologyEx(src, dst, CV_MOP_CLOSE, element);
morphologyEx(src, dst, MORPH_CLOSE, element);
imshow("Open/Close",dst);
}

2
samples/cpp/phase_corr.cpp
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@@ -13,7 +13,7 @@ int main(int, char* [])
do
{
video >> frame;
cvtColor(frame, curr, CV_RGB2GRAY);
cvtColor(frame, curr, COLOR_RGB2GRAY);
if(prev.empty())
{

4
samples/cpp/rgbdodometry.cpp
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@@ -125,8 +125,8 @@ int main(int argc, char** argv)
}
Mat grayImage0, grayImage1, depthFlt0, depthFlt1/*in meters*/;
cvtColor( colorImage0, grayImage0, CV_BGR2GRAY );
cvtColor( colorImage1, grayImage1, CV_BGR2GRAY );
cvtColor( colorImage0, grayImage0, COLOR_BGR2GRAY );
cvtColor( colorImage1, grayImage1, COLOR_BGR2GRAY );
depth0.convertTo( depthFlt0, CV_32FC1, 1./1000 );
depth1.convertTo( depthFlt1, CV_32FC1, 1./1000 );

2
samples/cpp/segment_objects.cpp
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@@ -30,7 +30,7 @@ static void refineSegments(const Mat& img, Mat& mask, Mat& dst)
erode(temp, temp, Mat(), Point(-1,-1), niters*2);
dilate(temp, temp, Mat(), Point(-1,-1), niters);
findContours( temp, contours, hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE );
findContours( temp, contours, hierarchy, RETR_CCOMP, CHAIN_APPROX_SIMPLE );
dst = Mat::zeros(img.size(), CV_8UC3);

2
samples/cpp/squares.cpp
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@@ -83,7 +83,7 @@ static void findSquares( const Mat& image, vector<vector<Point> >& squares )
}
// find contours and store them all as a list
findContours(gray, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);
findContours(gray, contours, RETR_LIST, CHAIN_APPROX_SIMPLE);
vector<Point> approx;

8
samples/cpp/stereo_calib.cpp
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@@ -121,7 +121,7 @@ StereoCalib(const vector<string>& imagelist, Size boardSize, bool useCalibrated=
{
cout << filename << endl;
Mat cimg, cimg1;
cvtColor(img, cimg, CV_GRAY2BGR);
cvtColor(img, cimg, COLOR_GRAY2BGR);
drawChessboardCorners(cimg, boardSize, corners, found);
double sf = 640./MAX(img.rows, img.cols);
resize(cimg, cimg1, Size(), sf, sf);
@@ -304,10 +304,10 @@ StereoCalib(const vector<string>& imagelist, Size boardSize, bool useCalibrated=
for( k = 0; k < 2; k++ )
{
Mat img = imread(goodImageList[i*2+k], 0), rimg, cimg;
remap(img, rimg, rmap[k][0], rmap[k][1], CV_INTER_LINEAR);
cvtColor(rimg, cimg, CV_GRAY2BGR);
remap(img, rimg, rmap[k][0], rmap[k][1], INTER_LINEAR);
cvtColor(rimg, cimg, COLOR_GRAY2BGR);
Mat canvasPart = !isVerticalStereo ? canvas(Rect(w*k, 0, w, h)) : canvas(Rect(0, h*k, w, h));
resize(cimg, canvasPart, canvasPart.size(), 0, 0, CV_INTER_AREA);
resize(cimg, canvasPart, canvasPart.size(), 0, 0, INTER_AREA);
if( useCalibrated )
{
Rect vroi(cvRound(validRoi[k].x*sf), cvRound(validRoi[k].y*sf),

2
samples/cpp/tutorial_code/Histograms_Matching/EqualizeHist_Demo.cpp
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@@ -31,7 +31,7 @@ int main( int, char** argv )
}
/// Convert to grayscale
cvtColor( src, src, CV_BGR2GRAY );
cvtColor( src, src, COLOR_BGR2GRAY );
/// Apply Histogram Equalization
equalizeHist( src, dst );

