generic-library/opencv
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fixed some more compile errors and test failures

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This commit is contained in:
Vadim Pisarevsky
2014-10-17 14:22:02 +04:00
parent d36b546df8
commit 1176d4ef84
16 changed files with 165 additions and 136 deletions
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7
modules/features2d/doc/feature_detection_and_description.rst
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@@ -14,11 +14,6 @@ Detects corners using the FAST algorithm
.. ocv:function:: void FAST( InputArray image, vector<KeyPoint>& keypoints, int threshold, bool nonmaxSuppression=true )
.. ocv:function:: void FAST( InputArray image, vector<KeyPoint>& keypoints, int threshold, bool nonmaxSuppression, int type )
.. ocv:pyfunction:: cv2.FastFeatureDetector([, threshold[, nonmaxSuppression]]) -> <FastFeatureDetector object>
.. ocv:pyfunction:: cv2.FastFeatureDetector(threshold, nonmaxSuppression, type) -> <FastFeatureDetector object>
.. ocv:pyfunction:: cv2.FastFeatureDetector.detect(image[, mask]) -> keypoints
:param image: grayscale image where keypoints (corners) are detected.
:param keypoints: keypoints detected on the image.
@@ -55,7 +50,7 @@ Maximally stable extremal region extractor. ::
// runs the extractor on the specified image; returns the MSERs,
// each encoded as a contour (vector<Point>, see findContours)
// the optional mask marks the area where MSERs are searched for
void operator()( const Mat& image, vector<vector<Point> >& msers, const Mat& mask ) const;
void detectRegions( InputArray image, vector<vector<Point> >& msers, vector<Rect>& bboxes ) const;
};
The class encapsulates all the parameters of the MSER extraction algorithm (see