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@ -293,7 +293,8 @@ k-tuples) are rotated according to the measured orientation). |
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class CV_EXPORTS_W ORB : public Feature2D |
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{ |
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public: |
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enum { kBytes = 32, HARRIS_SCORE=0, FAST_SCORE=1 }; |
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enum ScoreType { HARRIS_SCORE=0, FAST_SCORE=1 }; |
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static const int kBytes = 32; |
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/** @brief The ORB constructor
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@ -327,7 +328,7 @@ public: |
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@param fastThreshold |
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*/ |
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CV_WRAP static Ptr<ORB> create(int nfeatures=500, float scaleFactor=1.2f, int nlevels=8, int edgeThreshold=31, |
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int firstLevel=0, int WTA_K=2, int scoreType=ORB::HARRIS_SCORE, int patchSize=31, int fastThreshold=20); |
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int firstLevel=0, int WTA_K=2, ORB::ScoreType scoreType=ORB::HARRIS_SCORE, int patchSize=31, int fastThreshold=20); |
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CV_WRAP virtual void setMaxFeatures(int maxFeatures) = 0; |
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CV_WRAP virtual int getMaxFeatures() const = 0; |
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@ -347,8 +348,8 @@ public: |
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CV_WRAP virtual void setWTA_K(int wta_k) = 0; |
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CV_WRAP virtual int getWTA_K() const = 0; |
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CV_WRAP virtual void setScoreType(int scoreType) = 0; |
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CV_WRAP virtual int getScoreType() const = 0; |
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CV_WRAP virtual void setScoreType(ORB::ScoreType scoreType) = 0; |
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CV_WRAP virtual ORB::ScoreType getScoreType() const = 0; |
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CV_WRAP virtual void setPatchSize(int patchSize) = 0; |
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CV_WRAP virtual int getPatchSize() const = 0; |
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@ -418,6 +419,41 @@ public: |
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CV_WRAP virtual String getDefaultName() const CV_OVERRIDE; |
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}; |
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//! @} features2d_main
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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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*/ |
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class CV_EXPORTS_W FastFeatureDetector : public Feature2D |
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{ |
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public: |
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enum DetectorType |
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{ |
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TYPE_5_8 = 0, TYPE_7_12 = 1, TYPE_9_16 = 2 |
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}; |
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enum
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{ |
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THRESHOLD = 10000, NONMAX_SUPPRESSION=10001, FAST_N=10002 |
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}; |
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CV_WRAP static Ptr<FastFeatureDetector> create( int threshold=10, |
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bool nonmaxSuppression=true, |
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FastFeatureDetector::DetectorType type=FastFeatureDetector::TYPE_9_16 ); |
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CV_WRAP virtual void setThreshold(int threshold) = 0; |
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CV_WRAP virtual int getThreshold() const = 0; |
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CV_WRAP virtual void setNonmaxSuppression(bool f) = 0; |
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CV_WRAP virtual bool getNonmaxSuppression() const = 0; |
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CV_WRAP virtual void setType(FastFeatureDetector::DetectorType type) = 0; |
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CV_WRAP virtual FastFeatureDetector::DetectorType getType() const = 0; |
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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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@ -441,27 +477,31 @@ cv2.FAST_FEATURE_DETECTOR_TYPE_7_12 and cv2.FAST_FEATURE_DETECTOR_TYPE_9_16. For |
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detection, use cv2.FAST.detect() method. |
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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, int type ); |
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int threshold, bool nonmaxSuppression, FastFeatureDetector::DetectorType type ); |
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//! @} features2d_main
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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 AGAST method. :
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*/ |
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class CV_EXPORTS_W FastFeatureDetector : public Feature2D |
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class CV_EXPORTS_W AgastFeatureDetector : public Feature2D |
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{ |
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public: |
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enum DetectorType |
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{ |
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AGAST_5_8 = 0, AGAST_7_12d = 1, AGAST_7_12s = 2, OAST_9_16 = 3, |
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}; |
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enum
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{ |
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TYPE_5_8 = 0, TYPE_7_12 = 1, TYPE_9_16 = 2, |
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THRESHOLD = 10000, NONMAX_SUPPRESSION=10001, FAST_N=10002, |
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THRESHOLD = 10000, NONMAX_SUPPRESSION = 10001, |
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}; |
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CV_WRAP static Ptr<FastFeatureDetector> create( int threshold=10, |
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bool nonmaxSuppression=true, |
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int type=FastFeatureDetector::TYPE_9_16 ); |
