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Merge pull request #12310 from cv3d:chunks/enum_interface

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* Cleanup macros and enable expansion of `__VA_ARGS__` for Visual Studio

* Macros for enum-arguments backwards compatibility

* Convert struct Param to enum struct

* Enabled ParamType.type for enum types

* Enabled `cv.read` and `cv.write` for enum types

* Rename unnamed enum to AAKAZE.DescriptorType

* Rename unnamed enum to AccessFlag

* Rename unnamed enum to AgastFeatureDetector.DetectorType

* Convert struct DrawMatchesFlags to enum struct

* Rename unnamed enum to FastFeatureDetector.DetectorType

* Rename unnamed enum to Formatter.FormatType

* Rename unnamed enum to HOGDescriptor.HistogramNormType

* Rename unnamed enum to DescriptorMatcher.MatcherType

* Rename unnamed enum to KAZE.DiffusivityType

* Rename unnamed enum to ORB.ScoreType

* Rename unnamed enum to UMatData.MemoryFlag

* Rename unnamed enum to _InputArray.KindFlag

* Rename unnamed enum to _OutputArray.DepthMask

* Convert normType enums to static const NormTypes

* Avoid conflicts with ElemType

* Rename unnamed enum to DescriptorStorageFormat
This commit is contained in:
Hamdi Sahloul
2018-09-22 00:12:35 +09:00
committed by Alexander Alekhin
parent 84ae8097b1
commit ef5579dc86
51 changed files with 567 additions and 333 deletions
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modules/features2d/include/opencv2/features2d.hpp
+88 -77
View File
@@ -293,7 +293,8 @@ k-tuples) are rotated according to the measured orientation).
class CV_EXPORTS_W ORB : public Feature2D
{
public:
enum { kBytes = 32, HARRIS_SCORE=0, FAST_SCORE=1 };
enum ScoreType { HARRIS_SCORE=0, FAST_SCORE=1 };
static const int kBytes = 32;
/** @brief The ORB constructor
@@ -327,7 +328,7 @@ public:
@param fastThreshold
*/
CV_WRAP static Ptr<ORB> create(int nfeatures=500, float scaleFactor=1.2f, int nlevels=8, int edgeThreshold=31,
int firstLevel=0, int WTA_K=2, int scoreType=ORB::HARRIS_SCORE, int patchSize=31, int fastThreshold=20);
int firstLevel=0, int WTA_K=2, ORB::ScoreType scoreType=ORB::HARRIS_SCORE, int patchSize=31, int fastThreshold=20);
CV_WRAP virtual void setMaxFeatures(int maxFeatures) = 0;
CV_WRAP virtual int getMaxFeatures() const = 0;
@@ -347,8 +348,8 @@ public:
CV_WRAP virtual void setWTA_K(int wta_k) = 0;
CV_WRAP virtual int getWTA_K() const = 0;
CV_WRAP virtual void setScoreType(int scoreType) = 0;
CV_WRAP virtual int getScoreType() const = 0;
CV_WRAP virtual void setScoreType(ORB::ScoreType scoreType) = 0;
CV_WRAP virtual ORB::ScoreType getScoreType() const = 0;
CV_WRAP virtual void setPatchSize(int patchSize) = 0;
CV_WRAP virtual int getPatchSize() const = 0;
@@ -418,6 +419,41 @@ public:
CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
};
//! @} features2d_main
//! @addtogroup features2d_main
//! @{
/** @brief Wrapping class for feature detection using the FAST method. :
*/
class CV_EXPORTS_W FastFeatureDetector : public Feature2D
{
public:
enum DetectorType
{
TYPE_5_8 = 0, TYPE_7_12 = 1, TYPE_9_16 = 2
};
enum
{
THRESHOLD = 10000, NONMAX_SUPPRESSION=10001, FAST_N=10002
};
CV_WRAP static Ptr<FastFeatureDetector> create( int threshold=10,
bool nonmaxSuppression=true,
FastFeatureDetector::DetectorType type=FastFeatureDetector::TYPE_9_16 );
CV_WRAP virtual void setThreshold(int threshold) = 0;
CV_WRAP virtual int getThreshold() const = 0;
CV_WRAP virtual void setNonmaxSuppression(bool f) = 0;
CV_WRAP virtual bool getNonmaxSuppression() const = 0;
CV_WRAP virtual void setType(FastFeatureDetector::DetectorType type) = 0;
CV_WRAP virtual FastFeatureDetector::DetectorType getType() const = 0;
CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
};
/** @overload */
CV_EXPORTS void FAST( InputArray image, CV_OUT std::vector<KeyPoint>& keypoints,
int threshold, bool nonmaxSuppression=true );
@@ -441,27 +477,31 @@ cv2.FAST_FEATURE_DETECTOR_TYPE_7_12 and cv2.FAST_FEATURE_DETECTOR_TYPE_9_16. For
detection, use cv2.FAST.detect() method.
*/
CV_EXPORTS void FAST( InputArray image, CV_OUT std::vector<KeyPoint>& keypoints,
int threshold, bool nonmaxSuppression, int type );
int threshold, bool nonmaxSuppression, FastFeatureDetector::DetectorType type );
//! @} features2d_main
//! @addtogroup features2d_main
//! @{
/** @brief Wrapping class for feature detection using the FAST method. :
/** @brief Wrapping class for feature detection using the AGAST method. :
*/
class CV_EXPORTS_W FastFeatureDetector : public Feature2D
class CV_EXPORTS_W AgastFeatureDetector : public Feature2D
{
public:
enum
enum DetectorType
{
TYPE_5_8 = 0, TYPE_7_12 = 1, TYPE_9_16 = 2,
THRESHOLD = 10000, NONMAX_SUPPRESSION=10001, FAST_N=10002,
AGAST_5_8 = 0, AGAST_7_12d = 1, AGAST_7_12s = 2, OAST_9_16 = 3,
};
CV_WRAP static Ptr<FastFeatureDetector> create( int threshold=10,
bool nonmaxSuppression=true,
int type=FastFeatureDetector::TYPE_9_16 );
enum
{
THRESHOLD = 10000, NONMAX_SUPPRESSION = 10001,
};
CV_WRAP static Ptr<AgastFeatureDetector> create( int threshold=10,
bool nonmaxSuppression=true,
AgastFeatureDetector::DetectorType type = AgastFeatureDetector::OAST_9_16);
CV_WRAP virtual void setThreshold(int threshold) = 0;
CV_WRAP virtual int getThreshold() const = 0;
@@ -469,8 +509,8 @@ public:
CV_WRAP virtual void setNonmaxSuppression(bool f) = 0;
CV_WRAP virtual bool getNonmaxSuppression() const = 0;
CV_WRAP virtual void setType(int type) = 0;
CV_WRAP virtual int getType() const = 0;
CV_WRAP virtual void setType(AgastFeatureDetector::DetectorType type) = 0;
CV_WRAP virtual AgastFeatureDetector::DetectorType getType() const = 0;
CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
};
@@ -497,37 +537,7 @@ Detects corners using the AGAST algorithm by @cite mair2010_agast .
*/
CV_EXPORTS void AGAST( InputArray image, CV_OUT std::vector<KeyPoint>& keypoints,
int threshold, bool nonmaxSuppression, int type );
//! @} features2d_main
//! @addtogroup features2d_main
//! @{
/** @brief Wrapping class for feature detection using the AGAST method. :
*/
class CV_EXPORTS_W AgastFeatureDetector : public Feature2D
{
public:
enum
{
AGAST_5_8 = 0, AGAST_7_12d = 1, AGAST_7_12s = 2, OAST_9_16 = 3,
THRESHOLD = 10000, NONMAX_SUPPRESSION = 10001,
};
CV_WRAP static Ptr<AgastFeatureDetector> create( int threshold=10,
bool nonmaxSuppression=true,
int type=AgastFeatureDetector::OAST_9_16 );
CV_WRAP virtual void setThreshold(int threshold) = 0;
CV_WRAP virtual int getThreshold() const = 0;
CV_WRAP virtual void setNonmaxSuppression(bool f) = 0;
CV_WRAP virtual bool getNonmaxSuppression() const = 0;
CV_WRAP virtual void setType(int type) = 0;
CV_WRAP virtual int getType() const = 0;
CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
};
int threshold, bool nonmaxSuppression, AgastFeatureDetector::DetectorType type );
/** @brief Wrapping class for feature detection using the goodFeaturesToTrack function. :
*/
@@ -639,7 +649,7 @@ F. Alcantarilla, Adrien Bartoli and Andrew J. Davison. In European Conference on