2
samples/cpp/tutorial_code/Histograms_Matching/MatchTemplate_Demo.cpp
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@@ -74,7 +74,7 @@ void MatchingMethod( int, void* )
/// For SQDIFF and SQDIFF_NORMED, the best matches are lower values. For all the other methods, the higher the better
if( match_method == CV_TM_SQDIFF || match_method == CV_TM_SQDIFF_NORMED )
if( match_method == TM_SQDIFF || match_method == TM_SQDIFF_NORMED )
{ matchLoc = minLoc; }
else
{ matchLoc = maxLoc; }

2
samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo1.cpp
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@@ -28,7 +28,7 @@ int main( int, char** argv )
/// Read the image
src = imread( argv[1], 1 );
/// Transform it to HSV
cvtColor( src, hsv, CV_BGR2HSV );
cvtColor( src, hsv, COLOR_BGR2HSV );
/// Use only the Hue value
hue.create( hsv.size(), hsv.depth() );

2
samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo2.cpp
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@@ -31,7 +31,7 @@ int main( int, char** argv )
/// Read the image
src = imread( argv[1], 1 );
/// Transform it to HSV
cvtColor( src, hsv, CV_BGR2HSV );
cvtColor( src, hsv, COLOR_BGR2HSV );
/// Show the image
namedWindow( window_image, CV_WINDOW_AUTOSIZE );

6
samples/cpp/tutorial_code/Histograms_Matching/compareHist_Demo.cpp
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@@ -33,9 +33,9 @@ int main( int argc, char** argv )
src_test2 = imread( argv[3], 1 );
/// Convert to HSV
cvtColor( src_base, hsv_base, CV_BGR2HSV );
cvtColor( src_test1, hsv_test1, CV_BGR2HSV );
cvtColor( src_test2, hsv_test2, CV_BGR2HSV );
cvtColor( src_base, hsv_base, COLOR_BGR2HSV );
cvtColor( src_test1, hsv_test1, COLOR_BGR2HSV );
cvtColor( src_test2, hsv_test2, COLOR_BGR2HSV );
hsv_half_down = hsv_base( Range( hsv_base.rows/2, hsv_base.rows - 1 ), Range( 0, hsv_base.cols - 1 ) );

2
samples/cpp/tutorial_code/ImgProc/Threshold.cpp
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@@ -37,7 +37,7 @@ int main( int, char** argv )
src = imread( argv[1], 1 );
/// Convert the image to Gray
cvtColor( src, src_gray, CV_RGB2GRAY );
cvtColor( src, src_gray, COLOR_RGB2GRAY );
/// Create a window to display results
namedWindow( window_name, CV_WINDOW_AUTOSIZE );

2
samples/cpp/tutorial_code/ImgTrans/CannyDetector_Demo.cpp
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@@ -58,7 +58,7 @@ int main( int, char** argv )
dst.create( src.size(), src.type() );
/// Convert the image to grayscale
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
/// Create a window
namedWindow( window_name, CV_WINDOW_AUTOSIZE );

4
samples/cpp/tutorial_code/ImgTrans/HoughCircle_Demo.cpp
View File

@@ -26,7 +26,7 @@ int main(int, char** argv)
{ return -1; }
/// Convert it to gray
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
/// Reduce the noise so we avoid false circle detection
GaussianBlur( src_gray, src_gray, Size(9, 9), 2, 2 );
@@ -34,7 +34,7 @@ int main(int, char** argv)
vector<Vec3f> circles;
/// Apply the Hough Transform to find the circles
HoughCircles( src_gray, circles, CV_HOUGH_GRADIENT, 1, src_gray.rows/8, 200, 100, 0, 0 );
HoughCircles( src_gray, circles, HOUGH_GRADIENT, 1, src_gray.rows/8, 200, 100, 0, 0 );
/// Draw the circles detected
for( size_t i = 0; i < circles.size(); i++ )