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CV_WRAP static Ptr<AgastFeatureDetector> create( int threshold=10, |
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bool nonmaxSuppression=true, |
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AgastFeatureDetector::DetectorType type = AgastFeatureDetector::OAST_9_16); |
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CV_WRAP virtual void setThreshold(int threshold) = 0; |
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CV_WRAP virtual int getThreshold() const = 0; |
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@ -469,8 +509,8 @@ public: |
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CV_WRAP virtual void setNonmaxSuppression(bool f) = 0; |
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CV_WRAP virtual bool getNonmaxSuppression() const = 0; |
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CV_WRAP virtual void setType(int type) = 0; |
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CV_WRAP virtual int getType() const = 0; |
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CV_WRAP virtual void setType(AgastFeatureDetector::DetectorType type) = 0; |
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CV_WRAP virtual AgastFeatureDetector::DetectorType getType() const = 0; |
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CV_WRAP virtual String getDefaultName() const CV_OVERRIDE; |
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}; |
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@ -497,37 +537,7 @@ 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, int type ); |
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//! @} features2d_main
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//! @addtogroup features2d_main
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//! @{
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/** @brief Wrapping class for feature detection using the AGAST method. :
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*/ |
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class CV_EXPORTS_W AgastFeatureDetector : public Feature2D |
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{ |
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public: |
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enum
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{ |
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AGAST_5_8 = 0, AGAST_7_12d = 1, AGAST_7_12s = 2, OAST_9_16 = 3, |
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THRESHOLD = 10000, NONMAX_SUPPRESSION = 10001, |
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}; |
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CV_WRAP static Ptr<AgastFeatureDetector> create( int threshold=10, |
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bool nonmaxSuppression=true, |
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int type=AgastFeatureDetector::OAST_9_16 ); |
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CV_WRAP virtual void setThreshold(int threshold) = 0; |
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CV_WRAP virtual int getThreshold() const = 0; |
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CV_WRAP virtual void setNonmaxSuppression(bool f) = 0; |
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CV_WRAP virtual bool getNonmaxSuppression() const = 0; |
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CV_WRAP virtual void setType(int type) = 0; |
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CV_WRAP virtual int getType() const = 0; |
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CV_WRAP virtual String getDefaultName() const CV_OVERRIDE; |
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}; |
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int threshold, bool nonmaxSuppression, AgastFeatureDetector::DetectorType type ); |
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/** @brief Wrapping class for feature detection using the goodFeaturesToTrack function. :
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*/ |
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@ -639,7 +649,7 @@ F. Alcantarilla, Adrien Bartoli and Andrew J. Davison. In European Conference on |
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class CV_EXPORTS_W KAZE : public Feature2D |
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{ |
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public: |
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enum
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enum DiffusivityType |
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{ |
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DIFF_PM_G1 = 0, |
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DIFF_PM_G2 = 1, |
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@ -660,7 +670,7 @@ public: |
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CV_WRAP static Ptr<KAZE> create(bool extended=false, bool upright=false, |
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float threshold = 0.001f, |
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int nOctaves = 4, int nOctaveLayers = 4, |
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int diffusivity = KAZE::DIFF_PM_G2); |
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KAZE::DiffusivityType diffusivity = KAZE::DIFF_PM_G2); |
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CV_WRAP virtual void setExtended(bool extended) = 0; |
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CV_WRAP virtual bool getExtended() const = 0; |
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@ -677,8 +687,8 @@ public: |
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CV_WRAP virtual void setNOctaveLayers(int octaveLayers) = 0; |
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CV_WRAP virtual int getNOctaveLayers() const = 0; |
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CV_WRAP virtual void setDiffusivity(int diff) = 0; |
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CV_WRAP virtual int getDiffusivity() const = 0; |
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CV_WRAP virtual void setDiffusivity(KAZE::DiffusivityType diff) = 0; |
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CV_WRAP virtual KAZE::DiffusivityType getDiffusivity() const = 0; |
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CV_WRAP virtual String getDefaultName() const CV_OVERRIDE; |
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}; |
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@ -702,7 +712,7 @@ class CV_EXPORTS_W AKAZE : public Feature2D |
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{ |
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public: |
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// AKAZE descriptor type
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enum
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enum DescriptorType |
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{ |
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DESCRIPTOR_KAZE_UPRIGHT = 2, ///< Upright descriptors, not invariant to rotation
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DESCRIPTOR_KAZE = 3, |
