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change remaining c-api CV_ prefixes in constants

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This commit is contained in:
berak
2014-10-04 14:10:12 +02:00
parent b8457be394
commit 7cb3f3def7
49 changed files with 205 additions and 205 deletions
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doc/tutorials/imgproc/erosion_dilatation/erosion_dilatation.rst
+2 -2
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@@ -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
doc/tutorials/imgproc/gausian_median_blur_bilateral_filter/gausian_median_blur_bilateral_filter.rst
+2 -2
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@@ -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 );
doc/tutorials/imgproc/histograms/back_projection/back_projection.rst
+4 -4
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@@ -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);
doc/tutorials/imgproc/histograms/histogram_calculation/histogram_calculation.rst
+2 -2
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@@ -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);
doc/tutorials/imgproc/histograms/histogram_comparison/histogram_comparison.rst
+3 -3
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@@ -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):
doc/tutorials/imgproc/histograms/histogram_equalization/histogram_equalization.rst
+6 -6
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@@ -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 );
doc/tutorials/imgproc/histograms/template_matching/template_matching.rst
+6 -6
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@@ -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; }
doc/tutorials/imgproc/imgtrans/canny_detector/canny_detector.rst
+4 -4
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@@ -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:
doc/tutorials/imgproc/imgtrans/copyMakeBorder/copyMakeBorder.rst
+2 -2
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@@ -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*.
doc/tutorials/imgproc/imgtrans/filter_2d/filter_2d.rst
+2 -2
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@@ -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
doc/tutorials/imgproc/imgtrans/hough_circle/hough_circle.rst
+7 -7
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@@ -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<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++ )
@@ -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<Vec3f> 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
doc/tutorials/imgproc/imgtrans/hough_lines/hough_lines.rst
+4 -4
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@@ -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<Vec2f> 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<Vec4i> 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);
}
doc/tutorials/imgproc/imgtrans/laplace_operator/laplace_operator.rst
+3 -3
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@@ -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:
doc/tutorials/imgproc/imgtrans/remap/remap.rst
+5 -5
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@@ -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:
doc/tutorials/imgproc/imgtrans/sobel_derivatives/sobel_derivatives.rst
+3 -3
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@@ -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:
doc/tutorials/imgproc/imgtrans/warp_affine/warp_affine.rst
+6 -6
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@@ -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 );
doc/tutorials/imgproc/opening_closing_hats/opening_closing_hats.rst
+1 -1
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@@ -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 );
doc/tutorials/imgproc/pyramids/pyramids.rst
+2 -2
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@@ -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.
doc/tutorials/imgproc/shapedescriptors/bounding_rects_circles/bounding_rects_circles.rst
+4 -4
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@@ -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<vector<Point> > 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 );
}
doc/tutorials/imgproc/shapedescriptors/bounding_rotated_ellipses/bounding_rotated_ellipses.rst
+4 -4
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@@ -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<RotatedRect> 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 );
}
doc/tutorials/imgproc/shapedescriptors/find_contours/find_contours.rst
+4 -4
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@@ -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 );
}
doc/tutorials/imgproc/shapedescriptors/hull/hull.rst
+4 -4
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@@ -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<vector<Point> >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 );
}
doc/tutorials/imgproc/shapedescriptors/moments/moments.rst
+4 -4
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@@ -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<Moments> 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
doc/tutorials/imgproc/shapedescriptors/point_polygon_test/point_polygon_test.rst
+2 -2
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@@ -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);
doc/tutorials/imgproc/threshold/threshold.rst
+4 -4
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@@ -167,10 +167,10 @@ The tutorial code's is shown lines below. You can also download it from `here <h
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 );
namedWindow( window_name, WINDOW_AUTOSIZE );
/// Create Trackbar to choose type of Threshold
createTrackbar( trackbar_type,
@@ -228,14 +228,14 @@ Explanation
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 the result
.. code-block:: cpp
namedWindow( window_name, CV_WINDOW_AUTOSIZE );
namedWindow( window_name, WINDOW_AUTOSIZE );
* Create :math:`2` trackbars for the user to enter user input: