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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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46
modules/core/include/opencv2/core.hpp
View File

@ -2997,7 +2997,8 @@ public:
class CV_EXPORTS Formatter
{
public:
enum { FMT_DEFAULT = 0,
enum FormatType {
FMT_DEFAULT = 0,
FMT_MATLAB = 1,
FMT_CSV = 2,
FMT_PYTHON = 3,
@ -3014,7 +3015,7 @@ public:
virtual void set64fPrecision(int p = 16) = 0;
virtual void setMultiline(bool ml = true) = 0;
static Ptr<Formatter> get(int fmt = FMT_DEFAULT);
static Ptr<Formatter> get(Formatter::FormatType fmt = FMT_DEFAULT);
};
@ -3037,7 +3038,7 @@ String& operator << (String& out, const Mat& mtx)
class CV_EXPORTS Algorithm;
template<typename _Tp> struct ParamType {};
template<typename _Tp, typename _EnumTp = void> struct ParamType {};
/** @brief This is a base class for all more or less complex algorithms in OpenCV
@ -3150,9 +3151,9 @@ protected:
void writeFormat(FileStorage& fs) const;
};
struct Param {
enum { INT=0, BOOLEAN=1, REAL=2, STRING=3, MAT=4, MAT_VECTOR=5, ALGORITHM=6, FLOAT=7,
UNSIGNED_INT=8, UINT64=9, UCHAR=11, SCALAR=12 };
enum struct Param {
INT=0, BOOLEAN=1, REAL=2, STRING=3, MAT=4, MAT_VECTOR=5, ALGORITHM=6, FLOAT=7,
UNSIGNED_INT=8, UINT64=9, UCHAR=11, SCALAR=12
};
@ -3162,7 +3163,7 @@ template<> struct ParamType<bool>
typedef bool const_param_type;
typedef bool member_type;
enum { type = Param::BOOLEAN };
static const Param type = Param::BOOLEAN;
};
template<> struct ParamType<int>
@ -3170,7 +3171,7 @@ template<> struct ParamType<int>
typedef int const_param_type;
typedef int member_type;
enum { type = Param::INT };
static const Param type = Param::INT;
};
template<> struct ParamType<double>
@ -3178,7 +3179,7 @@ template<> struct ParamType<double>
typedef double const_param_type;
typedef double member_type;
enum { type = Param::REAL };
static const Param type = Param::REAL;
};
template<> struct ParamType<String>
@ -3186,7 +3187,7 @@ template<> struct ParamType<String>
typedef const String& const_param_type;
typedef String member_type;
enum { type = Param::STRING };
static const Param type = Param::STRING;
};
template<> struct ParamType<Mat>
@ -3194,7 +3195,7 @@ template<> struct ParamType<Mat>
typedef const Mat& const_param_type;
typedef Mat member_type;
enum { type = Param::MAT };
static const Param type = Param::MAT;
};
template<> struct ParamType<std::vector<Mat> >
@ -3202,7 +3203,7 @@ template<> struct ParamType<std::vector<Mat> >
typedef const std::vector<Mat>& const_param_type;
typedef std::vector<Mat> member_type;
enum { type = Param::MAT_VECTOR };
static const Param type = Param::MAT_VECTOR;
};
template<> struct ParamType<Algorithm>
@ -3210,7 +3211,7 @@ template<> struct ParamType<Algorithm>
typedef const Ptr<Algorithm>& const_param_type;
typedef Ptr<Algorithm> member_type;
enum { type = Param::ALGORITHM };
static const Param type = Param::ALGORITHM;
};
template<> struct ParamType<float>
@ -3218,7 +3219,7 @@ template<> struct ParamType<float>
typedef float const_param_type;
typedef float member_type;
enum { type = Param::FLOAT };
static const Param type = Param::FLOAT;
};
template<> struct ParamType<unsigned>
@ -3226,7 +3227,7 @@ template<> struct ParamType<unsigned>
typedef unsigned const_param_type;
typedef unsigned member_type;
enum { type = Param::UNSIGNED_INT };
static const Param type = Param::UNSIGNED_INT;
};
template<> struct ParamType<uint64>
@ -3234,7 +3235,7 @@ template<> struct ParamType<uint64>
typedef uint64 const_param_type;
typedef uint64 member_type;
enum { type = Param::UINT64 };
static const Param type = Param::UINT64;
};
template<> struct ParamType<uchar>
@ -3242,7 +3243,7 @@ template<> struct ParamType<uchar>
typedef uchar const_param_type;
typedef uchar member_type;
enum { type = Param::UCHAR };
static const Param type = Param::UCHAR;
};
template<> struct ParamType<Scalar>
@ -3250,7 +3251,16 @@ template<> struct ParamType<Scalar>
typedef const Scalar& const_param_type;
typedef Scalar member_type;
enum { type = Param::SCALAR };
static const Param type = Param::SCALAR;
};
template<typename _Tp>
struct ParamType<_Tp, typename std::enable_if< std::is_enum<_Tp>::value >::type>
{
typedef typename std::underlying_type<_Tp>::type const_param_type;
typedef typename std::underlying_type<_Tp>::type member_type;
static const Param type = Param::INT;
};
//! @} core_basic