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@ -722,13 +732,13 @@ public: |
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@param diffusivity Diffusivity type. DIFF_PM_G1, DIFF_PM_G2, DIFF_WEICKERT or |
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DIFF_CHARBONNIER |
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*/ |
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CV_WRAP static Ptr<AKAZE> create(int descriptor_type=AKAZE::DESCRIPTOR_MLDB, |
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CV_WRAP static Ptr<AKAZE> create(AKAZE::DescriptorType descriptor_type = AKAZE::DESCRIPTOR_MLDB, |
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int descriptor_size = 0, int descriptor_channels = 3, |
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float threshold = 0.001f, int nOctaves = 4, |
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int nOctaveLayers = 4, int diffusivity = KAZE::DIFF_PM_G2); |
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int nOctaveLayers = 4, KAZE::DiffusivityType diffusivity = KAZE::DIFF_PM_G2); |
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CV_WRAP virtual void setDescriptorType(int dtype) = 0; |
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CV_WRAP virtual int getDescriptorType() const = 0; |
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CV_WRAP virtual void setDescriptorType(AKAZE::DescriptorType dtype) = 0; |
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CV_WRAP virtual AKAZE::DescriptorType getDescriptorType() const = 0; |
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CV_WRAP virtual void setDescriptorSize(int dsize) = 0; |
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CV_WRAP virtual int getDescriptorSize() const = 0; |
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@ -745,8 +755,8 @@ public: |
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CV_WRAP virtual void setNOctaveLayers(int octaveLayers) = 0; |
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CV_WRAP virtual int getNOctaveLayers() const = 0; |
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CV_WRAP virtual void setDiffusivity(int diff) = 0; |
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CV_WRAP virtual int getDiffusivity() const = 0; |
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CV_WRAP virtual void setDiffusivity(KAZE::DiffusivityType diff) = 0; |
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CV_WRAP virtual KAZE::DiffusivityType getDiffusivity() const = 0; |
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CV_WRAP virtual String getDefaultName() const CV_OVERRIDE; |
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}; |
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@ -773,7 +783,7 @@ template<> struct Accumulator<short> { typedef float Type; }; |
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template<class T> |
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struct CV_EXPORTS SL2 |
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{ |
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enum { normType = NORM_L2SQR }; |
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static const NormTypes normType = NORM_L2SQR; |
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typedef T ValueType; |
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typedef typename Accumulator<T>::Type ResultType; |
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@ -789,7 +799,7 @@ struct CV_EXPORTS SL2 |
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template<class T> |
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struct L2 |
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{ |
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enum { normType = NORM_L2 }; |
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static const NormTypes normType = NORM_L2; |
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typedef T ValueType; |
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typedef typename Accumulator<T>::Type ResultType; |
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@ -805,7 +815,7 @@ struct L2 |
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template<class T> |
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struct L1 |
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{ |
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enum { normType = NORM_L1 }; |
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static const NormTypes normType = NORM_L1; |
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typedef T ValueType; |
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typedef typename Accumulator<T>::Type ResultType; |
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@ -830,7 +840,7 @@ an image set. |
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class CV_EXPORTS_W DescriptorMatcher : public Algorithm |
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{ |
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public: |
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enum
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enum MatcherType |
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{ |
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FLANNBASED = 1, |
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BRUTEFORCE = 2, |
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@ -839,6 +849,7 @@ public: |
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BRUTEFORCE_HAMMINGLUT = 5, |
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BRUTEFORCE_SL2 = 6 |
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}; |
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virtual ~DescriptorMatcher(); |
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/** @brief Adds descriptors to train a CPU(trainDescCollectionis) or GPU(utrainDescCollectionis) descriptor
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@ -1016,7 +1027,7 @@ public: |
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*/ |
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CV_WRAP static Ptr<DescriptorMatcher> create( const String& descriptorMatcherType ); |
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CV_WRAP static Ptr<DescriptorMatcher> create( int matcherType ); |
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CV_WRAP static Ptr<DescriptorMatcher> create( const DescriptorMatcher::MatcherType& matcherType ); |
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// see corresponding cv::Algorithm method
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@ -1171,20 +1182,20 @@ protected: |
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//! @addtogroup features2d_draw
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//! @{
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struct CV_EXPORTS DrawMatchesFlags |
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enum struct DrawMatchesFlags |
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{ |
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enum{ DEFAULT = 0, //!< Output image matrix will be created (Mat::create),
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//!< i.e. existing memory of output image may be reused.