6
samples/cpp/tutorial_code/ImgTrans/HoughLines_Demo.cpp
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@@ -46,7 +46,7 @@ int main( int, char** argv )
}
/// Pass the image to gray
cvtColor( src, src_gray, CV_RGB2GRAY );
cvtColor( src, src_gray, COLOR_RGB2GRAY );
/// Apply Canny edge detector
Canny( src_gray, edges, 50, 200, 3 );
@@ -85,7 +85,7 @@ void help()
void Standard_Hough( int, void* )
{
vector<Vec2f> s_lines;
cvtColor( edges, standard_hough, CV_GRAY2BGR );
cvtColor( edges, standard_hough, COLOR_GRAY2BGR );
/// 1. Use Standard Hough Transform
HoughLines( edges, s_lines, 1, CV_PI/180, min_threshold + s_trackbar, 0, 0 );
@@ -112,7 +112,7 @@ void Standard_Hough( int, void* )
void Probabilistic_Hough( int, void* )
{
vector<Vec4i> p_lines;
cvtColor( edges, probabilistic_hough, CV_GRAY2BGR );
cvtColor( edges, probabilistic_hough, COLOR_GRAY2BGR );
/// 2. Use Probabilistic Hough Transform
HoughLinesP( edges, p_lines, 1, CV_PI/180, min_threshold + p_trackbar, 30, 10 );

2
samples/cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp
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@@ -34,7 +34,7 @@ int main( int, char** argv )
GaussianBlur( src, src, Size(3,3), 0, 0, BORDER_DEFAULT );
/// Convert the image to grayscale
cvtColor( src, src_gray, CV_RGB2GRAY );
cvtColor( src, src_gray, COLOR_RGB2GRAY );
/// Create window
namedWindow( window_name, CV_WINDOW_AUTOSIZE );

2
samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp
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@@ -47,7 +47,7 @@ int main( int, char** argv )
/// Update map_x & map_y. Then apply remap
update_map();
remap( src, dst, map_x, map_y, CV_INTER_LINEAR, BORDER_CONSTANT, Scalar(0, 0, 0) );
remap( src, dst, map_x, map_y, INTER_LINEAR, BORDER_CONSTANT, Scalar(0, 0, 0) );
// Display results
imshow( remap_window, dst );

2
samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp
View File

@@ -33,7 +33,7 @@ int main( int, char** argv )
GaussianBlur( src, src, Size(3,3), 0, 0, BORDER_DEFAULT );
/// Convert it to gray
cvtColor( src, src_gray, CV_RGB2GRAY );
cvtColor( src, src_gray, COLOR_RGB2GRAY );
/// Create window
namedWindow( window_name, CV_WINDOW_AUTOSIZE );

4
samples/cpp/tutorial_code/ShapeDescriptors/findContours_demo.cpp
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@@ -30,7 +30,7 @@ int main( int, char** argv )
src = imread( argv[1], 1 );
/// Convert image to gray and blur it
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
blur( src_gray, src_gray, Size(3,3) );
/// Create Window
@@ -57,7 +57,7 @@ void thresh_callback(int, void* )
/// Detect edges using canny
Canny( src_gray, canny_output, thresh, thresh*2, 3 );
/// Find contours
findContours( canny_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );
findContours( canny_output, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0) );
/// Draw contours
Mat drawing = Mat::zeros( canny_output.size(), CV_8UC3 );

4
samples/cpp/tutorial_code/ShapeDescriptors/generalContours_demo1.cpp
View File

@@ -30,7 +30,7 @@ int main( int, char** argv )
src = imread( argv[1], 1 );
/// Convert image to gray and blur it
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
blur( src_gray, src_gray, Size(3,3) );
/// Create Window
@@ -57,7 +57,7 @@ void thresh_callback(int, void* )
/// Detect edges using Threshold
threshold( src_gray, threshold_output, thresh, 255, THRESH_BINARY );
/// Find contours
findContours( threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );
findContours( threshold_output, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0) );
/// Approximate contours to polygons + get bounding rects and circles
vector<vector<Point> > contours_poly( contours.size() );

