Merge pull request #224 from wswld:2.4

This commit is contained in:
Andrey Kamaev 2012-12-15 16:06:32 +04:00 committed by OpenCV Buildbot
commit 3de6846d12
4 changed files with 8 additions and 6 deletions

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@ -85,7 +85,7 @@ This tutorial code's is shown lines below. You can also download it from `here <
for( int i = 0; i < contours.size(); i++ )
{ approxPolyDP( Mat(contours[i]), contours_poly[i], 3, true );
boundRect[i] = boundingRect( Mat(contours_poly[i]) );
minEnclosingCircle( contours_poly[i], center[i], radius[i] );
minEnclosingCircle( (Mat)contours_poly[i], center[i], radius[i] );
}

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@ -71,7 +71,9 @@ There are functions in OpenCV, especially from calib3d module, such as ``project
//... fill the array
Mat pointsMat = Mat(points);
One can access a point in this matrix using the same method \texttt{Mat::at}: ::
One can access a point in this matrix using the same method ``Mat::at`` :
::
Point2f point = pointsMat.at<Point2f>(i, 0);
@ -109,7 +111,7 @@ Selecting a region of interest: ::
Rect r(10, 10, 100, 100);
Mat smallImg = img(r);
A convertion from \texttt{Mat} to C API data structures: ::
A convertion from ``Mat`` to C API data structures: ::
Mat img = imread("image.jpg");
IplImage img1 = img;
@ -150,7 +152,7 @@ A call to ``waitKey()`` starts a message passing cycle that waits for a key stro
double minVal, maxVal;
minMaxLoc(sobelx, &minVal, &maxVal); //find minimum and maximum intensities
Mat draw;
sobelx.convertTo(draw, CV_8U, 255.0/(maxVal - minVal), -minVal);
sobelx.convertTo(draw, CV_8U, 255.0/(maxVal - minVal), -minVal * 255.0/(maxVal - minVal));
namedWindow("image", CV_WINDOW_AUTOSIZE);
imshow("image", draw);

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@ -661,7 +661,7 @@ Applies a fixed-level threshold to each array element.
:param dst: output array of the same size and type as ``src``.
:param thresh: treshold value.
:param thresh: threshold value.
:param maxval: maximum value to use with the ``THRESH_BINARY`` and ``THRESH_BINARY_INV`` thresholding types.

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@ -137,7 +137,7 @@ Finds contours in a binary image.
:param contours: Detected contours. Each contour is stored as a vector of points.
:param hierarchy: Optional output vector containing information about the image topology. It has as many elements as the number of contours. For each contour ``contours[i]`` , the elements ``hierarchy[i][0]`` , ``hiearchy[i][1]`` , ``hiearchy[i][2]`` , and ``hiearchy[i][3]`` are set to 0-based indices in ``contours`` of the next and previous contours at the same hierarchical level: the first child contour and the parent contour, respectively. If for a contour ``i`` there are no next, previous, parent, or nested contours, the corresponding elements of ``hierarchy[i]`` will be negative.
:param hierarchy: Optional output vector, containing information about the image topology. It has as many elements as the number of contours. For each i-th contour ``contours[i]`` , the elements ``hierarchy[i][0]`` , ``hiearchy[i][1]`` , ``hiearchy[i][2]`` , and ``hiearchy[i][3]`` are set to 0-based indices in ``contours`` of the next and previous contours at the same hierarchical level, the first child contour and the parent contour, respectively. If for the contour ``i`` there are no next, previous, parent, or nested contours, the corresponding elements of ``hierarchy[i]`` will be negative.
:param mode: Contour retrieval mode (if you use Python see also a note below).