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//!< Two source image, matches and single keypoints will be drawn.
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//!< For each keypoint only the center point will be drawn (without
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//!< the circle around keypoint with keypoint size and orientation).
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DRAW_OVER_OUTIMG = 1, //!< Output image matrix will not be created (Mat::create).
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//!< Matches will be drawn on existing content of output image.
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NOT_DRAW_SINGLE_POINTS = 2, //!< Single keypoints will not be drawn.
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DRAW_RICH_KEYPOINTS = 4 //!< For each keypoint the circle around keypoint with keypoint size and
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//!< orientation will be drawn.
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}; |
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DEFAULT = 0, //!< Output image matrix will be created (Mat::create),
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//!< i.e. existing memory of output image may be reused.
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//!< Two source image, matches and single keypoints will be drawn.
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//!< For each keypoint only the center point will be drawn (without
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//!< the circle around keypoint with keypoint size and orientation).
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DRAW_OVER_OUTIMG = 1, //!< Output image matrix will not be created (Mat::create).
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//!< Matches will be drawn on existing content of output image.
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NOT_DRAW_SINGLE_POINTS = 2, //!< Single keypoints will not be drawn.
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DRAW_RICH_KEYPOINTS = 4 //!< For each keypoint the circle around keypoint with keypoint size and
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//!< orientation will be drawn.
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}; |
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CV_ENUM_FLAGS(DrawMatchesFlags); |
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/** @brief Draws keypoints.
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@ -1202,7 +1213,7 @@ cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS, cv2.DRAW_MATCHES_FLAGS_DRAW_OVER_OUT |
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cv2.DRAW_MATCHES_FLAGS_NOT_DRAW_SINGLE_POINTS |
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*/ |
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CV_EXPORTS_W void drawKeypoints( InputArray image, const std::vector<KeyPoint>& keypoints, InputOutputArray outImage, |
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const Scalar& color=Scalar::all(-1), int flags=DrawMatchesFlags::DEFAULT ); |
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const Scalar& color=Scalar::all(-1), DrawMatchesFlags flags=DrawMatchesFlags::DEFAULT ); |
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/** @brief Draws the found matches of keypoints from two images.
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@ -1230,14 +1241,14 @@ CV_EXPORTS_W void drawMatches( InputArray img1, const std::vector<KeyPoint>& key |
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InputArray img2, const std::vector<KeyPoint>& keypoints2, |
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const std::vector<DMatch>& matches1to2, InputOutputArray outImg, |
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const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1), |
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const std::vector<char>& matchesMask=std::vector<char>(), int flags=DrawMatchesFlags::DEFAULT ); |
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const std::vector<char>& matchesMask=std::vector<char>(), DrawMatchesFlags flags=DrawMatchesFlags::DEFAULT ); |
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/** @overload */ |
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CV_EXPORTS_AS(drawMatchesKnn) void drawMatches( InputArray img1, const std::vector<KeyPoint>& keypoints1, |
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InputArray img2, const std::vector<KeyPoint>& keypoints2, |
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const std::vector<std::vector<DMatch> >& matches1to2, InputOutputArray outImg, |
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const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1), |
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const std::vector<std::vector<char> >& matchesMask=std::vector<std::vector<char> >(), int flags=DrawMatchesFlags::DEFAULT ); |
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const std::vector<std::vector<char> >& matchesMask=std::vector<std::vector<char> >(), DrawMatchesFlags flags=DrawMatchesFlags::DEFAULT ); |
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//! @} features2d_draw
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Hamdi Sahloul
7 years ago
committed by
Alexander Alekhin