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Update features2d.hpp, agast.cpp, fast.cpp
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@ -516,7 +516,9 @@ public:
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//! @addtogroup features2d_main
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//! @{
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/** @brief Wrapping class for feature detection using the FAST method. :
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/** @brief Wrapping class for feature detection using the FAST method.
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Check @ref tutorial_py_fast "the corresponding tutorial" for more details.
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*/
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class CV_EXPORTS_W FastFeatureDetector : public Feature2D
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{
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@ -546,30 +548,23 @@ public:
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CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
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};
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/** @overload */
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CV_EXPORTS void FAST( InputArray image, CV_OUT std::vector<KeyPoint>& keypoints,
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int threshold, bool nonmaxSuppression=true );
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/** @brief Detects corners using the FAST algorithm
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@param image grayscale image where keypoints (corners) are detected.
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@param keypoints keypoints detected on the image.
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@param threshold threshold on difference between intensity of the central pixel and pixels of a
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circle around this pixel.
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@param nonmaxSuppression if true, non-maximum suppression is applied to detected corners
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(keypoints).
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@param nonmaxSuppression if true, non-maximum suppression is applied to detected keypoints (corners).
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@param type one of the three neighborhoods as defined in the paper:
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FastFeatureDetector::TYPE_9_16, FastFeatureDetector::TYPE_7_12,
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FastFeatureDetector::TYPE_5_8
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Detects corners using the FAST algorithm by @cite Rosten06 .
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@note In Python API, types are given as cv.FAST_FEATURE_DETECTOR_TYPE_5_8,
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cv.FAST_FEATURE_DETECTOR_TYPE_7_12 and cv.FAST_FEATURE_DETECTOR_TYPE_9_16. For corner
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detection, use cv.FAST.detect() method.
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Check @ref tutorial_py_fast "the corresponding tutorial" for more details.
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*/
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CV_EXPORTS void FAST( InputArray image, CV_OUT std::vector<KeyPoint>& keypoints,
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int threshold, bool nonmaxSuppression, FastFeatureDetector::DetectorType type );
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int threshold, bool nonmaxSuppression=true, FastFeatureDetector::DetectorType type=FastFeatureDetector::TYPE_9_16 );
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//! @} features2d_main
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@ -606,18 +601,13 @@ public:
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CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
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};
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/** @overload */
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CV_EXPORTS void AGAST( InputArray image, CV_OUT std::vector<KeyPoint>& keypoints,
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int threshold, bool nonmaxSuppression=true );
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/** @brief Detects corners using the AGAST algorithm
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@param image grayscale image where keypoints (corners) are detected.
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@param keypoints keypoints detected on the image.
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@param threshold threshold on difference between intensity of the central pixel and pixels of a
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circle around this pixel.
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@param nonmaxSuppression if true, non-maximum suppression is applied to detected corners
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(keypoints).
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@param nonmaxSuppression if true, non-maximum suppression is applied to detected keypoints (corners).
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@param type one of the four neighborhoods as defined in the paper:
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AgastFeatureDetector::AGAST_5_8, AgastFeatureDetector::AGAST_7_12d,
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AgastFeatureDetector::AGAST_7_12s, AgastFeatureDetector::OAST_9_16
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@ -629,7 +619,7 @@ Detects corners using the AGAST algorithm by @cite mair2010_agast .
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*/
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CV_EXPORTS void AGAST( InputArray image, CV_OUT std::vector<KeyPoint>& keypoints,
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int threshold, bool nonmaxSuppression, AgastFeatureDetector::DetectorType type );
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int threshold, bool nonmaxSuppression=true, AgastFeatureDetector::DetectorType type=AgastFeatureDetector::OAST_9_16 );
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/** @brief Wrapping class for feature detection using the goodFeaturesToTrack function. :
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*/
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@ -7934,13 +7934,6 @@ static void OAST_9_16(InputArray _img, std::vector<KeyPoint>& keypoints, int thr
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#endif // !(defined __i386__ || defined(_M_IX86) || defined __x86_64__ || defined(_M_X64))
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void AGAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool nonmax_suppression)
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{
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CV_INSTRUMENT_REGION();
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AGAST(_img, keypoints, threshold, nonmax_suppression, AgastFeatureDetector::OAST_9_16);
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}
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class AgastFeatureDetector_Impl CV_FINAL : public AgastFeatureDetector
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{
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public:
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@ -524,14 +524,6 @@ void FAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool
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}
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void FAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool nonmax_suppression)
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{
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CV_INSTRUMENT_REGION();
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FAST(_img, keypoints, threshold, nonmax_suppression, FastFeatureDetector::TYPE_9_16);
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}
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class FastFeatureDetector_Impl CV_FINAL : public FastFeatureDetector
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{
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public:
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