22
modules/core/include/opencv2/core/base.hpp
View File

@ -440,17 +440,17 @@ configurations while CV_DbgAssert is only retained in the Debug configuration.
#endif
#define CV_Assert_1 CV_Assert
#define CV_Assert_2( expr1, expr2 ) CV_Assert_1(expr1); CV_Assert_1(expr2)
#define CV_Assert_3( expr1, expr2, expr3 ) CV_Assert_2(expr1, expr2); CV_Assert_1(expr3)
#define CV_Assert_4( expr1, expr2, expr3, expr4 ) CV_Assert_3(expr1, expr2, expr3); CV_Assert_1(expr4)
#define CV_Assert_5( expr1, expr2, expr3, expr4, expr5 ) CV_Assert_4(expr1, expr2, expr3, expr4); CV_Assert_1(expr5)
#define CV_Assert_6( expr1, expr2, expr3, expr4, expr5, expr6 ) CV_Assert_5(expr1, expr2, expr3, expr4, expr5); CV_Assert_1(expr6)
#define CV_Assert_7( expr1, expr2, expr3, expr4, expr5, expr6, expr7 ) CV_Assert_6(expr1, expr2, expr3, expr4, expr5, expr6 ); CV_Assert_1(expr7)
#define CV_Assert_8( expr1, expr2, expr3, expr4, expr5, expr6, expr7, expr8 ) CV_Assert_7(expr1, expr2, expr3, expr4, expr5, expr6, expr7 ); CV_Assert_1(expr8)
#define CV_Assert_9( expr1, expr2, expr3, expr4, expr5, expr6, expr7, expr8, expr9 ) CV_Assert_8(expr1, expr2, expr3, expr4, expr5, expr6, expr7, expr8 ); CV_Assert_1(expr9)
#define CV_Assert_10( expr1, expr2, expr3, expr4, expr5, expr6, expr7, expr8, expr9, expr10 ) CV_Assert_9(expr1, expr2, expr3, expr4, expr5, expr6, expr7, expr8, expr9 ); CV_Assert_1(expr10)
#define CV_Assert_2( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_1( __VA_ARGS__ ))
#define CV_Assert_3( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_2( __VA_ARGS__ ))
#define CV_Assert_4( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_3( __VA_ARGS__ ))
#define CV_Assert_5( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_4( __VA_ARGS__ ))
#define CV_Assert_6( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_5( __VA_ARGS__ ))
#define CV_Assert_7( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_6( __VA_ARGS__ ))
#define CV_Assert_8( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_7( __VA_ARGS__ ))
#define CV_Assert_9( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_8( __VA_ARGS__ ))
#define CV_Assert_10( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_9( __VA_ARGS__ ))
#define CV_Assert_N(...) do { __CV_CAT(CV_Assert_, __CV_VA_NUM_ARGS(__VA_ARGS__)) (__VA_ARGS__); } while(0)
#define CV_Assert_N(...) do { __CV_EXPAND(__CV_CAT(CV_Assert_, __CV_VA_NUM_ARGS(__VA_ARGS__)) (__VA_ARGS__)); } while(0)
//! @endcond
@ -467,7 +467,7 @@ configurations while CV_DbgAssert is only retained in the Debug configuration.
*/
struct CV_EXPORTS Hamming
{
enum { normType = NORM_HAMMING };
static const NormTypes normType = NORM_HAMMING;
typedef unsigned char ValueType;
typedef int ResultType;