class CV_EXPORTS_W KAZE : public Feature2D
{
public:
enum
enum DiffusivityType
{
DIFF_PM_G1 = 0,
DIFF_PM_G2 = 1,
@@ -660,7 +670,7 @@ public:
CV_WRAP static Ptr<KAZE> create(bool extended=false, bool upright=false,
float threshold = 0.001f,
int nOctaves = 4, int nOctaveLayers = 4,
int diffusivity = KAZE::DIFF_PM_G2);
KAZE::DiffusivityType diffusivity = KAZE::DIFF_PM_G2);
CV_WRAP virtual void setExtended(bool extended) = 0;
CV_WRAP virtual bool getExtended() const = 0;
@@ -677,8 +687,8 @@ public:
CV_WRAP virtual void setNOctaveLayers(int octaveLayers) = 0;
CV_WRAP virtual int getNOctaveLayers() const = 0;
CV_WRAP virtual void setDiffusivity(int diff) = 0;
CV_WRAP virtual int getDiffusivity() const = 0;
CV_WRAP virtual void setDiffusivity(KAZE::DiffusivityType diff) = 0;
CV_WRAP virtual KAZE::DiffusivityType getDiffusivity() const = 0;
CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
};
@@ -702,7 +712,7 @@ class CV_EXPORTS_W AKAZE : public Feature2D
{
public:
// AKAZE descriptor type
enum
enum DescriptorType
{
DESCRIPTOR_KAZE_UPRIGHT = 2, ///< Upright descriptors, not invariant to rotation
DESCRIPTOR_KAZE = 3,
@@ -722,13 +732,13 @@ public:
@param diffusivity Diffusivity type. DIFF_PM_G1, DIFF_PM_G2, DIFF_WEICKERT or
DIFF_CHARBONNIER
*/
CV_WRAP static Ptr<AKAZE> create(int descriptor_type=AKAZE::DESCRIPTOR_MLDB,
CV_WRAP static Ptr<AKAZE> create(AKAZE::DescriptorType descriptor_type = AKAZE::DESCRIPTOR_MLDB,
int descriptor_size = 0, int descriptor_channels = 3,
float threshold = 0.001f, int nOctaves = 4,
int nOctaveLayers = 4, int diffusivity = KAZE::DIFF_PM_G2);
int nOctaveLayers = 4, KAZE::DiffusivityType diffusivity = KAZE::DIFF_PM_G2);
CV_WRAP virtual void setDescriptorType(int dtype) = 0;
CV_WRAP virtual int getDescriptorType() const = 0;
CV_WRAP virtual void setDescriptorType(AKAZE::DescriptorType dtype) = 0;
CV_WRAP virtual AKAZE::DescriptorType getDescriptorType() const = 0;
CV_WRAP virtual void setDescriptorSize(int dsize) = 0;
CV_WRAP virtual int getDescriptorSize() const = 0;
@@ -745,8 +755,8 @@ public:
CV_WRAP virtual void setNOctaveLayers(int octaveLayers) = 0;
CV_WRAP virtual int getNOctaveLayers() const = 0;
CV_WRAP virtual void setDiffusivity(int diff) = 0;
CV_WRAP virtual int getDiffusivity() const = 0;
CV_WRAP virtual void setDiffusivity(KAZE::DiffusivityType diff) = 0;
CV_WRAP virtual KAZE::DiffusivityType getDiffusivity() const = 0;
CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
};
@@ -773,7 +783,7 @@ template<> struct Accumulator<short> { typedef float Type; };
template<class T>
struct CV_EXPORTS SL2
{
enum { normType = NORM_L2SQR };
static const NormTypes normType = NORM_L2SQR;
typedef T ValueType;
typedef typename Accumulator<T>::Type ResultType;
@@ -789,7 +799,7 @@ struct CV_EXPORTS SL2
template<class T>
struct L2
{
enum { normType = NORM_L2 };
static const NormTypes normType = NORM_L2;
typedef T ValueType;
typedef typename Accumulator<T>::Type ResultType;
@@ -805,7 +815,7 @@ struct L2
template<class T>
struct L1
{
enum { normType = NORM_L1 };
static const NormTypes normType = NORM_L1;
typedef T ValueType;
typedef typename Accumulator<T>::Type ResultType;
@@ -830,7 +840,7 @@ an image set.
class CV_EXPORTS_W DescriptorMatcher : public Algorithm
{
public:
enum
enum MatcherType
{
FLANNBASED = 1,
BRUTEFORCE = 2,
@@ -839,6 +849,7 @@ public:
BRUTEFORCE_HAMMINGLUT = 5,
BRUTEFORCE_SL2 = 6
};
virtual ~DescriptorMatcher();
/** @brief Adds descriptors to train a CPU(trainDescCollectionis) or GPU(utrainDescCollectionis) descriptor
