diff --git a/doc/tutorials/calib3d/camera_calibration/camera_calibration.rst b/doc/tutorials/calib3d/camera_calibration/camera_calibration.rst index 2cf00f42a..ff9417ed1 100644 --- a/doc/tutorials/calib3d/camera_calibration/camera_calibration.rst +++ b/doc/tutorials/calib3d/camera_calibration/camera_calibration.rst @@ -136,7 +136,7 @@ Explanation { case Settings::CHESSBOARD: found = findChessboardCorners( view, s.boardSize, pointBuf, - CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_FAST_CHECK | CV_CALIB_CB_NORMALIZE_IMAGE); + CALIB_CB_ADAPTIVE_THRESH | CALIB_CB_FAST_CHECK | CALIB_CB_NORMALIZE_IMAGE); break; case Settings::CIRCLES_GRID: found = findCirclesGrid( view, s.boardSize, pointBuf ); @@ -158,9 +158,9 @@ Explanation 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 )); + Size(-1,-1), TermCriteria( TermCriteria::EPS+TermCriteria::MAX_ITER, 30, 0.1 )); } if( mode == CAPTURING && // For camera only take new samples after delay time @@ -327,7 +327,7 @@ We do the calibration with the help of the :calib3d:`calibrateCamera (0,0) = 1.0; + The distortion coefficient matrix. Initialize with zero. @@ -364,7 +364,7 @@ We do the calibration with the help of the :calib3d:`calibrateCamera `` array of 3d coordinates of a chessboard in any coordinate system. For simplicity, let us choose a system such that one of the chessboard corners is in the origin and the board is in the plane *z = 0*. diff --git a/doc/tutorials/core/discrete_fourier_transform/discrete_fourier_transform.rst b/doc/tutorials/core/discrete_fourier_transform/discrete_fourier_transform.rst index ca3d75dca..17527a712 100644 --- a/doc/tutorials/core/discrete_fourier_transform/discrete_fourier_transform.rst +++ b/doc/tutorials/core/discrete_fourier_transform/discrete_fourier_transform.rst @@ -120,8 +120,8 @@ In this sample I'll show how to calculate and show the *magnitude* image of a Fo .. code-block:: cpp - normalize(magI, magI, 0, 1, CV_MINMAX); // Transform the matrix with float values into a - // viewable image form (float between values 0 and 1). + normalize(magI, magI, 0, 1, NORM_MINMAX); // Transform the matrix with float values into a + // viewable image form (float between values 0 and 1). Result ====== diff --git a/doc/tutorials/core/mat_the_basic_image_container/mat_the_basic_image_container.rst b/doc/tutorials/core/mat_the_basic_image_container/mat_the_basic_image_container.rst index 67517d32f..a3938c872 100644 --- a/doc/tutorials/core/mat_the_basic_image_container/mat_the_basic_image_container.rst +++ b/doc/tutorials/core/mat_the_basic_image_container/mat_the_basic_image_container.rst @@ -32,8 +32,8 @@ To tackle this issue OpenCV uses a reference counting system. The idea is that e .. code-block:: cpp :linenos: - Mat A, C; // creates just the header parts - A = imread(argv[1], CV_LOAD_IMAGE_COLOR); // here we'll know the method used (allocate matrix) + Mat A, C; // creates just the header parts + A = imread(argv[1], IMREAD_COLOR); // here we'll know the method used (allocate matrix) Mat B(A); // Use the copy constructor diff --git a/doc/tutorials/core/random_generator_and_text/random_generator_and_text.rst b/doc/tutorials/core/random_generator_and_text/random_generator_and_text.rst index 38c761fc6..ebd1e333f 100644 --- a/doc/tutorials/core/random_generator_and_text/random_generator_and_text.rst +++ b/doc/tutorials/core/random_generator_and_text/random_generator_and_text.rst @@ -194,7 +194,7 @@ Explanation int Displaying_Big_End( Mat image, char* window_name, RNG rng ) { - Size textsize = getTextSize("OpenCV forever!", CV_FONT_HERSHEY_COMPLEX, 3, 5, 0); + Size textsize = getTextSize("OpenCV forever!", FONT_HERSHEY_COMPLEX, 3, 5, 0); Point org((window_width - textsize.width)/2, (window_height - textsize.height)/2); int lineType = 8; @@ -203,7 +203,7 @@ Explanation for( int i = 0; i < 255; i += 2 ) { image2 = image - Scalar::all(i); - putText( image2, "OpenCV forever!", org, CV_FONT_HERSHEY_COMPLEX, 3, + putText( image2, "OpenCV forever!", org, FONT_HERSHEY_COMPLEX, 3, Scalar(i, i, 255), 5, lineType ); imshow( window_name, image2 ); diff --git a/doc/tutorials/features2d/detection_of_planar_objects/detection_of_planar_objects.rst b/doc/tutorials/features2d/detection_of_planar_objects/detection_of_planar_objects.rst index 009d537d5..add22756e 100644 --- a/doc/tutorials/features2d/detection_of_planar_objects/detection_of_planar_objects.rst +++ b/doc/tutorials/features2d/detection_of_planar_objects/detection_of_planar_objects.rst @@ -12,8 +12,8 @@ The goal of this tutorial is to learn how to use *features2d* and *calib3d* modu #. Create a new console project. Read two input images. :: - Mat img1 = imread(argv[1], CV_LOAD_IMAGE_GRAYSCALE); - Mat img2 = imread(argv[2], CV_LOAD_IMAGE_GRAYSCALE); + Mat img1 = imread(argv[1], IMREAD_GRAYSCALE); + Mat img2 = imread(argv[2], IMREAD_GRAYSCALE); #. Detect keypoints in both images. :: @@ -59,7 +59,7 @@ The goal of this tutorial is to learn how to use *features2d* and *calib3d* modu vector points1, points2; // fill the arrays with the points .... - Mat H = findHomography(Mat(points1), Mat(points2), CV_RANSAC, ransacReprojThreshold); + Mat H = findHomography(Mat(points1), Mat(points2), RANSAC, ransacReprojThreshold); #. diff --git a/doc/tutorials/features2d/feature_description/feature_description.rst b/doc/tutorials/features2d/feature_description/feature_description.rst index 17dee727e..1937f5476 100644 --- a/doc/tutorials/features2d/feature_description/feature_description.rst +++ b/doc/tutorials/features2d/feature_description/feature_description.rst @@ -45,8 +45,8 @@ This tutorial code's is shown lines below. if( argc != 3 ) { return -1; } - Mat img_1 = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE ); - Mat img_2 = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE ); + Mat img_1 = imread( argv[1], IMREAD_GRAYSCALE ); + Mat img_2 = imread( argv[2], IMREAD_GRAYSCALE ); if( !img_1.data || !img_2.data ) { return -1; } diff --git a/doc/tutorials/features2d/feature_detection/feature_detection.rst b/doc/tutorials/features2d/feature_detection/feature_detection.rst index 685a05878..7d5e2600e 100644 --- a/doc/tutorials/features2d/feature_detection/feature_detection.rst +++ b/doc/tutorials/features2d/feature_detection/feature_detection.rst @@ -44,8 +44,8 @@ This tutorial code's is shown lines below. if( argc != 3 ) { readme(); return -1; } - Mat img_1 = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE ); - Mat img_2 = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE ); + Mat img_1 = imread( argv[1], IMREAD_GRAYSCALE ); + Mat img_2 = imread( argv[2], IMREAD_GRAYSCALE ); if( !img_1.data || !img_2.data ) { std::cout<< " --(!) Error reading images " << std::endl; return -1; } diff --git a/doc/tutorials/features2d/feature_homography/feature_homography.rst b/doc/tutorials/features2d/feature_homography/feature_homography.rst index 91e70c9a6..47e984baa 100644 --- a/doc/tutorials/features2d/feature_homography/feature_homography.rst +++ b/doc/tutorials/features2d/feature_homography/feature_homography.rst @@ -43,8 +43,8 @@ This tutorial code's is shown lines below. if( argc != 3 ) { readme(); return -1; } - Mat img_object = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE ); - Mat img_scene = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE ); + Mat img_object = imread( argv[1], IMREAD_GRAYSCALE ); + Mat img_scene = imread( argv[2], IMREAD_GRAYSCALE ); if( !img_object.data || !img_scene.data ) { std::cout<< " --(!) Error reading images " << std::endl; return -1; } @@ -108,7 +108,7 @@ This tutorial code's is shown lines below. scene.push_back( keypoints_scene[ good_matches[i].trainIdx ].pt ); } - Mat H = findHomography( obj, scene, CV_RANSAC ); + Mat H = findHomography( obj, scene, RANSAC ); //-- Get the corners from the image_1 ( the object to be "detected" ) std::vector obj_corners(4); diff --git a/doc/tutorials/features2d/trackingmotion/corner_subpixeles/corner_subpixeles.rst b/doc/tutorials/features2d/trackingmotion/corner_subpixeles/corner_subpixeles.rst index f0d018870..38302424b 100644 --- a/doc/tutorials/features2d/trackingmotion/corner_subpixeles/corner_subpixeles.rst +++ b/doc/tutorials/features2d/trackingmotion/corner_subpixeles/corner_subpixeles.rst @@ -49,10 +49,10 @@ This tutorial code's is shown lines below. You can also download it from `here < { /// 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 ); + namedWindow( source_window, WINDOW_AUTOSIZE ); /// Create Trackbar to set the number of corners createTrackbar( "Max corners:", source_window, &maxCorners, maxTrackbar, goodFeaturesToTrack_Demo); @@ -105,13 +105,13 @@ This tutorial code's is shown lines below. You can also download it from `here < rng.uniform(0,255)), -1, 8, 0 ); } /// Show what you got - namedWindow( source_window, CV_WINDOW_AUTOSIZE ); + namedWindow( source_window, WINDOW_AUTOSIZE ); imshow( source_window, copy ); /// Set the neeed parameters to find the refined corners Size winSize = Size( 5, 5 ); Size zeroZone = Size( -1, -1 ); - TermCriteria criteria = TermCriteria( CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 40, 0.001 ); + TermCriteria criteria = TermCriteria( TermCriteria::EPS + TermCriteria::MAX_ITER, 40, 0.001 ); /// Calculate the refined corner locations cornerSubPix( src_gray, corners, winSize, zeroZone, criteria ); diff --git a/doc/tutorials/features2d/trackingmotion/good_features_to_track/good_features_to_track.rst b/doc/tutorials/features2d/trackingmotion/good_features_to_track/good_features_to_track.rst index 52e1eb463..05bc66d26 100644 --- a/doc/tutorials/features2d/trackingmotion/good_features_to_track/good_features_to_track.rst +++ b/doc/tutorials/features2d/trackingmotion/good_features_to_track/good_features_to_track.rst @@ -50,10 +50,10 @@ This tutorial code's is shown lines below. You can also download it from `here < { /// 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 ); + namedWindow( source_window, WINDOW_AUTOSIZE ); /// Create Trackbar to set the number of corners createTrackbar( "Max corners:", source_window, &maxCorners, maxTrackbar, goodFeaturesToTrack_Demo ); @@ -106,7 +106,7 @@ This tutorial code's is shown lines below. You can also download it from `here < rng.uniform(0,255)), -1, 8, 0 ); } /// Show what you got - namedWindow( source_window, CV_WINDOW_AUTOSIZE ); + namedWindow( source_window, WINDOW_AUTOSIZE ); imshow( source_window, copy ); } diff --git a/doc/tutorials/features2d/trackingmotion/harris_detector/harris_detector.rst b/doc/tutorials/features2d/trackingmotion/harris_detector/harris_detector.rst index d2c12fc84..8cdeb2aa2 100644 --- a/doc/tutorials/features2d/trackingmotion/harris_detector/harris_detector.rst +++ b/doc/tutorials/features2d/trackingmotion/harris_detector/harris_detector.rst @@ -180,10 +180,10 @@ This tutorial code's is shown lines below. You can also download it from `here < { /// 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 ); + namedWindow( source_window, WINDOW_AUTOSIZE ); createTrackbar( "Threshold: ", source_window, &thresh, max_thresh, cornerHarris_demo ); imshow( source_window, src ); @@ -223,7 +223,7 @@ This tutorial code's is shown lines below. You can also download it from `here < } } /// Showing the result - namedWindow( corners_window, CV_WINDOW_AUTOSIZE ); + namedWindow( corners_window, WINDOW_AUTOSIZE ); imshow( corners_window, dst_norm_scaled ); } diff --git a/doc/tutorials/highgui/video-input-psnr-ssim/video-input-psnr-ssim.rst b/doc/tutorials/highgui/video-input-psnr-ssim/video-input-psnr-ssim.rst index 8f63bf1a2..eac1f2404 100644 --- a/doc/tutorials/highgui/video-input-psnr-ssim/video-input-psnr-ssim.rst +++ b/doc/tutorials/highgui/video-input-psnr-ssim/video-input-psnr-ssim.rst @@ -79,18 +79,18 @@ Videos have many-many information attached to them besides the content of the fr .. code-block:: cpp - Size refS = Size((int) captRefrnc.get(CV_CAP_PROP_FRAME_WIDTH), - (int) captRefrnc.get(CV_CAP_PROP_FRAME_HEIGHT)), + Size refS = Size((int) captRefrnc.get(CAP_PROP_FRAME_WIDTH), + (int) captRefrnc.get(CAP_PROP_FRAME_HEIGHT)), cout << "Reference frame resolution: Width=" << refS.width << " Height=" << refS.height - << " of nr#: " << captRefrnc.get(CV_CAP_PROP_FRAME_COUNT) << endl; + << " of nr#: " << captRefrnc.get(CAP_PROP_FRAME_COUNT) << endl; When you are working with videos you may often want to control these values yourself. To do this there is a :hgvideo:`set ` function. Its first argument remains the name of the property you want to change and there is a second of double type containing the value to be set. It will return true if it succeeds and false otherwise. Good examples for this is seeking in a video file to a given time or frame: .. code-block:: cpp - captRefrnc.set(CV_CAP_PROP_POS_MSEC, 1.2); // go to the 1.2 second in the video - captRefrnc.set(CV_CAP_PROP_POS_FRAMES, 10); // go to the 10th frame of the video + captRefrnc.set(CAP_PROP_POS_MSEC, 1.2); // go to the 1.2 second in the video + captRefrnc.set(CAP_PROP_POS_FRAMES, 10); // go to the 10th frame of the video // now a read operation would read the frame at the set position For properties you can read and change look into the documentation of the :hgvideo:`get ` and :hgvideo:`set ` functions. @@ -122,7 +122,7 @@ Here the :math:`MAX_I^2` is the maximum valid value for a pixel. In case of the s1.convertTo(s1, CV_32F); // cannot make a square on 8 bits s1 = s1.mul(s1); // |I1 - I2|^2 - Scalar s = sum(s1); // sum elements per channel + Scalar s = sum(s1); // sum elements per channel double sse = s.val[0] + s.val[1] + s.val[2]; // sum channels diff --git a/doc/tutorials/highgui/video-write/video-write.rst b/doc/tutorials/highgui/video-write/video-write.rst index 16be92bbe..36ecf8869 100644 --- a/doc/tutorials/highgui/video-write/video-write.rst +++ b/doc/tutorials/highgui/video-write/video-write.rst @@ -62,8 +62,8 @@ To create a video file you just need to create an instance of the :hgvideo:`Vide .. code-block:: cpp - VideoCapture inputVideo(source); // Open input - int ex = static_cast(inputVideo.get(CV_CAP_PROP_FOURCC)); // Get Codec Type- Int form + VideoCapture inputVideo(source); // Open input + int ex = static_cast(inputVideo.get(CAP_PROP_FOURCC)); // Get Codec Type- Int form OpenCV internally works with this integer type and expect this as its second parameter. Now to convert from the integer form to string we may use two methods: a bitwise operator and a union method. The first one extracting from an int the characters looks like (an "and" operation, some shifting and adding a 0 at the end to close the string): @@ -100,9 +100,9 @@ Here it is, how I use it in the sample: .. code-block:: cpp VideoWriter outputVideo; - Size S = Size((int) inputVideo.get(CV_CAP_PROP_FRAME_WIDTH), //Acquire input size - (int) inputVideo.get(CV_CAP_PROP_FRAME_HEIGHT)); - outputVideo.open(NAME , ex, inputVideo.get(CV_CAP_PROP_FPS),S, true); + Size S = Size((int) inputVideo.get(CAP_PROP_FRAME_WIDTH), //Acquire input size + (int) inputVideo.get(CAP_PROP_FRAME_HEIGHT)); + outputVideo.open(NAME , ex, inputVideo.get(CAP_PROP_FPS),S, true); Afterwards, you use the :hgvideo:`isOpened() ` function to find out if the open operation succeeded or not. The video file automatically closes when the *VideoWriter* object is destroyed. After you open the object with success you can send the frames of the video in a sequential order by using the :hgvideo:`write` function of the class. Alternatively, you can use its overloaded operator << : diff --git a/doc/tutorials/imgproc/erosion_dilatation/erosion_dilatation.rst b/doc/tutorials/imgproc/erosion_dilatation/erosion_dilatation.rst index 0f8f5fd91..bda9b624a 100644 --- a/doc/tutorials/imgproc/erosion_dilatation/erosion_dilatation.rst +++ b/doc/tutorials/imgproc/erosion_dilatation/erosion_dilatation.rst @@ -106,8 +106,8 @@ This tutorial code's is shown lines below. You can also download it from `here < { return -1; } /// Create windows - namedWindow( "Erosion Demo", CV_WINDOW_AUTOSIZE ); - namedWindow( "Dilation Demo", CV_WINDOW_AUTOSIZE ); + namedWindow( "Erosion Demo", WINDOW_AUTOSIZE ); + namedWindow( "Dilation Demo", WINDOW_AUTOSIZE ); cvMoveWindow( "Dilation Demo", src.cols, 0 ); /// Create Erosion Trackbar