138
modules/core/include/opencv2/core/cvdef.h
View File

@ -80,7 +80,7 @@ namespace cv { namespace debug_build_guard { } using namespace debug_build_guard
#endif
#define __CV_VA_NUM_ARGS_HELPER(_1, _2, _3, _4, _5, _6, _7, _8, _9, _10, N, ...) N
#define __CV_VA_NUM_ARGS(...) __CV_VA_NUM_ARGS_HELPER(__VA_ARGS__, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0)
#define __CV_VA_NUM_ARGS(...) __CV_EXPAND(__CV_VA_NUM_ARGS_HELPER(__VA_ARGS__, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0))
// undef problematic defines sometimes defined by system headers (windows.h in particular)
#undef small
@ -330,6 +330,142 @@ Cv64suf;
# define MAX(a,b) ((a) < (b) ? (b) : (a))
#endif
///////////////////////////////////////// Enum operators ///////////////////////////////////////
/**
Provides compatibility operators for both classical and C++11 enum classes,
as well as exposing the C++11 enum class members for backwards compatibility
@code
// Provides operators required for flag enums
CV_ENUM_FLAGS(AccessFlag);
// Exposes the listed members of the enum class AccessFlag to the current namespace
CV_ENUM_CLASS_EXPOSE(AccessFlag, ACCESS_READ [, ACCESS_WRITE [, ...] ]);
@endcode
*/
#define __CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST) \
static const EnumType MEMBER_CONST = EnumType::MEMBER_CONST; \
#define __CV_ENUM_CLASS_EXPOSE_2(EnumType, MEMBER_CONST, ...) \
__CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST); \
__CV_EXPAND(__CV_ENUM_CLASS_EXPOSE_1(EnumType, __VA_ARGS__)); \
#define __CV_ENUM_CLASS_EXPOSE_3(EnumType, MEMBER_CONST, ...) \
__CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST); \
__CV_EXPAND(__CV_ENUM_CLASS_EXPOSE_2(EnumType, __VA_ARGS__)); \
#define __CV_ENUM_CLASS_EXPOSE_4(EnumType, MEMBER_CONST, ...) \
__CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST); \
__CV_EXPAND(__CV_ENUM_CLASS_EXPOSE_3(EnumType, __VA_ARGS__)); \
#define __CV_ENUM_CLASS_EXPOSE_5(EnumType, MEMBER_CONST, ...) \
__CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST); \
__CV_EXPAND(__CV_ENUM_CLASS_EXPOSE_4(EnumType, __VA_ARGS__)); \
#define __CV_ENUM_CLASS_EXPOSE_6(EnumType, MEMBER_CONST, ...) \
__CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST); \
__CV_EXPAND(__CV_ENUM_CLASS_EXPOSE_5(EnumType, __VA_ARGS__)); \
#define __CV_ENUM_CLASS_EXPOSE_7(EnumType, MEMBER_CONST, ...) \
__CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST); \
__CV_EXPAND(__CV_ENUM_CLASS_EXPOSE_6(EnumType, __VA_ARGS__)); \
#define __CV_ENUM_CLASS_EXPOSE_8(EnumType, MEMBER_CONST, ...) \
__CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST); \
__CV_EXPAND(__CV_ENUM_CLASS_EXPOSE_7(EnumType, __VA_ARGS__)); \
#define __CV_ENUM_CLASS_EXPOSE_9(EnumType, MEMBER_CONST, ...) \
__CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST); \
__CV_EXPAND(__CV_ENUM_CLASS_EXPOSE_8(EnumType, __VA_ARGS__)); \
#define __CV_ENUM_FLAGS_LOGICAL_NOT(EnumType) \
static inline bool operator!(const EnumType& val) \
{ \
typedef std::underlying_type<EnumType>::type UnderlyingType; \
return !static_cast<UnderlyingType>(val); \
} \
#define __CV_ENUM_FLAGS_LOGICAL_NOT_EQ(Arg1Type, Arg2Type) \
static inline bool operator!=(const Arg1Type& a, const Arg2Type& b) \
{ \
return static_cast<int>(a) != static_cast<int>(b); \
} \
#define __CV_ENUM_FLAGS_LOGICAL_EQ(Arg1Type, Arg2Type) \
static inline bool operator==(const Arg1Type& a, const Arg2Type& b) \
{ \
return static_cast<int>(a) == static_cast<int>(b); \
} \
#define __CV_ENUM_FLAGS_BITWISE_NOT(EnumType) \
static inline EnumType operator~(const EnumType& val) \
{ \
typedef std::underlying_type<EnumType>::type UnderlyingType; \
return static_cast<EnumType>(~static_cast<UnderlyingType>(val)); \
} \
#define __CV_ENUM_FLAGS_BITWISE_OR(EnumType, Arg1Type, Arg2Type) \
static inline EnumType operator|(const Arg1Type& a, const Arg2Type& b) \
{ \
typedef std::underlying_type<EnumType>::type UnderlyingType; \
return static_cast<EnumType>(static_cast<UnderlyingType>(a) | static_cast<UnderlyingType>(b)); \
} \
#define __CV_ENUM_FLAGS_BITWISE_AND(EnumType, Arg1Type, Arg2Type) \
static inline EnumType operator&(const Arg1Type& a, const Arg2Type& b) \
{ \
typedef std::underlying_type<EnumType>::type UnderlyingType; \
return static_cast<EnumType>(static_cast<UnderlyingType>(a) & static_cast<UnderlyingType>(b)); \
} \
#define __CV_ENUM_FLAGS_BITWISE_XOR(EnumType, Arg1Type, Arg2Type) \
static inline EnumType operator^(const Arg1Type& a, const Arg2Type& b) \
{ \
typedef std::underlying_type<EnumType>::type UnderlyingType; \
return static_cast<EnumType>(static_cast<UnderlyingType>(a) ^ static_cast<UnderlyingType>(b)); \
} \
#define __CV_ENUM_FLAGS_BITWISE_OR_EQ(EnumType, Arg1Type) \
static inline EnumType& operator|=(EnumType& _this, const Arg1Type& val) \
{ \
_this = static_cast<EnumType>(static_cast<int>(_this) | static_cast<int>(val)); \
return _this; \
} \
#define __CV_ENUM_FLAGS_BITWISE_AND_EQ(EnumType, Arg1Type) \
static inline EnumType& operator&=(EnumType& _this, const Arg1Type& val) \
{ \
_this = static_cast<EnumType>(static_cast<int>(_this) & static_cast<int>(val)); \
return _this; \
} \
#define __CV_ENUM_FLAGS_BITWISE_XOR_EQ(EnumType, Arg1Type) \
static inline EnumType& operator^=(EnumType& _this, const Arg1Type& val) \
{ \
_this = static_cast<EnumType>(static_cast<int>(_this) ^ static_cast<int>(val)); \
return _this; \
} \
#define CV_ENUM_CLASS_EXPOSE(EnumType, ...) \
__CV_EXPAND(__CV_CAT(__CV_ENUM_CLASS_EXPOSE_, __CV_VA_NUM_ARGS(__VA_ARGS__))(EnumType, __VA_ARGS__)); \
#define CV_ENUM_FLAGS(EnumType) \
__CV_ENUM_FLAGS_LOGICAL_NOT (EnumType); \
__CV_ENUM_FLAGS_LOGICAL_EQ (EnumType, int); \
__CV_ENUM_FLAGS_LOGICAL_NOT_EQ (EnumType, int); \
\
__CV_ENUM_FLAGS_BITWISE_NOT (EnumType); \
__CV_ENUM_FLAGS_BITWISE_OR (EnumType, EnumType, EnumType); \
__CV_ENUM_FLAGS_BITWISE_AND (EnumType, EnumType, EnumType); \
__CV_ENUM_FLAGS_BITWISE_XOR (EnumType, EnumType, EnumType); \
\
__CV_ENUM_FLAGS_BITWISE_OR_EQ (EnumType, EnumType); \
__CV_ENUM_FLAGS_BITWISE_AND_EQ (EnumType, EnumType); \
__CV_ENUM_FLAGS_BITWISE_XOR_EQ (EnumType, EnumType); \
/****************************************************************************************\
* static analysys *
\****************************************************************************************/