@@ -1016,7 +1027,7 @@ public:
*/
CV_WRAP static Ptr<DescriptorMatcher> create( const String& descriptorMatcherType );
CV_WRAP static Ptr<DescriptorMatcher> create( int matcherType );
CV_WRAP static Ptr<DescriptorMatcher> create( const DescriptorMatcher::MatcherType& matcherType );
// see corresponding cv::Algorithm method
@@ -1171,20 +1182,20 @@ protected:
//! @addtogroup features2d_draw
//! @{
struct CV_EXPORTS DrawMatchesFlags
enum struct DrawMatchesFlags
{
enum{ DEFAULT = 0, //!< Output image matrix will be created (Mat::create),
//!< i.e. existing memory of output image may be reused.
//!< Two source image, matches and single keypoints will be drawn.
//!< For each keypoint only the center point will be drawn (without
//!< the circle around keypoint with keypoint size and orientation).
DRAW_OVER_OUTIMG = 1, //!< Output image matrix will not be created (Mat::create).
//!< Matches will be drawn on existing content of output image.
NOT_DRAW_SINGLE_POINTS = 2, //!< Single keypoints will not be drawn.
DRAW_RICH_KEYPOINTS = 4 //!< For each keypoint the circle around keypoint with keypoint size and
//!< orientation will be drawn.
};
DEFAULT = 0, //!< Output image matrix will be created (Mat::create),
//!< i.e. existing memory of output image may be reused.
//!< Two source image, matches and single keypoints will be drawn.
//!< For each keypoint only the center point will be drawn (without
//!< the circle around keypoint with keypoint size and orientation).
DRAW_OVER_OUTIMG = 1, //!< Output image matrix will not be created (Mat::create).
//!< Matches will be drawn on existing content of output image.
NOT_DRAW_SINGLE_POINTS = 2, //!< Single keypoints will not be drawn.
DRAW_RICH_KEYPOINTS = 4 //!< For each keypoint the circle around keypoint with keypoint size and
//!< orientation will be drawn.
};
CV_ENUM_FLAGS(DrawMatchesFlags);
/** @brief Draws keypoints.
@@ -1202,7 +1213,7 @@ cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS, cv2.DRAW_MATCHES_FLAGS_DRAW_OVER_OUT
cv2.DRAW_MATCHES_FLAGS_NOT_DRAW_SINGLE_POINTS
*/
CV_EXPORTS_W void drawKeypoints( InputArray image, const std::vector<KeyPoint>& keypoints, InputOutputArray outImage,
const Scalar& color=Scalar::all(-1), int flags=DrawMatchesFlags::DEFAULT );
const Scalar& color=Scalar::all(-1), DrawMatchesFlags flags=DrawMatchesFlags::DEFAULT );
/** @brief Draws the found matches of keypoints from two images.
@@ -1230,14 +1241,14 @@ CV_EXPORTS_W void drawMatches( InputArray img1, const std::vector<KeyPoint>& key
InputArray img2, const std::vector<KeyPoint>& keypoints2,
const std::vector<DMatch>& matches1to2, InputOutputArray outImg,
const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1),
const std::vector<char>& matchesMask=std::vector<char>(), int flags=DrawMatchesFlags::DEFAULT );
const std::vector<char>& matchesMask=std::vector<char>(), DrawMatchesFlags flags=DrawMatchesFlags::DEFAULT );
/** @overload */
CV_EXPORTS_AS(drawMatchesKnn) void drawMatches( InputArray img1, const std::vector<KeyPoint>& keypoints1,
InputArray img2, const std::vector<KeyPoint>& keypoints2,
const std::vector<std::vector<DMatch> >& matches1to2, InputOutputArray outImg,
const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1),
const std::vector<std::vector<char> >& matchesMask=std::vector<std::vector<char> >(), int flags=DrawMatchesFlags::DEFAULT );
const std::vector<std::vector<char> >& matchesMask=std::vector<std::vector<char> >(), DrawMatchesFlags flags=DrawMatchesFlags::DEFAULT );
//! @} features2d_draw