diff --git a/doc/tutorials/imgproc/gausian_median_blur_bilateral_filter/gausian_median_blur_bilateral_filter.rst b/doc/tutorials/imgproc/gausian_median_blur_bilateral_filter/gausian_median_blur_bilateral_filter.rst index 0c72a0ab4..e708f08ae 100644 --- a/doc/tutorials/imgproc/gausian_median_blur_bilateral_filter/gausian_median_blur_bilateral_filter.rst +++ b/doc/tutorials/imgproc/gausian_median_blur_bilateral_filter/gausian_median_blur_bilateral_filter.rst @@ -145,7 +145,7 @@ Code */ int main( int argc, char** argv ) { - namedWindow( window_name, CV_WINDOW_AUTOSIZE ); + namedWindow( window_name, WINDOW_AUTOSIZE ); /// Load the source image src = imread( "../images/lena.jpg", 1 ); @@ -195,7 +195,7 @@ Code dst = Mat::zeros( src.size(), src.type() ); putText( dst, caption, Point( src.cols/4, src.rows/2), - CV_FONT_HERSHEY_COMPLEX, 1, Scalar(255, 255, 255) ); + FONT_HERSHEY_COMPLEX, 1, Scalar(255, 255, 255) ); imshow( window_name, dst ); int c = waitKey( DELAY_CAPTION ); diff --git a/doc/tutorials/imgproc/histograms/back_projection/back_projection.rst b/doc/tutorials/imgproc/histograms/back_projection/back_projection.rst index fbb7dc4dd..5c3a78f6f 100644 --- a/doc/tutorials/imgproc/histograms/back_projection/back_projection.rst +++ b/doc/tutorials/imgproc/histograms/back_projection/back_projection.rst @@ -128,7 +128,7 @@ Code /// 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() ); @@ -137,7 +137,7 @@ Code /// Create Trackbar to enter the number of bins char* window_image = "Source image"; - namedWindow( window_image, CV_WINDOW_AUTOSIZE ); + namedWindow( window_image, WINDOW_AUTOSIZE ); createTrackbar("* Hue bins: ", window_image, &bins, 180, Hist_and_Backproj ); Hist_and_Backproj(0, 0); @@ -198,7 +198,7 @@ Explanation .. code-block:: cpp src = imread( argv[1], 1 ); - cvtColor( src, hsv, CV_BGR2HSV ); + cvtColor( src, hsv, COLOR_BGR2HSV ); #. For this tutorial, we will use only the Hue value for our 1-D histogram (check out the fancier code in the links above if you want to use the more standard H-S histogram, which yields better results): @@ -224,7 +224,7 @@ Explanation .. code-block:: cpp char* window_image = "Source image"; - namedWindow( window_image, CV_WINDOW_AUTOSIZE ); + namedWindow( window_image, WINDOW_AUTOSIZE ); createTrackbar("* Hue bins: ", window_image, &bins, 180, Hist_and_Backproj ); Hist_and_Backproj(0, 0); diff --git a/doc/tutorials/imgproc/histograms/histogram_calculation/histogram_calculation.rst b/doc/tutorials/imgproc/histograms/histogram_calculation/histogram_calculation.rst index 9a0b4b645..558c4e76e 100644 --- a/doc/tutorials/imgproc/histograms/histogram_calculation/histogram_calculation.rst +++ b/doc/tutorials/imgproc/histograms/histogram_calculation/histogram_calculation.rst @@ -155,7 +155,7 @@ Code } /// Display - namedWindow("calcHist Demo", CV_WINDOW_AUTOSIZE ); + namedWindow("calcHist Demo", WINDOW_AUTOSIZE ); imshow("calcHist Demo", histImage ); waitKey(0); @@ -309,7 +309,7 @@ Explanation .. code-block:: cpp - namedWindow("calcHist Demo", CV_WINDOW_AUTOSIZE ); + namedWindow("calcHist Demo", WINDOW_AUTOSIZE ); imshow("calcHist Demo", histImage ); waitKey(0); diff --git a/doc/tutorials/imgproc/histograms/histogram_comparison/histogram_comparison.rst b/doc/tutorials/imgproc/histograms/histogram_comparison/histogram_comparison.rst index f5f636d08..8bb72da9f 100644 --- a/doc/tutorials/imgproc/histograms/histogram_comparison/histogram_comparison.rst +++ b/doc/tutorials/imgproc/histograms/histogram_comparison/histogram_comparison.rst @@ -119,9 +119,9 @@ Explanation .. code-block:: cpp - 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 ); #. Also, create an image of half the base image (in HSV format): diff --git a/doc/tutorials/imgproc/histograms/histogram_equalization/histogram_equalization.rst b/doc/tutorials/imgproc/histograms/histogram_equalization/histogram_equalization.rst index 7004da738..884c82a2f 100644 --- a/doc/tutorials/imgproc/histograms/histogram_equalization/histogram_equalization.rst +++ b/doc/tutorials/imgproc/histograms/histogram_equalization/histogram_equalization.rst @@ -113,14 +113,14 @@ Code return -1;} /// Convert to grayscale - cvtColor( src, src, CV_BGR2GRAY ); + cvtColor( src, src, COLOR_BGR2GRAY ); /// Apply Histogram Equalization equalizeHist( src, dst ); /// Display results - namedWindow( source_window, CV_WINDOW_AUTOSIZE ); - namedWindow( equalized_window, CV_WINDOW_AUTOSIZE ); + namedWindow( source_window, WINDOW_AUTOSIZE ); + namedWindow( equalized_window, WINDOW_AUTOSIZE ); imshow( source_window, src ); imshow( equalized_window, dst ); @@ -157,7 +157,7 @@ Explanation .. code-block:: cpp - cvtColor( src, src, CV_BGR2GRAY ); + cvtColor( src, src, COLOR_BGR2GRAY ); #. Apply histogram equalization with the function :equalize_hist:`equalizeHist <>` : @@ -171,8 +171,8 @@ Explanation .. code-block:: cpp - namedWindow( source_window, CV_WINDOW_AUTOSIZE ); - namedWindow( equalized_window, CV_WINDOW_AUTOSIZE ); + namedWindow( source_window, WINDOW_AUTOSIZE ); + namedWindow( equalized_window, WINDOW_AUTOSIZE ); imshow( source_window, src ); imshow( equalized_window, dst ); diff --git a/doc/tutorials/imgproc/histograms/template_matching/template_matching.rst b/doc/tutorials/imgproc/histograms/template_matching/template_matching.rst index eb90369ff..9997bb60d 100644 --- a/doc/tutorials/imgproc/histograms/template_matching/template_matching.rst +++ b/doc/tutorials/imgproc/histograms/template_matching/template_matching.rst @@ -158,8 +158,8 @@ Code templ = imread( argv[2], 1 ); /// Create windows - namedWindow( image_window, CV_WINDOW_AUTOSIZE ); - namedWindow( result_window, CV_WINDOW_AUTOSIZE ); + namedWindow( image_window, WINDOW_AUTOSIZE ); + namedWindow( result_window, WINDOW_AUTOSIZE ); /// Create Trackbar char* trackbar_label = "Method: \n 0: SQDIFF \n 1: SQDIFF NORMED \n 2: TM CCORR \n 3: TM CCORR NORMED \n 4: TM COEFF \n 5: TM COEFF NORMED"; @@ -239,8 +239,8 @@ Explanation .. code-block:: cpp - namedWindow( image_window, CV_WINDOW_AUTOSIZE ); - namedWindow( result_window, CV_WINDOW_AUTOSIZE ); + namedWindow( image_window, WINDOW_AUTOSIZE ); + namedWindow( result_window, WINDOW_AUTOSIZE ); #. Create the Trackbar to enter the kind of matching method to be used. When a change is detected the callback function **MatchingMethod** is called. @@ -306,11 +306,11 @@ Explanation + **Mat():** Optional mask -#. For the first two methods ( CV\_SQDIFF and CV\_SQDIFF\_NORMED ) the best match are the lowest values. For all the others, higher values represent better matches. So, we save the corresponding value in the **matchLoc** variable: +#. For the first two methods ( TM\_SQDIFF and MT\_SQDIFF\_NORMED ) the best match are the lowest values. For all the others, higher values represent better matches. So, we save the corresponding value in the **matchLoc** variable: .. code-block:: cpp - 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; } diff --git a/doc/tutorials/imgproc/imgtrans/canny_detector/canny_detector.rst b/doc/tutorials/imgproc/imgtrans/canny_detector/canny_detector.rst index c516fea21..ba0f7cd68 100644 --- a/doc/tutorials/imgproc/imgtrans/canny_detector/canny_detector.rst +++ b/doc/tutorials/imgproc/imgtrans/canny_detector/canny_detector.rst @@ -142,10 +142,10 @@ Code 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 ); + namedWindow( window_name, WINDOW_AUTOSIZE ); /// Create a Trackbar for user to enter threshold createTrackbar( "Min Threshold:", window_name, &lowThreshold, max_lowThreshold, CannyThreshold ); @@ -203,13 +203,13 @@ Explanation .. code-block:: cpp - cvtColor( src, src_gray, CV_BGR2GRAY ); + cvtColor( src, src_gray, COLOR_BGR2GRAY ); #. Create a window to display the results .. code-block:: cpp - namedWindow( window_name, CV_WINDOW_AUTOSIZE ); + namedWindow( window_name, WINDOW_AUTOSIZE ); #. Create a Trackbar for the user to enter the lower threshold for our Canny detector: diff --git a/doc/tutorials/imgproc/imgtrans/copyMakeBorder/copyMakeBorder.rst b/doc/tutorials/imgproc/imgtrans/copyMakeBorder/copyMakeBorder.rst index a8ba92b1e..6546323b0 100644 --- a/doc/tutorials/imgproc/imgtrans/copyMakeBorder/copyMakeBorder.rst +++ b/doc/tutorials/imgproc/imgtrans/copyMakeBorder/copyMakeBorder.rst @@ -89,7 +89,7 @@ Code printf( " ** Press 'ESC' to exit the program \n"); /// Create window - namedWindow( window_name, CV_WINDOW_AUTOSIZE ); + namedWindow( window_name, WINDOW_AUTOSIZE ); /// Initialize arguments for the filter top = (int) (0.05*src.rows); bottom = (int) (0.05*src.rows); @@ -150,7 +150,7 @@ Explanation .. code-block:: cpp - namedWindow( window_name, CV_WINDOW_AUTOSIZE ); + namedWindow( window_name, WINDOW_AUTOSIZE ); #. Now we initialize the argument that defines the size of the borders (*top*, *bottom*, *left* and *right*). We give them a value of 5% the size of *src*. diff --git a/doc/tutorials/imgproc/imgtrans/filter_2d/filter_2d.rst b/doc/tutorials/imgproc/imgtrans/filter_2d/filter_2d.rst index 933f8888c..1b6074f8d 100644 --- a/doc/tutorials/imgproc/imgtrans/filter_2d/filter_2d.rst +++ b/doc/tutorials/imgproc/imgtrans/filter_2d/filter_2d.rst @@ -106,7 +106,7 @@ Code { return -1; } /// Create window - namedWindow( window_name, CV_WINDOW_AUTOSIZE ); + namedWindow( window_name, WINDOW_AUTOSIZE ); /// Initialize arguments for the filter anchor = Point( -1, -1 ); @@ -151,7 +151,7 @@ Explanation .. code-block:: cpp - namedWindow( window_name, CV_WINDOW_AUTOSIZE ); + namedWindow( window_name, WINDOW_AUTOSIZE ); #. Initialize the arguments for the linear filter diff --git a/doc/tutorials/imgproc/imgtrans/hough_circle/hough_circle.rst b/doc/tutorials/imgproc/imgtrans/hough_circle/hough_circle.rst index 6aae4bb9c..3eb2e04e6 100644 --- a/doc/tutorials/imgproc/imgtrans/hough_circle/hough_circle.rst +++ b/doc/tutorials/imgproc/imgtrans/hough_circle/hough_circle.rst @@ -67,7 +67,7 @@ Code { 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 ); @@ -75,7 +75,7 @@ Code vector 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++ ) @@ -89,7 +89,7 @@ Code } /// Show your results - namedWindow( "Hough Circle Transform Demo", CV_WINDOW_AUTOSIZE ); + namedWindow( "Hough Circle Transform Demo", WINDOW_AUTOSIZE ); imshow( "Hough Circle Transform Demo", src ); waitKey(0); @@ -114,7 +114,7 @@ Explanation .. code-block:: cpp - cvtColor( src, src_gray, CV_BGR2GRAY ); + cvtColor( src, src_gray, COLOR_BGR2GRAY ); #. Apply a Gaussian blur to reduce noise and avoid false circle detection: @@ -128,13 +128,13 @@ Explanation vector 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 ); with the arguments: * *src_gray*: Input image (grayscale). * *circles*: A vector that stores sets of 3 values: :math:`x_{c}, y_{c}, r` for each detected circle. - * *CV_HOUGH_GRADIENT*: Define the detection method. Currently this is the only one available in OpenCV. + * *HOUGH_GRADIENT*: Define the detection method. Currently this is the only one available in OpenCV. * *dp = 1*: The inverse ratio of resolution. * *min_dist = src_gray.rows/8*: Minimum distance between detected centers. * *param_1 = 200*: Upper threshold for the internal Canny edge detector. @@ -162,7 +162,7 @@ Explanation .. code-block:: cpp - namedWindow( "Hough Circle Transform Demo", CV_WINDOW_AUTOSIZE ); + namedWindow( "Hough Circle Transform Demo", WINDOW_AUTOSIZE ); imshow( "Hough Circle Transform Demo", src ); #. Wait for the user to exit the program diff --git a/doc/tutorials/imgproc/imgtrans/hough_lines/hough_lines.rst b/doc/tutorials/imgproc/imgtrans/hough_lines/hough_lines.rst index a786fdb15..52602d8d5 100644 --- a/doc/tutorials/imgproc/imgtrans/hough_lines/hough_lines.rst +++ b/doc/tutorials/imgproc/imgtrans/hough_lines/hough_lines.rst @@ -133,7 +133,7 @@ Code Mat dst, cdst; Canny(src, dst, 50, 200, 3); - cvtColor(dst, cdst, CV_GRAY2BGR); + cvtColor(dst, cdst, COLOR_GRAY2BGR); #if 0 vector lines; @@ -149,7 +149,7 @@ Code pt1.y = cvRound(y0 + 1000*(a)); pt2.x = cvRound(x0 - 1000*(-b)); pt2.y = cvRound(y0 - 1000*(a)); - line( cdst, pt1, pt2, Scalar(0,0,255), 3, CV_AA); + line( cdst, pt1, pt2, Scalar(0,0,255), 3, LINE_AA); } #else vector lines; @@ -223,7 +223,7 @@ Explanation pt1.y = cvRound(y0 + 1000*(a)); pt2.x = cvRound(x0 - 1000*(-b)); pt2.y = cvRound(y0 - 1000*(a)); - line( cdst, pt1, pt2, Scalar(0,0,255), 3, CV_AA); + line( cdst, pt1, pt2, Scalar(0,0,255), 3, LINE_AA); } #. **Probabilistic Hough Line Transform** @@ -252,7 +252,7 @@ Explanation for( size_t i = 0; i < lines.size(); i++ ) { Vec4i l = lines[i]; - line( cdst, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(0,0,255), 3, CV_AA); + line( cdst, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(0,0,255), 3, LINE_AA); } diff --git a/doc/tutorials/imgproc/imgtrans/laplace_operator/laplace_operator.rst b/doc/tutorials/imgproc/imgtrans/laplace_operator/laplace_operator.rst index d30870f1d..13bea48a0 100644 --- a/doc/tutorials/imgproc/imgtrans/laplace_operator/laplace_operator.rst +++ b/doc/tutorials/imgproc/imgtrans/laplace_operator/laplace_operator.rst @@ -88,10 +88,10 @@ Code 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 ); + namedWindow( window_name, WINDOW_AUTOSIZE ); /// Apply Laplace function Mat abs_dst; @@ -141,7 +141,7 @@ Explanation .. code-block:: cpp - cvtColor( src, src_gray, CV_RGB2GRAY ); + cvtColor( src, src_gray, COLOR_RGB2GRAY ); #. Apply the Laplacian operator to the grayscale image: diff --git a/doc/tutorials/imgproc/imgtrans/remap/remap.rst b/doc/tutorials/imgproc/imgtrans/remap/remap.rst index f5db120e6..fad8443e2 100644 --- a/doc/tutorials/imgproc/imgtrans/remap/remap.rst +++ b/doc/tutorials/imgproc/imgtrans/remap/remap.rst @@ -93,7 +93,7 @@ Code map_y.create( src.size(), CV_32FC1 ); /// Create window - namedWindow( remap_window, CV_WINDOW_AUTOSIZE ); + namedWindow( remap_window, WINDOW_AUTOSIZE ); /// Loop while( true ) @@ -106,7 +106,7 @@ Code /// 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 ); @@ -186,7 +186,7 @@ Explanation .. code-block:: cpp - namedWindow( remap_window, CV_WINDOW_AUTOSIZE ); + namedWindow( remap_window, WINDOW_AUTOSIZE ); #. Establish a loop. Each 1000 ms we update our mapping matrices (*mat_x* and *mat_y*) and apply them to our source image: @@ -202,7 +202,7 @@ Explanation /// 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 ); @@ -214,7 +214,7 @@ Explanation * **dst**: Destination image of same size as *src* * **map_x**: The mapping function in the x direction. It is equivalent to the first component of :math:`h(i,j)` * **map_y**: Same as above, but in y direction. Note that *map_y* and *map_x* are both of the same size as *src* - * **CV_INTER_LINEAR**: The type of interpolation to use for non-integer pixels. This is by default. + * **INTER_LINEAR**: The type of interpolation to use for non-integer pixels. This is by default. * **BORDER_CONSTANT**: Default How do we update our mapping matrices *mat_x* and *mat_y*? Go on reading: diff --git a/doc/tutorials/imgproc/imgtrans/sobel_derivatives/sobel_derivatives.rst b/doc/tutorials/imgproc/imgtrans/sobel_derivatives/sobel_derivatives.rst index e5e7bdfcf..a7583780c 100644 --- a/doc/tutorials/imgproc/imgtrans/sobel_derivatives/sobel_derivatives.rst +++ b/doc/tutorials/imgproc/imgtrans/sobel_derivatives/sobel_derivatives.rst @@ -154,10 +154,10 @@ Code 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 ); + namedWindow( window_name, WINDOW_AUTOSIZE ); /// Generate grad_x and grad_y Mat grad_x, grad_y; @@ -217,7 +217,7 @@ Explanation .. code-block:: cpp - cvtColor( src, src_gray, CV_RGB2GRAY ); + cvtColor( src, src_gray, COLOR_RGB2GRAY ); #. Second, we calculate the "*derivatives*" in *x* and *y* directions. For this, we use the function :sobel:`Sobel <>` as shown below: diff --git a/doc/tutorials/imgproc/imgtrans/warp_affine/warp_affine.rst b/doc/tutorials/imgproc/imgtrans/warp_affine/warp_affine.rst index 4fc97ee92..4717a5bbd 100644 --- a/doc/tutorials/imgproc/imgtrans/warp_affine/warp_affine.rst +++ b/doc/tutorials/imgproc/imgtrans/warp_affine/warp_affine.rst @@ -155,13 +155,13 @@ Code warpAffine( warp_dst, warp_rotate_dst, rot_mat, warp_dst.size() ); /// Show what you got - namedWindow( source_window, CV_WINDOW_AUTOSIZE ); + namedWindow( source_window, WINDOW_AUTOSIZE ); imshow( source_window, src ); - namedWindow( warp_window, CV_WINDOW_AUTOSIZE ); + namedWindow( warp_window, WINDOW_AUTOSIZE ); imshow( warp_window, warp_dst ); - namedWindow( warp_rotate_window, CV_WINDOW_AUTOSIZE ); + namedWindow( warp_rotate_window, WINDOW_AUTOSIZE ); imshow( warp_rotate_window, warp_rotate_dst ); /// Wait until user exits the program @@ -265,13 +265,13 @@ Explanation .. code-block:: cpp - namedWindow( source_window, CV_WINDOW_AUTOSIZE ); + namedWindow( source_window, WINDOW_AUTOSIZE ); imshow( source_window, src ); - namedWindow( warp_window, CV_WINDOW_AUTOSIZE ); + namedWindow( warp_window, WINDOW_AUTOSIZE ); imshow( warp_window, warp_dst ); - namedWindow( warp_rotate_window, CV_WINDOW_AUTOSIZE ); + namedWindow( warp_rotate_window, WINDOW_AUTOSIZE ); imshow( warp_rotate_window, warp_rotate_dst ); diff --git a/doc/tutorials/imgproc/opening_closing_hats/opening_closing_hats.rst b/doc/tutorials/imgproc/opening_closing_hats/opening_closing_hats.rst index ac734d94d..a807e9f2d 100644 --- a/doc/tutorials/imgproc/opening_closing_hats/opening_closing_hats.rst +++ b/doc/tutorials/imgproc/opening_closing_hats/opening_closing_hats.rst @@ -147,7 +147,7 @@ This tutorial code's is shown lines below. You can also download it from `here < { return -1; } /// Create window - namedWindow( window_name, CV_WINDOW_AUTOSIZE ); + namedWindow( window_name, WINDOW_AUTOSIZE ); /// Create Trackbar to select Morphology operation createTrackbar("Operator:\n 0: Opening - 1: Closing \n 2: Gradient - 3: Top Hat \n 4: Black Hat", window_name, &morph_operator, max_operator, Morphology_Operations ); diff --git a/doc/tutorials/imgproc/pyramids/pyramids.rst b/doc/tutorials/imgproc/pyramids/pyramids.rst index 7b78f0dc0..1d28ea46e 100644 --- a/doc/tutorials/imgproc/pyramids/pyramids.rst +++ b/doc/tutorials/imgproc/pyramids/pyramids.rst @@ -119,7 +119,7 @@ This tutorial code's is shown lines below. You can also download it from `here < dst = tmp; /// Create window - namedWindow( window_name, CV_WINDOW_AUTOSIZE ); + namedWindow( window_name, WINDOW_AUTOSIZE ); imshow( window_name, dst ); /// Loop @@ -175,7 +175,7 @@ Explanation .. code-block:: cpp - namedWindow( window_name, CV_WINDOW_AUTOSIZE ); + namedWindow( window_name, WINDOW_AUTOSIZE ); imshow( window_name, dst ); * Perform an infinite loop waiting for user input. diff --git a/doc/tutorials/imgproc/shapedescriptors/bounding_rects_circles/bounding_rects_circles.rst b/doc/tutorials/imgproc/shapedescriptors/bounding_rects_circles/bounding_rects_circles.rst index 519f6943a..66ee018ee 100644 --- a/doc/tutorials/imgproc/shapedescriptors/bounding_rects_circles/bounding_rects_circles.rst +++ b/doc/tutorials/imgproc/shapedescriptors/bounding_rects_circles/bounding_rects_circles.rst @@ -49,12 +49,12 @@ This tutorial code's is shown lines below. You can also download it from `here < 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 char* source_window = "Source"; - namedWindow( source_window, CV_WINDOW_AUTOSIZE ); + namedWindow( source_window, WINDOW_AUTOSIZE ); imshow( source_window, src ); createTrackbar( " Threshold:", "Source", &thresh, max_thresh, thresh_callback ); @@ -74,7 +74,7 @@ This tutorial code's is shown lines below. You can also download it from `here < /// 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 > contours_poly( contours.size() ); @@ -100,7 +100,7 @@ This tutorial code's is shown lines below. You can also download it from `here < } /// Show in a window - namedWindow( "Contours", CV_WINDOW_AUTOSIZE ); + namedWindow( "Contours", WINDOW_AUTOSIZE ); imshow( "Contours", drawing ); } diff --git a/doc/tutorials/imgproc/shapedescriptors/bounding_rotated_ellipses/bounding_rotated_ellipses.rst b/doc/tutorials/imgproc/shapedescriptors/bounding_rotated_ellipses/bounding_rotated_ellipses.rst index a8e996655..8e639fcf4 100644 --- a/doc/tutorials/imgproc/shapedescriptors/bounding_rotated_ellipses/bounding_rotated_ellipses.rst +++ b/doc/tutorials/imgproc/shapedescriptors/bounding_rotated_ellipses/bounding_rotated_ellipses.rst @@ -49,12 +49,12 @@ This tutorial code's is shown lines below. You can also download it from `here < 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 char* source_window = "Source"; - namedWindow( source_window, CV_WINDOW_AUTOSIZE ); + namedWindow( source_window, WINDOW_AUTOSIZE ); imshow( source_window, src ); createTrackbar( " Threshold:", "Source", &thresh, max_thresh, thresh_callback ); @@ -74,7 +74,7 @@ This tutorial code's is shown lines below. You can also download it from `here < /// 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 minRect( contours.size() ); @@ -102,7 +102,7 @@ This tutorial code's is shown lines below. You can also download it from `here < } /// Show in a window - namedWindow( "Contours", CV_WINDOW_AUTOSIZE ); + namedWindow( "Contours", WINDOW_AUTOSIZE ); imshow( "Contours", drawing ); } diff --git a/doc/tutorials/imgproc/shapedescriptors/find_contours/find_contours.rst b/doc/tutorials/imgproc/shapedescriptors/find_contours/find_contours.rst index ebb58f831..f3645e24d 100644 --- a/doc/tutorials/imgproc/shapedescriptors/find_contours/find_contours.rst +++ b/doc/tutorials/imgproc/shapedescriptors/find_contours/find_contours.rst @@ -47,12 +47,12 @@ This tutorial code's is shown lines below. You can also download it from `here < 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 char* source_window = "Source"; - namedWindow( source_window, CV_WINDOW_AUTOSIZE ); + namedWindow( source_window, WINDOW_AUTOSIZE ); imshow( source_window, src ); createTrackbar( " Canny thresh:", "Source", &thresh, max_thresh, thresh_callback ); @@ -72,7 +72,7 @@ This tutorial code's is shown lines below. You can also download it from `here < /// 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 ); @@ -83,7 +83,7 @@ This tutorial code's is shown lines below. You can also download it from `here < } /// Show in a window - namedWindow( "Contours", CV_WINDOW_AUTOSIZE ); + namedWindow( "Contours", WINDOW_AUTOSIZE ); imshow( "Contours", drawing ); } diff --git a/doc/tutorials/imgproc/shapedescriptors/hull/hull.rst b/doc/tutorials/imgproc/shapedescriptors/hull/hull.rst index 6a6bb62a4..1f35a7c92 100644 --- a/doc/tutorials/imgproc/shapedescriptors/hull/hull.rst +++ b/doc/tutorials/imgproc/shapedescriptors/hull/hull.rst @@ -47,12 +47,12 @@ This tutorial code's is shown lines below. You can also download it from `here < 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 char* source_window = "Source"; - namedWindow( source_window, CV_WINDOW_AUTOSIZE ); + namedWindow( source_window, WINDOW_AUTOSIZE ); imshow( source_window, src ); createTrackbar( " Threshold:", "Source", &thresh, max_thresh, thresh_callback ); @@ -74,7 +74,7 @@ This tutorial code's is shown lines below. You can also download it from `here < 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 >hull( contours.size() ); @@ -91,7 +91,7 @@ This tutorial code's is shown lines below. You can also download it from `here < } /// Show in a window - namedWindow( "Hull demo", CV_WINDOW_AUTOSIZE ); + namedWindow( "Hull demo", WINDOW_AUTOSIZE ); imshow( "Hull demo", drawing ); } diff --git a/doc/tutorials/imgproc/shapedescriptors/moments/moments.rst b/doc/tutorials/imgproc/shapedescriptors/moments/moments.rst index 537842850..a77c6ea74 100644 --- a/doc/tutorials/imgproc/shapedescriptors/moments/moments.rst +++ b/doc/tutorials/imgproc/shapedescriptors/moments/moments.rst @@ -49,12 +49,12 @@ This tutorial code's is shown lines below. You can also download it from `here < 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 char* source_window = "Source"; - namedWindow( source_window, CV_WINDOW_AUTOSIZE ); + namedWindow( source_window, WINDOW_AUTOSIZE ); imshow( source_window, src ); createTrackbar( " Canny thresh:", "Source", &thresh, max_thresh, thresh_callback ); @@ -74,7 +74,7 @@ This tutorial code's is shown lines below. You can also download it from `here < /// 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 mu(contours.size() ); @@ -96,7 +96,7 @@ This tutorial code's is shown lines below. You can also download it from `here < } /// Show in a