36
modules/core/include/opencv2/core/mat.hpp
View File

@ -61,8 +61,10 @@ namespace cv
//! @addtogroup core_basic
//! @{
enum { ACCESS_READ=1<<24, ACCESS_WRITE=1<<25,
enum AccessFlag { ACCESS_READ=1<<24, ACCESS_WRITE=1<<25,
ACCESS_RW=3<<24, ACCESS_MASK=ACCESS_RW, ACCESS_FAST=1<<26 };
CV_ENUM_FLAGS(AccessFlag);
__CV_ENUM_FLAGS_BITWISE_AND(AccessFlag, int, AccessFlag);
CV__DEBUG_NS_BEGIN
@ -156,7 +158,7 @@ Custom type is wrapped as Mat-compatible `CV_8UC<N>` values (N = sizeof(T), N <=
class CV_EXPORTS _InputArray
{
public:
enum {
enum KindFlag {
KIND_SHIFT = 16,
FIXED_TYPE = 0x8000 << KIND_SHIFT,
FIXED_SIZE = 0x4000 << KIND_SHIFT,
@ -221,7 +223,7 @@ public:
void* getObj() const;
Size getSz() const;
int kind() const;
_InputArray::KindFlag kind() const;
int dims(int i=-1) const;
int cols(int i=-1) const;
int rows(int i=-1) const;
@ -257,7 +259,8 @@ protected:
void init(int _flags, const void* _obj);
void init(int _flags, const void* _obj, Size _sz);
};
CV_ENUM_FLAGS(_InputArray::KindFlag);
__CV_ENUM_FLAGS_BITWISE_AND(_InputArray::KindFlag, int, _InputArray::KindFlag);
/** @brief This type is very similar to InputArray except that it is used for input/output and output function
parameters.
@ -287,7 +290,7 @@ generators:
class CV_EXPORTS _OutputArray : public _InputArray
{
public:
enum
enum DepthMask
{
DEPTH_MASK_8U = 1 << CV_8U,
DEPTH_MASK_8S = 1 << CV_8S,
@ -356,9 +359,9 @@ public:
std::vector<cuda::GpuMat>& getGpuMatVecRef() const;
ogl::Buffer& getOGlBufferRef() const;
cuda::HostMem& getHostMemRef() const;
void create(Size sz, int type, int i=-1, bool allowTransposed=false, int fixedDepthMask=0) const;
void create(int rows, int cols, int type, int i=-1, bool allowTransposed=false, int fixedDepthMask=0) const;
void create(int dims, const int* size, int type, int i=-1, bool allowTransposed=false, int fixedDepthMask=0) const;
void create(Size sz, int type, int i=-1, bool allowTransposed=false, _OutputArray::DepthMask fixedDepthMask=static_cast<_OutputArray::DepthMask>(0)) const;
void create(int rows, int cols, int type, int i=-1, bool allowTransposed=false, _OutputArray::DepthMask fixedDepthMask=static_cast<_OutputArray::DepthMask>(0)) const;
void create(int dims, const int* size, int type, int i=-1, bool allowTransposed=false, _OutputArray::DepthMask fixedDepthMask=static_cast<_OutputArray::DepthMask>(0)) const;
void createSameSize(const _InputArray& arr, int mtype) const;
void release() const;
void clear() const;
@ -467,10 +470,10 @@ public:
// uchar*& datastart, uchar*& data, size_t* step) = 0;
//virtual void deallocate(int* refcount, uchar* datastart, uchar* data) = 0;
virtual UMatData* allocate(int dims, const int* sizes, int type,
void* data, size_t* step, int flags, UMatUsageFlags usageFlags) const = 0;
virtual bool allocate(UMatData* data, int accessflags, UMatUsageFlags usageFlags) const = 0;
void* data, size_t* step, AccessFlag flags, UMatUsageFlags usageFlags) const = 0;
virtual bool allocate(UMatData* data, AccessFlag accessflags, UMatUsageFlags usageFlags) const = 0;
virtual void deallocate(UMatData* data) const = 0;
virtual void map(UMatData* data, int accessflags) const;
virtual void map(UMatData* data, AccessFlag accessflags) const;
virtual void unmap(UMatData* data) const;
virtual void download(UMatData* data, void* dst, int dims, const size_t sz[],
const size_t srcofs[], const size_t srcstep[],
@ -523,7 +526,7 @@ protected:
// it should be explicitly initialized using init().
struct CV_EXPORTS UMatData
{
enum { COPY_ON_MAP=1, HOST_COPY_OBSOLETE=2,
enum MemoryFlag { COPY_ON_MAP=1, HOST_COPY_OBSOLETE=2,
DEVICE_COPY_OBSOLETE=4, TEMP_UMAT=8, TEMP_COPIED_UMAT=24,
USER_ALLOCATED=32, DEVICE_MEM_MAPPED=64,
ASYNC_CLEANUP=128
@ -553,13 +556,14 @@ struct CV_EXPORTS UMatData
uchar* origdata;
size_t size;
int flags;
UMatData::MemoryFlag flags;
void* handle;
void* userdata;
int allocatorFlags_;
int mapcount;
UMatData* originalUMatData;
};
CV_ENUM_FLAGS(UMatData::MemoryFlag);
struct CV_EXPORTS MatSize
@ -1061,7 +1065,7 @@ public:
Mat& operator = (const MatExpr& expr);
//! retrieve UMat from Mat
UMat getUMat(int accessFlags, UMatUsageFlags usageFlags = USAGE_DEFAULT) const;
UMat getUMat(AccessFlag accessFlags, UMatUsageFlags usageFlags = USAGE_DEFAULT) const;
/** @brief Creates a matrix header for the specified matrix row.
@ -2420,7 +2424,7 @@ public:
//! assignment operators
UMat& operator = (const UMat& m);
Mat getMat(int flags) const;
Mat getMat(AccessFlag flags) const;
//! returns a new matrix header for the specified row
UMat row(int y) const;
@ -2546,7 +2550,7 @@ public:
The UMat instance should be kept alive during the use of the handle to prevent the buffer to be
returned to the OpenCV buffer pool.
*/
void* handle(int accessFlags) const;
void* handle(AccessFlag accessFlags) const;
void ndoffset(size_t* ofs) const;
enum { MAGIC_VAL = 0x42FF0000, AUTO_STEP = 0, CONTINUOUS_FLAG = CV_MAT_CONT_FLAG, SUBMATRIX_FLAG = CV_SUBMAT_FLAG };