4
samples/cpp/tutorial_code/ShapeDescriptors/generalContours_demo2.cpp
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@@ -30,7 +30,7 @@ int main( int, char** argv )
src = imread( argv[1], 1 );
/// Convert image to gray and blur it
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
blur( src_gray, src_gray, Size(3,3) );
/// Create Window
@@ -57,7 +57,7 @@ void thresh_callback(int, void* )
/// Detect edges using Threshold
threshold( src_gray, threshold_output, thresh, 255, THRESH_BINARY );
/// Find contours
findContours( threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );
findContours( threshold_output, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0) );
/// Find the rotated rectangles and ellipses for each contour
vector<RotatedRect> minRect( contours.size() );

4
samples/cpp/tutorial_code/ShapeDescriptors/hull_demo.cpp
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@@ -30,7 +30,7 @@ int main( int, char** argv )
src = imread( argv[1], 1 );
/// Convert image to gray and blur it
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
blur( src_gray, src_gray, Size(3,3) );
/// Create Window
@@ -59,7 +59,7 @@ void thresh_callback(int, void* )
threshold( src_gray, threshold_output, thresh, 255, THRESH_BINARY );
/// Find contours
findContours( threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );
findContours( threshold_output, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0) );
/// Find the convex hull object for each contour
vector<vector<Point> >hull( contours.size() );

4
samples/cpp/tutorial_code/ShapeDescriptors/moments_demo.cpp
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@@ -30,7 +30,7 @@ int main( int, char** argv )
src = imread( argv[1], 1 );
/// Convert image to gray and blur it
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
blur( src_gray, src_gray, Size(3,3) );
/// Create Window
@@ -57,7 +57,7 @@ void thresh_callback(int, void* )
/// Detect edges using canny
Canny( src_gray, canny_output, thresh, thresh*2, 3 );
/// Find contours
findContours( canny_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );
findContours( canny_output, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0) );
/// Get the moments
vector<Moments> mu(contours.size() );

2
samples/cpp/tutorial_code/TrackingMotion/cornerDetector_Demo.cpp
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@@ -40,7 +40,7 @@ int main( int, char** argv )
{
/// Load source image and convert it to gray
src = imread( argv[1], 1 );
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
/// Set some parameters
int blockSize = 3; int apertureSize = 3;

2
samples/cpp/tutorial_code/TrackingMotion/cornerHarris_Demo.cpp
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@@ -31,7 +31,7 @@ int main( int, char** argv )
{
/// Load source image and convert it to gray
src = imread( argv[1], 1 );
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
/// Create a window and a trackbar
namedWindow( source_window, CV_WINDOW_AUTOSIZE );

2
samples/cpp/tutorial_code/TrackingMotion/cornerSubPix_Demo.cpp
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@@ -32,7 +32,7 @@ int main( int, char** argv )
{
/// Load source image and convert it to gray
src = imread( argv[1], 1 );
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
/// Create Window
namedWindow( source_window, CV_WINDOW_AUTOSIZE );

2
samples/cpp/tutorial_code/TrackingMotion/goodFeaturesToTrack_Demo.cpp
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@@ -32,7 +32,7 @@ int main( int, char** argv )
{
/// Load source image and convert it to gray
src = imread( argv[1], 1 );
cvtColor( src, src_gray, CV_BGR2GRAY );
cvtColor( src, src_gray, COLOR_BGR2GRAY );
/// Create Window
namedWindow( source_window, CV_WINDOW_AUTOSIZE );