window - namedWindow( "Contours", CV_WINDOW_AUTOSIZE ); + namedWindow( "Contours", WINDOW_AUTOSIZE ); imshow( "Contours", drawing ); /// Calculate the area with the moments 00 and compare with the result of the OpenCV function diff --git a/doc/tutorials/imgproc/shapedescriptors/point_polygon_test/point_polygon_test.rst b/doc/tutorials/imgproc/shapedescriptors/point_polygon_test/point_polygon_test.rst index 1f698108c..836159c8e 100644 --- a/doc/tutorials/imgproc/shapedescriptors/point_polygon_test/point_polygon_test.rst +++ b/doc/tutorials/imgproc/shapedescriptors/point_polygon_test/point_polygon_test.rst @@ -88,9 +88,9 @@ This tutorial code's is shown lines below. You can also download it from `here < /// Create Window and show your results char* source_window = "Source"; - namedWindow( source_window, CV_WINDOW_AUTOSIZE ); + namedWindow( source_window, WINDOW_AUTOSIZE ); imshow( source_window, src ); - namedWindow( "Distance", CV_WINDOW_AUTOSIZE ); + namedWindow( "Distance", WINDOW_AUTOSIZE ); imshow( "Distance", drawing ); waitKey(0); diff --git a/doc/tutorials/imgproc/threshold/threshold.rst b/doc/tutorials/imgproc/threshold/threshold.rst index e4ed3030c..960f3b2c9 100644 --- a/doc/tutorials/imgproc/threshold/threshold.rst +++ b/doc/tutorials/imgproc/threshold/threshold.rst @@ -167,10 +167,10 @@ The tutorial code's is shown lines below. You can also download it from `here ` function which loads the image name specifie .. container:: enumeratevisibleitemswithsquare - + CV_LOAD_IMAGE_UNCHANGED (<0) loads the image as is (including the alpha channel if present) - + CV_LOAD_IMAGE_GRAYSCALE ( 0) loads the image as an intensity one - + CV_LOAD_IMAGE_COLOR (>0) loads the image in the RGB format + + IMREAD_UNCHANGED (<0) loads the image as is (including the alpha channel if present) + + IMREAD_GRAYSCALE ( 0) loads the image as an intensity one + + IMREAD_COLOR (>0) loads the image in the RGB format .. literalinclude:: ../../../../samples/cpp/tutorial_code/introduction/display_image/display_image.cpp :language: cpp @@ -83,8 +83,8 @@ After checking that the image data was loaded correctly, we want to display our .. container:: enumeratevisibleitemswithsquare - + *CV_WINDOW_AUTOSIZE* is the only supported one if you do not use the Qt backend. In this case the window size will take up the size of the image it shows. No resize permitted! - + *CV_WINDOW_NORMAL* on Qt you may use this to allow window resize. The image will resize itself according to the current window size. By using the | operator you also need to specify if you would like the image to keep its aspect ratio (*CV_WINDOW_KEEPRATIO*) or not (*CV_WINDOW_FREERATIO*). + + *WINDOW_AUTOSIZE* is the only supported one if you do not use the Qt backend. In this case the window size will take up the size of the image it shows. No resize permitted! + + *WINDOW_NORMAL* on Qt you may use this to allow window resize. The image will resize itself according to the current window size. By using the | operator you also need to specify if you would like the image to keep its aspect ratio (*WINDOW_KEEPRATIO*) or not (*WINDOW_FREERATIO*). .. literalinclude:: ../../../../samples/cpp/tutorial_code/introduction/display_image/display_image.cpp :language: cpp diff --git a/doc/tutorials/introduction/load_save_image/load_save_image.rst b/doc/tutorials/introduction/load_save_image/load_save_image.rst index cde81e12b..1f494360e 100644 --- a/doc/tutorials/introduction/load_save_image/load_save_image.rst +++ b/doc/tutorials/introduction/load_save_image/load_save_image.rst @@ -68,7 +68,7 @@ Explanation .. code-block:: cpp - cvtColor( image, gray_image, CV_BGR2GRAY ); + cvtColor( image, gray_image, COLOR_BGR2GRAY ); As you can see, :miscellaneous_transformations:`cvtColor ` takes as arguments: @@ -76,7 +76,7 @@ Explanation * a source image (*image*) * a destination image (*gray_image*), in which we will save the converted image. - * an additional parameter that indicates what kind of transformation will be performed. In this case we use **CV_BGR2GRAY** (because of :readwriteimage:`imread ` has BGR default channel order in case of color images). + * an additional parameter that indicates what kind of transformation will be performed. In this case we use **COLOR_BGR2GRAY** (because of :readwriteimage:`imread ` has BGR default channel order in case of color images). #. So now we have our new *gray_image* and want to save it on disk (otherwise it will get lost after the program ends). To save it, we will use a function analagous to :readwriteimage:`imread `: :readwriteimage:`imwrite ` @@ -90,8 +90,8 @@ Explanation .. code-block:: cpp - namedWindow( imageName, CV_WINDOW_AUTOSIZE ); - namedWindow( "Gray image", CV_WINDOW_AUTOSIZE ); + namedWindow( imageName, WINDOW_AUTOSIZE ); + namedWindow( "Gray image", WINDOW_AUTOSIZE ); imshow( imageName, image ); imshow( "Gray image", gray_image ); diff --git a/doc/tutorials/introduction/windows_visual_studio_image_watch/windows_visual_studio_image_watch.rst b/doc/tutorials/introduction/windows_visual_studio_image_watch/windows_visual_studio_image_watch.rst index 21f679c97..19a4116a2 100644 --- a/doc/tutorials/introduction/windows_visual_studio_image_watch/windows_visual_studio_image_watch.rst +++ b/doc/tutorials/introduction/windows_visual_studio_image_watch/windows_visual_studio_image_watch.rst @@ -65,7 +65,7 @@ Image Watch works with any existing project that uses OpenCV image objects (for cout << "Loading input image: " << argv[1] << endl; Mat input; - input = imread(argv[1], CV_LOAD_IMAGE_COLOR); + input = imread(argv[1], IMREAD_COLOR); cout << "Detecting edges in input image" << endl; Mat edges; diff --git a/doc/tutorials/ios/image_manipulation/image_manipulation.rst b/doc/tutorials/ios/image_manipulation/image_manipulation.rst index 3eb8913be..d9851887d 100644 --- a/doc/tutorials/ios/image_manipulation/image_manipulation.rst +++ b/doc/tutorials/ios/image_manipulation/image_manipulation.rst @@ -70,7 +70,7 @@ After the processing we need to convert it back to UIImage. The code below can h .. code-block:: cpp cv::Mat greyMat; - cv::cvtColor(inputMat, greyMat, CV_BGR2GRAY); + cv::cvtColor(inputMat, greyMat, COLOR_BGR2GRAY); After the processing we need to convert it back to UIImage. diff --git a/doc/tutorials/ml/introduction_to_svm/introduction_to_svm.rst b/doc/tutorials/ml/introduction_to_svm/introduction_to_svm.rst index 574071de7..42d36d6b6 100644 --- a/doc/tutorials/ml/introduction_to_svm/introduction_to_svm.rst +++ b/doc/tutorials/ml/introduction_to_svm/introduction_to_svm.rst @@ -114,16 +114,16 @@ Explanation .. code-block:: cpp - CvSVMParams params; - params.svm_type = CvSVM::C_SVC; - params.kernel_type = CvSVM::LINEAR; - params.term_crit = cvTermCriteria(CV_TERMCRIT_ITER, 100, 1e-6); + ml::SVM::Params params; + params.svmType = ml::SVM::C_SVC; + params.kernelType = ml::SVM::LINEAR; + params.termCrit = TermCriteria(TermCriteria::MAX_ITER, 100, 1e-6); - * *Type of SVM*. We choose here the type **CvSVM::C_SVC** that can be used for n-class classification (n :math:`\geq` 2). This parameter is defined in the attribute *CvSVMParams.svm_type*. + * *Type of SVM*. We choose here the type **ml::SVM::C_SVC** that can be used for n-class classification (n :math:`\geq` 2). This parameter is defined in the attribute *ml::SVM::Params.svmType*. .. note:: The important feature of the type of SVM **CvSVM::C_SVC** deals with imperfect separation of classes (i.e. when the training data is non-linearly separable). This feature is not important here since the data is linearly separable and we chose this SVM type only for being the most commonly used. - * *Type of SVM kernel*. We have not talked about kernel functions since they are not interesting for the training data we are dealing with. Nevertheless, let's explain briefly now the main idea behind a kernel function. It is a mapping done to the training data to improve its resemblance to a linearly separable set of data. This mapping consists of increasing the dimensionality of the data and is done efficiently using a kernel function. We choose here the type **CvSVM::LINEAR** which means that no mapping is done. This parameter is defined in the attribute *CvSVMParams.kernel_type*. + * *Type of SVM kernel*. We have not talked about kernel functions since they are not interesting for the training data we are dealing with. Nevertheless, let's explain briefly now the main idea behind a kernel function. It is a mapping done to the training data to improve its resemblance to a linearly separable set of data. This mapping consists of increasing the dimensionality of the data and is done efficiently using a kernel function. We choose here the type **ml::SVM::LINEAR** which means that no mapping is done. This parameter is defined in the attribute *ml::SVMParams.kernel_type*. * *Termination criteria of the algorithm*. The SVM training procedure is implemented solving a constrained quadratic optimization problem in an **iterative** fashion. Here we specify a maximum number of iterations and a tolerance error so we allow the algorithm to finish in less number of steps even if the optimal hyperplane has not been computed yet. This parameter is defined in a structure :oldbasicstructures:`cvTermCriteria `. diff --git a/doc/tutorials/ml/non_linear_svms/non_linear_svms.rst b/doc/tutorials/ml/non_linear_svms/non_linear_svms.rst index bd7fde877..e7b0f9889 100644 --- a/doc/tutorials/ml/non_linear_svms/non_linear_svms.rst +++ b/doc/tutorials/ml/non_linear_svms/non_linear_svms.rst @@ -131,7 +131,7 @@ Explanation params.svm_type = SVM::C_SVC; params.C = 0.1; params.kernel_type = SVM::LINEAR; - params.term_crit = TermCriteria(CV_TERMCRIT_ITER, (int)1e7, 1e-6); + params.term_crit = TermCriteria(TermCriteria::ITER, (int)1e7, 1e-6); There are just two differences between the configuration we do here and the one that was done in the :ref:`previous tutorial ` that we use as reference. diff --git a/doc/user_guide/ug_features2d.rst b/doc/user_guide/ug_features2d.rst index e3ef302dc..37f2097ff 100644 --- a/doc/user_guide/ug_features2d.rst +++ b/doc/user_guide/ug_features2d.rst @@ -17,8 +17,8 @@ The code -------- We will start with a short sample ``opencv/samples/cpp/matcher_simple.cpp``: :: - Mat img1 = imread(argv[1], CV_LOAD_IMAGE_GRAYSCALE); - Mat img2 = imread(argv[2], CV_LOAD_IMAGE_GRAYSCALE); + Mat img1 = imread(argv[1], IMREAD_GRAYSCALE); + Mat img2 = imread(argv[2], IMREAD_GRAYSCALE); if(img1.empty() || img2.empty()) { printf("Can't read one of the images\n"); @@ -54,8 +54,8 @@ The code explained Let us break the code down. :: - Mat img1 = imread(argv[1], CV_LOAD_IMAGE_GRAYSCALE); - Mat img2 = imread(argv[2], CV_LOAD_IMAGE_GRAYSCALE); + Mat img1 = imread(argv[1], IMREAD_GRAYSCALE); + Mat img2 = imread(argv[2], IMREAD_GRAYSCALE); if(img1.empty() || img2.empty()) { printf("Can't read one of the images\n"); diff --git a/doc/user_guide/ug_highgui.rst b/doc/user_guide/ug_highgui.rst index 196714a5a..0250bf762 100644 --- a/doc/user_guide/ug_highgui.rst +++ b/doc/user_guide/ug_highgui.rst @@ -41,19 +41,19 @@ VideoCapture can retrieve the following data: #. data given from depth generator: - * ``CV_CAP_OPENNI_DEPTH_MAP`` - depth values in mm (CV_16UC1) - * ``CV_CAP_OPENNI_POINT_CLOUD_MAP`` - XYZ in meters (CV_32FC3) - * ``CV_CAP_OPENNI_DISPARITY_MAP`` - disparity in pixels (CV_8UC1) - * ``CV_CAP_OPENNI_DISPARITY_MAP_32F`` - disparity in pixels (CV_32FC1) - * ``CV_CAP_OPENNI_VALID_DEPTH_MASK`` - mask of valid pixels (not ocluded, not shaded etc.) (CV_8UC1) + * ``CAP_OPENNI_DEPTH_MAP`` - depth values in mm (CV_16UC1) + * ``CAP_OPENNI_POINT_CLOUD_MAP`` - XYZ in meters (CV_32FC3) + * ``CAP_OPENNI_DISPARITY_MAP`` - disparity in pixels (CV_8UC1) + * ``CAP_OPENNI_DISPARITY_MAP_32F`` - disparity in pixels (CV_32FC1) + * ``CAP_OPENNI_VALID_DEPTH_MASK`` - mask of valid pixels (not ocluded, not shaded etc.) (CV_8UC1) #. data given from RGB image generator: - * ``CV_CAP_OPENNI_BGR_IMAGE`` - color image (CV_8UC3) - * ``CV_CAP_OPENNI_GRAY_IMAGE`` - gray image (CV_8UC1) + * ``CAP_OPENNI_BGR_IMAGE`` - color image (CV_8UC3) + * ``CAP_OPENNI_GRAY_IMAGE`` - gray image (CV_8UC1) In order to get depth map from depth sensor use ``VideoCapture::operator >>``, e. g. :: - VideoCapture capture( CV_CAP_OPENNI ); + VideoCapture capture( CAP_OPENNI ); for(;;) { Mat depthMap; @@ -65,7 +65,7 @@ In order to get depth map from depth sensor use ``VideoCapture::operator >>``, e For getting several data maps use ``VideoCapture::grab`` and ``VideoCapture::retrieve``, e.g. :: - VideoCapture capture(0); // or CV_CAP_OPENNI + VideoCapture capture(0); // or CAP_OPENNI for(;;) { Mat depthMap; @@ -73,8 +73,8 @@ For getting several data maps use ``VideoCapture::grab`` and ``VideoCapture::ret capture.grab(); - capture.retrieve( depthMap, CV_CAP_OPENNI_DEPTH_MAP ); - capture.retrieve( bgrImage, CV_CAP_OPENNI_BGR_IMAGE ); + capture.retrieve( depthMap, CAP_OPENNI_DEPTH_MAP ); + capture.retrieve( bgrImage, CAP_OPENNI_BGR_IMAGE ); if( waitKey( 30 ) >= 0 ) break; @@ -82,20 +82,20 @@ For getting several data maps use ``VideoCapture::grab`` and ``VideoCapture::ret For setting and getting some property of sensor` data generators use ``VideoCapture::set`` and ``VideoCapture::get`` methods respectively, e.g. :: - VideoCapture capture( CV_CAP_OPENNI ); - capture.set( CV_CAP_OPENNI_IMAGE_GENERATOR_OUTPUT_MODE, CV_CAP_OPENNI_VGA_30HZ ); - cout << "FPS " << capture.get( CV_CAP_OPENNI_IMAGE_GENERATOR+CV_CAP_PROP_FPS ) << endl; + VideoCapture capture( CAP_OPENNI ); + capture.set( CAP_OPENNI_IMAGE_GENERATOR_OUTPUT_MODE, CAP_OPENNI_VGA_30HZ ); + cout << "FPS " << capture.get( CAP_OPENNI_IMAGE_GENERATOR+CAP_PROP_FPS ) << endl; Since two types of sensor's data generators are supported (image generator and depth generator), there are two flags that should be used to set/get property of the needed generator: -* CV_CAP_OPENNI_IMAGE_GENERATOR -- A flag for access to the image generator properties. +* CAP_OPENNI_IMAGE_GENERATOR -- A flag for access to the image generator properties. -* CV_CAP_OPENNI_DEPTH_GENERATOR -- A flag for access to the depth generator properties. This flag value is assumed by default if neither of the two possible values of the property is not set. +* CAP_OPENNI_DEPTH_GENERATOR -- A flag for access to the depth generator properties. This flag value is assumed by default if neither of the two possible values of the property is not set. -Some depth sensors (for example XtionPRO) do not have image generator. In order to check it you can get ``CV_CAP_OPENNI_IMAGE_GENERATOR_PRESENT`` property. +Some depth sensors (for example XtionPRO) do not have image generator. In order to check it you can get ``CAP_OPENNI_IMAGE_GENERATOR_PRESENT`` property. :: - bool isImageGeneratorPresent = capture.get( CV_CAP_PROP_OPENNI_IMAGE_GENERATOR_PRESENT ) != 0; // or == 1 + bool isImageGeneratorPresent = capture.get( CAP_PROP_OPENNI_IMAGE_GENERATOR_PRESENT ) != 0; // or == 1 Flags specifing the needed generator type must be used in combination with particular generator property. The following properties of cameras available through OpenNI interfaces are supported: @@ -103,30 +103,30 @@ Flags specifing the needed generator type must be used in combination with parti * For image generator: - - ``CV_CAP_PROP_OPENNI_OUTPUT_MODE`` -- Three output modes are supported: ``CV_CAP_OPENNI_VGA_30HZ`` used by default (image generator returns images in VGA resolution with 30 FPS), ``CV_CAP_OPENNI_SXGA_15HZ`` (image generator returns images in SXGA resolution with 15 FPS) and ``CV_CAP_OPENNI_SXGA_30HZ`` (image generator returns images in SXGA resolution with 30 FPS, the mode is supported by XtionPRO Live); depth generator's maps are always in VGA resolution. + - ``CAP_PROP_OPENNI_OUTPUT_MODE`` -- Three output modes are supported: ``CAP_OPENNI_VGA_30HZ`` used by default (image generator returns images in VGA resolution with 30 FPS), ``CAP_OPENNI_SXGA_15HZ`` (image generator returns images in SXGA resolution with 15 FPS) and ``CAP_OPENNI_SXGA_30HZ`` (image generator returns images in SXGA resolution with 30 FPS, the mode is supported by XtionPRO Live); depth generator's maps are always in VGA resolution. * For depth generator: - - ``CV_CAP_PROP_OPENNI_REGISTRATION`` -- Flag that registers the remapping depth map to image map by changing depth generator's view point (if the flag is ``"on"``) or sets this view point to its normal one (if the flag is ``"off"``). The registration process’s resulting images are pixel-aligned,which means that every pixel in the image is aligned to a pixel in the depth image. + - ``CAP_PROP_OPENNI_REGISTRATION`` -- Flag that registers the remapping depth map to image map by changing depth generator's view point (if the flag is ``"on"``) or sets this view point to its normal one (if the flag is ``"off"``). The registration process’s resulting images are pixel-aligned,which means that every pixel in the image is aligned to a pixel in the depth image. Next properties are available for getting only: - - ``CV_CAP_PROP_OPENNI_FRAME_MAX_DEPTH`` -- A maximum supported depth of Kinect in mm. - - ``CV_CAP_PROP_OPENNI_BASELINE`` -- Baseline value in mm. - - ``CV_CAP_PROP_OPENNI_FOCAL_LENGTH`` -- A focal length in pixels. - - ``CV_CAP_PROP_FRAME_WIDTH`` -- Frame width in pixels. - - ``CV_CAP_PROP_FRAME_HEIGHT`` -- Frame height in pixels. - - ``CV_CAP_PROP_FPS`` -- Frame rate in FPS. + - ``CAP_PROP_OPENNI_FRAME_MAX_DEPTH`` -- A maximum supported depth of Kinect in mm. + - ``CAP_PROP_OPENNI_BASELINE`` -- Baseline value in mm. + - ``CAP_PROP_OPENNI_FOCAL_LENGTH`` -- A focal length in pixels. + - ``CAP_PROP_FRAME_WIDTH`` -- Frame width in pixels. + - ``CAP_PROP_FRAME_HEIGHT`` -- Frame height in pixels. + - ``CAP_PROP_FPS`` -- Frame rate in FPS. * Some typical flags combinations "generator type + property" are defined as single flags: - - ``CV_CAP_OPENNI_IMAGE_GENERATOR_OUTPUT_MODE = CV_CAP_OPENNI_IMAGE_GENERATOR + CV_CAP_PROP_OPENNI_OUTPUT_MODE`` - - ``CV_CAP_OPENNI_DEPTH_GENERATOR_BASELINE = CV_CAP_OPENNI_DEPTH_GENERATOR + CV_CAP_PROP_OPENNI_BASELINE`` - - ``CV_CAP_OPENNI_DEPTH_GENERATOR_FOCAL_LENGTH = CV_CAP_OPENNI_DEPTH_GENERATOR + CV_CAP_PROP_OPENNI_FOCAL_LENGTH`` - - ``CV_CAP_OPENNI_DEPTH_GENERATOR_REGISTRATION = CV_CAP_OPENNI_DEPTH_GENERATOR + CV_CAP_PROP_OPENNI_REGISTRATION`` + - ``CAP_OPENNI_IMAGE_GENERATOR_OUTPUT_MODE = CAP_OPENNI_IMAGE_GENERATOR + CAP_PROP_OPENNI_OUTPUT_MODE`` + - ``CAP_OPENNI_DEPTH_GENERATOR_BASELINE = CAP_OPENNI_DEPTH_GENERATOR + CAP_PROP_OPENNI_BASELINE`` + - ``CAP_OPENNI_DEPTH_GENERATOR_FOCAL_LENGTH = CAP_OPENNI_DEPTH_GENERATOR + CAP_PROP_OPENNI_FOCAL_LENGTH`` + - ``CAP_OPENNI_DEPTH_GENERATOR_REGISTRATION = CAP_OPENNI_DEPTH_GENERATOR + CAP_PROP_OPENNI_REGISTRATION`` For more information please refer to the example of usage openni_capture.cpp_ in ``opencv/samples/cpp`` folder. diff --git a/doc/user_guide/ug_intelperc.rst b/doc/user_guide/ug_intelperc.rst index bae5f7014..9381760a0 100644 --- a/doc/user_guide/ug_intelperc.rst +++ b/doc/user_guide/ug_intelperc.rst @@ -24,16 +24,16 @@ VideoCapture can retrieve the following data: #. data given from depth generator: - * ``CV_CAP_INTELPERC_DEPTH_MAP`` - each pixel is a 16-bit integer. The value indicates the distance from an object to the camera's XY plane or the Cartesian depth. (CV_16UC1) - * ``CV_CAP_INTELPERC_UVDEPTH_MAP`` - each pixel contains two 32-bit floating point values in the range of 0-1, representing the mapping of depth coordinates to the color coordinates. (CV_32FC2) - * ``CV_CAP_INTELPERC_IR_MAP`` - each pixel is a 16-bit integer. The value indicates the intensity of the reflected laser beam. (CV_16UC1) + * ``CAP_INTELPERC_DEPTH_MAP`` - each pixel is a 16-bit integer. The value indicates the distance from an object to the camera's XY plane or the Cartesian depth. (CV_16UC1) + * ``CAP_INTELPERC_UVDEPTH_MAP`` - each pixel contains two 32-bit floating point values in the range of 0-1, representing the mapping of depth coordinates to the color coordinates. (CV_32FC2) + * ``CAP_INTELPERC_IR_MAP`` - each pixel is a 16-bit integer. The value indicates the intensity of the reflected laser beam. (CV_16UC1) #. data given from RGB image generator: - * ``CV_CAP_INTELPERC_IMAGE`` - color image. (CV_8UC3) + * ``CAP_INTELPERC_IMAGE`` - color image. (CV_8UC3) In order to get depth map from depth sensor use ``VideoCapture::operator >>``, e. g. :: - VideoCapture capture( CV_CAP_INTELPERC ); + VideoCapture capture( CAP_INTELPERC ); for(;;) { Mat depthMap; @@ -45,7 +45,7 @@ In order to get depth map from depth sensor use ``VideoCapture::operator >>``, e For getting several data maps use ``VideoCapture::grab`` and ``VideoCapture::retrieve``, e.g. :: - VideoCapture capture(CV_CAP_INTELPERC); + VideoCapture capture(CAP_INTELPERC); for(;;) { Mat depthMap; @@ -54,9 +54,9 @@ For getting several data maps use ``VideoCapture::grab`` and ``VideoCapture::ret capture.grab(); - capture.retrieve( depthMap, CV_CAP_INTELPERC_DEPTH_MAP ); - capture.retrieve( image, CV_CAP_INTELPERC_IMAGE ); - capture.retrieve( irImage, CV_CAP_INTELPERC_IR_MAP); + capture.retrieve( depthMap, CAP_INTELPERC_DEPTH_MAP ); + capture.retrieve( image, CAP_INTELPERC_IMAGE ); + capture.retrieve( irImage, CAP_INTELPERC_IR_MAP); if( waitKey( 30 ) >= 0 ) break; @@ -64,16 +64,16 @@ For getting several data maps use ``VideoCapture::grab`` and ``VideoCapture::ret For setting and getting some property of sensor` data generators use ``VideoCapture::set`` and ``VideoCapture::get`` methods respectively, e.g. :: - VideoCapture capture( CV_CAP_INTELPERC ); - capture.set( CV_CAP_INTELPERC_DEPTH_GENERATOR | CV_CAP_PROP_INTELPERC_PROFILE_IDX, 0 ); - cout << "FPS " << capture.get( CV_CAP_INTELPERC_DEPTH_GENERATOR+CV_CAP_PROP_FPS ) << endl; + VideoCapture capture( CAP_INTELPERC ); + capture.set( CAP_INTELPERC_DEPTH_GENERATOR | CAP_PROP_INTELPERC_PROFILE_IDX, 0 ); + cout << "FPS " << capture.get( CAP_INTELPERC_DEPTH_GENERATOR+CAP_PROP_FPS ) << endl; Since two types of sensor's data generators are supported (image generator and depth generator), there are two flags that should be used to set/get property of the needed generator: -* CV_CAP_INTELPERC_IMAGE_GENERATOR -- a flag for access to the image generator properties. +* CAP_INTELPERC_IMAGE_GENERATOR -- a flag for access to the image generator properties. -* CV_CAP_INTELPERC_DEPTH_GENERATOR -- a flag for access to the depth generator properties. This flag value is assumed by default if neither of the two possible values of the property is set. +* CAP_INTELPERC_DEPTH_GENERATOR -- a flag for access to the depth generator properties. This flag value is assumed by default if neither of the two possible values of the property is set. For more information please refer to the example of usage intelperc_capture.cpp_ in ``opencv/samples/cpp`` folder. -.. _intelperc_capture.cpp: https://github.com/Itseez/opencv/tree/master/samples/cpp/intelperc_capture.cpp \ No newline at end of file +.. _intelperc_capture.cpp: https://github.com/Itseez/opencv/tree/master/samples/cpp/intelperc_capture.cpp diff --git a/doc/user_guide/ug_mat.rst b/doc/user_guide/ug_mat.rst index d4cef8f23..a3d143a86 100644 --- a/doc/user_guide/ug_mat.rst +++ b/doc/user_guide/ug_mat.rst @@ -123,7 +123,7 @@ Conversion from color to grey scale: :: Mat img = imread("image.jpg"); // loading a 8UC3 image Mat grey; - cvtColor(img, grey, CV_BGR2GRAY); + cvtColor(img, grey, COLOR_BGR2GRAY); Change image type from 8UC1 to 32FC1: :: @@ -136,7 +136,7 @@ It is very useful to see intermediate results of your algorithm during developme Mat img = imread("image.jpg"); - namedWindow("image", CV_WINDOW_AUTOSIZE); + namedWindow("image", WINDOW_AUTOSIZE); imshow("image", img); waitKey(); @@ -144,7 +144,7 @@ A call to ``waitKey()`` starts a message passing cycle that waits for a key stro Mat img = imread("image.jpg"); Mat grey; - cvtColor(img, grey, CV_BGR2GRAY); + cvtColor(img, grey, COLOR_BGR2GRAY); Mat sobelx; Sobel(grey, sobelx, CV_32F, 1, 0); @@ -154,6 +154,6 @@ A call to ``waitKey()`` starts a message passing cycle that waits for a key stro Mat draw; sobelx.convertTo(draw, CV_8U, 255.0/(maxVal - minVal), -minVal * 255.0/(maxVal - minVal)); - namedWindow("image", CV_WINDOW_AUTOSIZE); + namedWindow("image", WINDOW_AUTOSIZE); imshow("image", draw); waitKey();