44
modules/core/include/opencv2/core/mat.inl.hpp
View File

@ -83,7 +83,7 @@ inline void* _InputArray::getObj() const { return obj; }
inline int _InputArray::getFlags() const { return flags; }
inline Size _InputArray::getSz() const { return sz; }
inline _InputArray::_InputArray() { init(NONE, 0); }
inline _InputArray::_InputArray() { init(0 + NONE, 0); }
inline _InputArray::_InputArray(int _flags, void* _obj) { init(_flags, _obj); }
inline _InputArray::_InputArray(const Mat& m) { init(MAT+ACCESS_READ, &m); }
inline _InputArray::_InputArray(const std::vector<Mat>& vec) { init(STD_VECTOR_MAT+ACCESS_READ, &vec); }
@ -185,12 +185,12 @@ inline bool _InputArray::isGpuMatVector() const { return kind() == _InputArray::
////////////////////////////////////////////////////////////////////////////////////////
inline _OutputArray::_OutputArray() { init(ACCESS_WRITE, 0); }
inline _OutputArray::_OutputArray(int _flags, void* _obj) { init(_flags|ACCESS_WRITE, _obj); }
inline _OutputArray::_OutputArray() { init(NONE + ACCESS_WRITE, 0); }
inline _OutputArray::_OutputArray(int _flags, void* _obj) { init(_flags + ACCESS_WRITE, _obj); }
inline _OutputArray::_OutputArray(Mat& m) { init(MAT+ACCESS_WRITE, &m); }
inline _OutputArray::_OutputArray(std::vector<Mat>& vec) { init(STD_VECTOR_MAT+ACCESS_WRITE, &vec); }
inline _OutputArray::_OutputArray(UMat& m) { init(UMAT+ACCESS_WRITE, &m); }
inline _OutputArray::_OutputArray(std::vector<UMat>& vec) { init(STD_VECTOR_UMAT+ACCESS_WRITE, &vec); }
inline _OutputArray::_OutputArray(std::vector<Mat>& vec) { init(STD_VECTOR_MAT + ACCESS_WRITE, &vec); }
inline _OutputArray::_OutputArray(UMat& m) { init(UMAT + ACCESS_WRITE, &m); }
inline _OutputArray::_OutputArray(std::vector<UMat>& vec) { init(STD_VECTOR_UMAT + ACCESS_WRITE, &vec); }
template<typename _Tp> inline
_OutputArray::_OutputArray(std::vector<_Tp>& vec)
@ -311,8 +311,8 @@ _OutputArray _OutputArray::rawOut(std::array<_Tp, _Nm>& arr)
///////////////////////////////////////////////////////////////////////////////////////////
inline _InputOutputArray::_InputOutputArray() { init(ACCESS_RW, 0); }
inline _InputOutputArray::_InputOutputArray(int _flags, void* _obj) { init(_flags|ACCESS_RW, _obj); }
inline _InputOutputArray::_InputOutputArray() { init(0+ACCESS_RW, 0); }
inline _InputOutputArray::_InputOutputArray(int _flags, void* _obj) { init(_flags+ACCESS_RW, _obj); }
inline _InputOutputArray::_InputOutputArray(Mat& m) { init(MAT+ACCESS_RW, &m); }
inline _InputOutputArray::_InputOutputArray(std::vector<Mat>& vec) { init(STD_VECTOR_MAT+ACCESS_RW, &vec); }
inline _InputOutputArray::_InputOutputArray(UMat& m) { init(UMAT+ACCESS_RW, &m); }
@ -600,7 +600,7 @@ Mat::Mat(Size _sz, int _type, void* _data, size_t _step)
template<typename _Tp> inline
Mat::Mat(const std::vector<_Tp>& vec, bool copyData)
: flags(MAGIC_VAL | traits::Type<_Tp>::value | CV_MAT_CONT_FLAG), dims(2), rows((int)vec.size()),
: flags(MAGIC_VAL + traits::Type<_Tp>::value + CV_MAT_CONT_FLAG), dims(2), rows((int)vec.size()),
cols(1), data(0), datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0)
{
if(vec.empty())
@ -637,7 +637,7 @@ Mat::Mat(const std::initializer_list<int> sizes, const std::initializer_list<_Tp
template<typename _Tp, std::size_t _Nm> inline
Mat::Mat(const std::array<_Tp, _Nm>& arr, bool copyData)
: flags(MAGIC_VAL | traits::Type<_Tp>::value | CV_MAT_CONT_FLAG), dims(2), rows((int)arr.size()),
: flags(MAGIC_VAL + traits::Type<_Tp>::value + CV_MAT_CONT_FLAG), dims(2), rows((int)arr.size()),
cols(1), data(0), datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0)
{
if(arr.empty())
@ -654,7 +654,7 @@ Mat::Mat(const std::array<_Tp, _Nm>& arr, bool copyData)
template<typename _Tp, int n> inline
Mat::Mat(const Vec<_Tp, n>& vec, bool copyData)
: flags(MAGIC_VAL | traits::Type<_Tp>::value | CV_MAT_CONT_FLAG), dims(2), rows(n), cols(1), data(0),
: flags(MAGIC_VAL + traits::Type<_Tp>::value + CV_MAT_CONT_FLAG), dims(2), rows(n), cols(1), data(0),
datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0)
{
if( !copyData )
@ -670,7 +670,7 @@ Mat::Mat(const Vec<_Tp, n>& vec, bool copyData)
template<typename _Tp, int m, int n> inline
Mat::Mat(const Matx<_Tp,m,n>& M, bool copyData)
: flags(MAGIC_VAL | traits::Type<_Tp>::value | CV_MAT_CONT_FLAG), dims(2), rows(m), cols(n), data(0),
: flags(MAGIC_VAL + traits::Type<_Tp>::value + CV_MAT_CONT_FLAG), dims(2), rows(m), cols(n), data(0),
datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0)
{
if( !copyData )
@ -686,7 +686,7 @@ Mat::Mat(const Matx<_Tp,m,n>& M, bool copyData)
template<typename _Tp> inline
Mat::Mat(const Point_<_Tp>& pt, bool copyData)
: flags(MAGIC_VAL | traits::Type<_Tp>::value | CV_MAT_CONT_FLAG), dims(2), rows(2), cols(1), data(0),
: flags(MAGIC_VAL + traits::Type<_Tp>::value + CV_MAT_CONT_FLAG), dims(2), rows(2), cols(1), data(0),
datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0)
{
if( !copyData )
@ -705,7 +705,7 @@ Mat::Mat(const Point_<_Tp>& pt, bool copyData)
template<typename _Tp> inline
Mat::Mat(const Point3_<_Tp>& pt, bool copyData)
: flags(MAGIC_VAL | traits::Type<_Tp>::value | CV_MAT_CONT_FLAG), dims(2), rows(3), cols(1), data(0),
: flags(MAGIC_VAL + traits::Type<_Tp>::value + CV_MAT_CONT_FLAG), dims(2), rows(3), cols(1), data(0),
datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0)
{
if( !copyData )
@ -725,7 +725,7 @@ Mat::Mat(const Point3_<_Tp>& pt, bool copyData)
template<typename _Tp> inline
Mat::Mat(const MatCommaInitializer_<_Tp>& commaInitializer)
: flags(MAGIC_VAL | traits::Type<_Tp>::value | CV_MAT_CONT_FLAG), dims(0), rows(0), cols(0), data(0),
: flags(MAGIC_VAL + traits::Type<_Tp>::value + CV_MAT_CONT_FLAG), dims(0), rows(0), cols(0), data(0),
datastart(0), dataend(0), allocator(0), u(0), size(&rows)
{
*this = commaInitializer.operator Mat_<_Tp>();
@ -1554,7 +1554,7 @@ template<typename _Tp> inline
Mat_<_Tp>::Mat_()
: Mat()
{
flags = (flags & ~CV_MAT_TYPE_MASK) | traits::Type<_Tp>::value;
flags = (flags & ~CV_MAT_TYPE_MASK) + traits::Type<_Tp>::value;
}
template<typename _Tp> inline
@ -1611,7 +1611,7 @@ template<typename _Tp> inline
Mat_<_Tp>::Mat_(const Mat& m)
: Mat()
{
flags = (flags & ~CV_MAT_TYPE_MASK) | traits::Type<_Tp>::value;
flags = (flags & ~CV_MAT_TYPE_MASK) + traits::Type<_Tp>::value;
*this = m;
}
@ -1751,7 +1751,7 @@ void Mat_<_Tp>::release()
{
Mat::release();
#ifdef _DEBUG
flags = (flags & ~CV_MAT_TYPE_MASK) | traits::Type<_Tp>::value;
flags = (flags & ~CV_MAT_TYPE_MASK) + traits::Type<_Tp>::value;
#endif
}
@ -2069,7 +2069,7 @@ template<typename _Tp> inline
Mat_<_Tp>::Mat_(Mat&& m)
: Mat()
{
flags = (flags & ~CV_MAT_TYPE_MASK) | traits::Type<_Tp>::value;
flags = (flags & ~CV_MAT_TYPE_MASK) + traits::Type<_Tp>::value;
*this = m;
}
@ -2095,7 +2095,7 @@ template<typename _Tp> inline
Mat_<_Tp>::Mat_(MatExpr&& e)
: Mat()
{
flags = (flags & ~CV_MAT_TYPE_MASK) | traits::Type<_Tp>::value;
flags = (flags & ~CV_MAT_TYPE_MASK) + traits::Type<_Tp>::value;
*this = Mat(e);
}
@ -2431,7 +2431,7 @@ SparseMatConstIterator_<_Tp> SparseMat::end() const
template<typename _Tp> inline
SparseMat_<_Tp>::SparseMat_()
{
flags = MAGIC_VAL | traits::Type<_Tp>::value;
flags = MAGIC_VAL + traits::Type<_Tp>::value;
}
template<typename _Tp> inline
@ -3654,7 +3654,7 @@ UMat::UMat(const UMat& m)
template<typename _Tp> inline
UMat::UMat(const std::vector<_Tp>& vec, bool copyData)
: flags(MAGIC_VAL | traits::Type<_Tp>::value | CV_MAT_CONT_FLAG), dims(2), rows((int)vec.size()),
: flags(MAGIC_VAL + traits::Type<_Tp>::value + CV_MAT_CONT_FLAG), dims(2), rows((int)vec.size()),
cols(1), allocator(0), usageFlags(USAGE_DEFAULT), u(0), offset(0), size(&rows)
{
if(vec.empty())