2
samples/cpp/tutorial_code/calib3d/camera_calibration/camera_calibration.cpp
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@@ -291,7 +291,7 @@ int main(int argc, char* argv[])
if( s.calibrationPattern == Settings::CHESSBOARD)
{
Mat viewGray;
cvtColor(view, viewGray, CV_BGR2GRAY);
cvtColor(view, viewGray, COLOR_BGR2GRAY);
cornerSubPix( viewGray, pointBuf, Size(11,11),
Size(-1,-1), TermCriteria( CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 30, 0.1 ));
}

4
samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp
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@@ -46,7 +46,7 @@ int main( int argc, char** argv )
// convert image to YUV color space. The output image will be created automatically.
Mat I_YUV;
cvtColor(I, I_YUV, CV_BGR2YCrCb);
cvtColor(I, I_YUV, COLOR_BGR2YCrCb);
vector<Mat> planes; // Use the STL's vector structure to store multiple Mat objects
split(I_YUV, planes); // split the image into separate color planes (Y U V)
@@ -115,7 +115,7 @@ int main( int argc, char** argv )
merge(planes, I_YUV); // now merge the results back
cvtColor(I_YUV, I, CV_YCrCb2BGR); // and produce the output RGB image
cvtColor(I_YUV, I, COLOR_YCrCb2BGR); // and produce the output RGB image
namedWindow("image with grain", CV_WINDOW_AUTOSIZE); // use this to create images

2
samples/cpp/tutorial_code/objectDetection/objectDetection.cpp
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@@ -68,7 +68,7 @@ void detectAndDisplay( Mat frame )
std::vector<Rect> faces;
Mat frame_gray;
cvtColor( frame, frame_gray, CV_BGR2GRAY );
cvtColor( frame, frame_gray, COLOR_BGR2GRAY );
equalizeHist( frame_gray, frame_gray );
//-- Detect faces
face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0|CV_HAAR_SCALE_IMAGE, Size(30, 30) );

2
samples/cpp/tutorial_code/objectDetection/objectDetection2.cpp
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@@ -68,7 +68,7 @@ void detectAndDisplay( Mat frame )
std::vector<Rect> faces;
Mat frame_gray;
cvtColor( frame, frame_gray, CV_BGR2GRAY );
cvtColor( frame, frame_gray, COLOR_BGR2GRAY );
equalizeHist( frame_gray, frame_gray );
//-- Detect faces

2
samples/cpp/video_dmtx.cpp
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@@ -52,7 +52,7 @@ namespace
if (frame.empty())
break;
cv::Mat gray;
cv::cvtColor(frame,gray,CV_RGB2GRAY);
cv::cvtColor(frame,gray, COLOR_RGB2GRAY);
vector<String> codes;
Mat corners;
findDataMatrix(gray, codes, corners);

2
samples/cpp/video_homography.cpp
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@@ -161,7 +161,7 @@ int main(int ac, char ** av)
if (frame.empty())
break;
cvtColor(frame, gray, CV_RGB2GRAY);
cvtColor(frame, gray, COLOR_RGB2GRAY);
detector.detect(gray, query_kpts); //Find interest points

6
samples/cpp/watershed.cpp
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@@ -59,8 +59,8 @@ int main( int argc, char** argv )
namedWindow( "image", 1 );
img0.copyTo(img);
cvtColor(img, markerMask, CV_BGR2GRAY);
cvtColor(markerMask, imgGray, CV_GRAY2BGR);
cvtColor(img, markerMask, COLOR_BGR2GRAY);
cvtColor(markerMask, imgGray, COLOR_GRAY2BGR);
markerMask = Scalar::all(0);
imshow( "image", img );
setMouseCallback( "image", onMouse, 0 );
@@ -85,7 +85,7 @@ int main( int argc, char** argv )
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
findContours(markerMask, contours, hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE);
findContours(markerMask, contours, hierarchy, RETR_CCOMP, CHAIN_APPROX_SIMPLE);
if( contours.empty() )
continue;