2
modules/core/include/opencv2/core/opengl.hpp
View File

@ -548,7 +548,7 @@ calling unmapGLBuffer() function.
@param accessFlags - data access flags (ACCESS_READ|ACCESS_WRITE).
@return Returns UMat object
*/
CV_EXPORTS UMat mapGLBuffer(const Buffer& buffer, int accessFlags = ACCESS_READ|ACCESS_WRITE);
CV_EXPORTS UMat mapGLBuffer(const Buffer& buffer, AccessFlag accessFlags = ACCESS_READ | ACCESS_WRITE);
/** @brief Unmaps Buffer object (releases UMat, previously mapped from Buffer).

2
modules/core/include/opencv2/core/operations.hpp
View File

@ -392,7 +392,7 @@ CV_EXPORTS String format( const char* fmt, ... );
///////////////////////////////// Formatted output of cv::Mat /////////////////////////////////
static inline
Ptr<Formatted> format(InputArray mtx, int fmt)
Ptr<Formatted> format(InputArray mtx, Formatter::FormatType fmt)
{
return Formatter::get(fmt)->format(mtx.getMat());
}

14
modules/core/include/opencv2/core/persistence.hpp
View File

@ -1049,6 +1049,12 @@ void write(FileStorage& fs, const String& name, const DMatch& m)
write(fs, m.distance);
}
template<typename _Tp, typename std::enable_if< std::is_enum<_Tp>::value >::type* = nullptr>
static inline void write( FileStorage& fs, const String& name, const _Tp& val )
{
write(fs, name, static_cast<int>(val));
}
template<typename _Tp> static inline
void write( FileStorage& fs, const String& name, const std::vector<_Tp>& vec )
{
@ -1137,6 +1143,14 @@ void read( FileNodeIterator& it, std::vector<_Tp>& vec, size_t maxCount = (size_
r(vec, maxCount);
}
template<typename _Tp, typename std::enable_if< std::is_enum<_Tp>::value >::type* = nullptr>
static inline void read(const FileNode& node, _Tp& value, const _Tp& default_value = static_cast<_Tp>(0))
{
int temp;
read(node, temp, static_cast<int>(default_value));
value = static_cast<_Tp>(temp);
}
template<typename _Tp> static inline
void read( const FileNode& node, std::vector<_Tp>& vec, const std::vector<_Tp>& default_value = std::vector<_Tp>() )
{

4
modules/core/include/opencv2/core/utility.hpp
View File

@ -943,8 +943,8 @@ public:
void printErrors() const;
protected:
void getByName(const String& name, bool space_delete, int type, void* dst) const;
void getByIndex(int index, bool space_delete, int type, void* dst) const;
void getByName(const String& name, bool space_delete, Param type, void* dst) const;
void getByIndex(int index, bool space_delete, Param type, void* dst) const;
struct Impl;
Impl* impl;

2
modules/core/misc/python/pyopencv_umat.hpp
View File

@ -7,6 +7,8 @@ typedef std::vector<Range> vector_Range;
CV_PY_TO_CLASS(UMat);
CV_PY_FROM_CLASS(UMat);
CV_PY_TO_ENUM(UMatUsageFlags);
CV_PY_FROM_ENUM(AccessFlag);
CV_PY_TO_ENUM(AccessFlag);
static bool cv_mappable_to(const Ptr<Mat>& src, Ptr<UMat>& dst)
{

2
modules/core/misc/python/shadow_umat.hpp
View File

@ -50,7 +50,7 @@ public:
The UMat instance should be kept alive during the use of the handle to prevent the buffer to be
returned to the OpenCV buffer pool.
*/
CV_WRAP void* handle(int accessFlags) const;
CV_WRAP void* handle(AccessFlag accessFlags) const;
// offset of the submatrix (or 0)
CV_PROP_RW size_t offset;

10
modules/core/src/arithm.cpp
View File

@ -167,7 +167,7 @@ static void binary_op( InputArray _src1, InputArray _src2, OutputArray _dst,
bool bitwise, int oclop )
{
const _InputArray *psrc1 = &_src1, *psrc2 = &_src2;
int kind1 = psrc1->kind(), kind2 = psrc2->kind();
_InputArray::KindFlag kind1 = psrc1->kind(), kind2 = psrc2->kind();
int type1 = psrc1->type(), depth1 = CV_MAT_DEPTH(type1), cn = CV_MAT_CN(type1);
int type2 = psrc2->type(), depth2 = CV_MAT_DEPTH(type2), cn2 = CV_MAT_CN(type2);
int dims1 = psrc1->dims(), dims2 = psrc2->dims();
@ -600,7 +600,7 @@ static void arithm_op(InputArray _src1, InputArray _src2, OutputArray _dst,
void* usrdata=0, int oclop=-1 )
{
const _InputArray *psrc1 = &_src1, *psrc2 = &_src2;
int kind1 = psrc1->kind(), kind2 = psrc2->kind();
_InputArray::KindFlag kind1 = psrc1->kind(), kind2 = psrc2->kind();
bool haveMask = !_mask.empty();
bool reallocate = false;
int type1 = psrc1->type(), depth1 = CV_MAT_DEPTH(type1), cn = CV_MAT_CN(type1);
@ -1214,7 +1214,7 @@ void cv::compare(InputArray _src1, InputArray _src2, OutputArray _dst, int op)
CV_OCL_RUN(_src1.dims() <= 2 && _src2.dims() <= 2 && OCL_PERFORMANCE_CHECK(_dst.isUMat()),
ocl_compare(_src1, _src2, _dst, op, haveScalar))
int kind1 = _src1.kind(), kind2 = _src2.kind();
_InputArray::KindFlag kind1 = _src1.kind(), kind2 = _src2.kind();
Mat src1 = _src1.getMat(), src2 = _src2.getMat();
if( kind1 == kind2 && src1.dims <= 2 && src2.dims <= 2 && src1.size() == src2.size() && src1.type() == src2.type() )
@ -1587,7 +1587,7 @@ static bool ocl_inRange( InputArray _src, InputArray _lowerb,
InputArray _upperb, OutputArray _dst )
{
const ocl::Device & d = ocl::Device::getDefault();
int skind = _src.kind(), lkind = _lowerb.kind(), ukind = _upperb.kind();
_InputArray::KindFlag skind = _src.kind(), lkind = _lowerb.kind(), ukind = _upperb.kind();
Size ssize = _src.size(), lsize = _lowerb.size(), usize = _upperb.size();
int stype = _src.type(), ltype = _lowerb.type(), utype = _upperb.type();
int sdepth = CV_MAT_DEPTH(stype), ldepth = CV_MAT_DEPTH(ltype), udepth = CV_MAT_DEPTH(utype);
@ -1712,7 +1712,7 @@ void cv::inRange(InputArray _src, InputArray _lowerb,
_upperb.dims() <= 2 && OCL_PERFORMANCE_CHECK(_dst.isUMat()),
ocl_inRange(_src, _lowerb, _upperb, _dst))
int skind = _src.kind(), lkind = _lowerb.kind(), ukind = _upperb.kind();
_InputArray::KindFlag skind = _src.kind(), lkind = _lowerb.kind(), ukind = _upperb.kind();
Mat src = _src.getMat(), lb = _lowerb.getMat(), ub = _upperb.getMat();
bool lbScalar = false, ubScalar = false;

8
modules/core/src/command_line_parser.cpp
View File

@ -53,7 +53,7 @@ struct CommandLineParser::Impl
};
static const char* get_type_name(int type)
static const char* get_type_name(Param type)
{
if( type == Param::INT )
return "int";
@ -81,7 +81,7 @@ static bool parse_bool(std::string str)
return b;
}
static void from_str(const String& str, int type, void* dst)
static void from_str(const String& str, Param type, void* dst)
{
std::stringstream ss(str.c_str());
if( type == Param::INT )
@ -117,7 +117,7 @@ static void from_str(const String& str, int type, void* dst)
}
}
void CommandLineParser::getByName(const String& name, bool space_delete, int type, void* dst) const
void CommandLineParser::getByName(const String& name, bool space_delete, Param type, void* dst) const
{
CV_TRY
{
@ -154,7 +154,7 @@ void CommandLineParser::getByName(const String& name, bool space_delete, int typ
}
void CommandLineParser::getByIndex(int index, bool space_delete, int type, void* dst) const
void CommandLineParser::getByIndex(int index, bool space_delete, Param type, void* dst) const
{
CV_TRY
{

4
modules/core/src/cuda_host_mem.cpp
View File

@ -60,7 +60,7 @@ public:
UMatData* allocate(int dims, const int* sizes, int type,
void* data0, size_t* step,
int /*flags*/, UMatUsageFlags /*usageFlags*/) const CV_OVERRIDE
AccessFlag /*flags*/, UMatUsageFlags /*usageFlags*/) const CV_OVERRIDE
{
size_t total = CV_ELEM_SIZE(type);
for (int i = dims-1; i >= 0; i--)
@ -100,7 +100,7 @@ public:
return u;
}
bool allocate(UMatData* u, int /*accessFlags*/, UMatUsageFlags /*usageFlags*/) const CV_OVERRIDE
bool allocate(UMatData* u, AccessFlag /*accessFlags*/, UMatUsageFlags /*usageFlags*/) const CV_OVERRIDE
{
return (u != NULL);
}

10
modules/core/src/matrix.cpp
View File

@ -7,7 +7,7 @@
namespace cv {
void MatAllocator::map(UMatData*, int) const
void MatAllocator::map(UMatData*, AccessFlag) const
{
}
@ -127,7 +127,7 @@ class StdMatAllocator CV_FINAL : public MatAllocator
{
public:
UMatData* allocate(int dims, const int* sizes, int type,
void* data0, size_t* step, int /*flags*/, UMatUsageFlags /*usageFlags*/) const CV_OVERRIDE
void* data0, size_t* step, AccessFlag /*flags*/, UMatUsageFlags /*usageFlags*/) const CV_OVERRIDE
{
size_t total = CV_ELEM_SIZE(type);
for( int i = dims-1; i >= 0; i-- )
@ -154,7 +154,7 @@ public:
return u;
}
bool allocate(UMatData* u, int /*accessFlags*/, UMatUsageFlags /*usageFlags*/) const CV_OVERRIDE
bool allocate(UMatData* u, AccessFlag /*accessFlags*/, UMatUsageFlags /*usageFlags*/) const CV_OVERRIDE
{
if(!u) return false;
return true;
@ -357,13 +357,13 @@ void Mat::create(int d, const int* _sizes, int _type)
a = a0;
CV_TRY
{
u = a->allocate(dims, size, _type, 0, step.p, 0, USAGE_DEFAULT);
u = a->allocate(dims, size, _type, 0, step.p, ACCESS_RW /* ignored */, USAGE_DEFAULT);
CV_Assert(u != 0);
}
CV_CATCH_ALL
{
if(a != a0)
u = a0->allocate(dims, size, _type, 0, step.p, 0, USAGE_DEFAULT);
u = a0->allocate(dims, size, _type, 0, step.p, ACCESS_RW /* ignored */, USAGE_DEFAULT);
CV_Assert(u != 0);
}
CV_Assert( step[dims-1] == (size_t)CV_ELEM_SIZE(flags) );

89
modules/core/src/matrix_wrap.cpp
View File

@ -14,8 +14,8 @@ namespace cv {
Mat _InputArray::getMat_(int i) const
{
int k = kind();
int accessFlags = flags & ACCESS_MASK;
_InputArray::KindFlag k = kind();
AccessFlag accessFlags = flags & ACCESS_MASK;
if( k == MAT )
{
@ -132,8 +132,8 @@ Mat _InputArray::getMat_(int i) const
UMat _InputArray::getUMat(int i) const
{
int k = kind();
int accessFlags = flags & ACCESS_MASK;
_InputArray::KindFlag k = kind();
AccessFlag accessFlags = flags & ACCESS_MASK;
if( k == UMAT )
{
@ -164,8 +164,8 @@ UMat _InputArray::getUMat(int i) const
void _InputArray::getMatVector(std::vector<Mat>& mv) const
{
int k = kind();
int accessFlags = flags & ACCESS_MASK;
_InputArray::KindFlag k = kind();
AccessFlag accessFlags = flags & ACCESS_MASK;
if( k == MAT )
{
@ -272,8 +272,8 @@ void _InputArray::getMatVector(std::vector<Mat>& mv) const
void _InputArray::getUMatVector(std::vector<UMat>& umv) const
{
int k = kind();
int accessFlags = flags & ACCESS_MASK;
_InputArray::KindFlag k = kind();
AccessFlag accessFlags = flags & ACCESS_MASK;
if( k == NONE )
{
@ -334,7 +334,7 @@ void _InputArray::getUMatVector(std::vector<UMat>& umv) const
cuda::GpuMat _InputArray::getGpuMat() const
{
int k = kind();
_InputArray::KindFlag k = kind();
if (k == CUDA_GPU_MAT)
{
@ -360,7 +360,7 @@ cuda::GpuMat _InputArray::getGpuMat() const
}
void _InputArray::getGpuMatVector(std::vector<cuda::GpuMat>& gpumv) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if (k == STD_VECTOR_CUDA_GPU_MAT)
{
gpumv = *(std::vector<cuda::GpuMat>*)obj;
@ -368,7 +368,7 @@ void _InputArray::getGpuMatVector(std::vector<cuda::GpuMat>& gpumv) const
}
ogl::Buffer _InputArray::getOGlBuffer() const
{
int k = kind();
_InputArray::KindFlag k = kind();
CV_Assert(k == OPENGL_BUFFER);
@ -376,7 +376,7 @@ ogl::Buffer _InputArray::getOGlBuffer() const
return *gl_buf;
}
int _InputArray::kind() const
_InputArray::KindFlag _InputArray::kind() const
{
return flags & KIND_MASK;
}
@ -393,7 +393,7 @@ int _InputArray::cols(int i) const
Size _InputArray::size(int i) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if( k == MAT )
{
@ -515,7 +515,8 @@ Size _InputArray::size(int i) const
int _InputArray::sizend(int* arrsz, int i) const
{
int j, d=0, k = kind();
int j, d = 0;
_InputArray::KindFlag k = kind();
if( k == NONE )
;
@ -583,7 +584,7 @@ int _InputArray::sizend(int* arrsz, int i) const
bool _InputArray::sameSize(const _InputArray& arr) const
{
int k1 = kind(), k2 = arr.kind();
_InputArray::KindFlag k1 = kind(), k2 = arr.kind();
Size sz1;
if( k1 == MAT )
@ -617,7 +618,7 @@ bool _InputArray::sameSize(const _InputArray& arr) const
int _InputArray::dims(int i) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if( k == MAT )
{
@ -714,7 +715,7 @@ int _InputArray::dims(int i) const
size_t _InputArray::total(int i) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if( k == MAT )
{
@ -763,7 +764,7 @@ size_t _InputArray::total(int i) const
int _InputArray::type(int i) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if( k == MAT )
return ((const Mat*)obj)->type();
@ -852,7 +853,7 @@ int _InputArray::channels(int i) const
bool _InputArray::empty() const
{
int k = kind();
_InputArray::KindFlag k = kind();
if( k == MAT )
return ((const Mat*)obj)->empty();
@ -924,7 +925,7 @@ bool _InputArray::empty() const
bool _InputArray::isContinuous(int i) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if( k == MAT )
return i < 0 ? ((const Mat*)obj)->isContinuous() : true;
@ -965,7 +966,7 @@ bool _InputArray::isContinuous(int i) const
bool _InputArray::isSubmatrix(int i) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if( k == MAT )
return i < 0 ? ((const Mat*)obj)->isSubmatrix() : false;
@ -1003,7 +1004,7 @@ bool _InputArray::isSubmatrix(int i) const
size_t _InputArray::offset(int i) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if( k == MAT )
{
@ -1067,7 +1068,7 @@ size_t _InputArray::offset(int i) const
size_t _InputArray::step(int i) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if( k == MAT )
{
@ -1127,7 +1128,7 @@ size_t _InputArray::step(int i) const
void _InputArray::copyTo(const _OutputArray& arr) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if( k == NONE )
arr.release();
@ -1156,7 +1157,7 @@ void _InputArray::copyTo(const _OutputArray& arr) const
void _InputArray::copyTo(const _OutputArray& arr, const _InputArray & mask) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if( k == NONE )
arr.release();
@ -1185,9 +1186,9 @@ bool _OutputArray::fixedType() const
return (flags & FIXED_TYPE) == FIXED_TYPE;
}
void _OutputArray::create(Size _sz, int mtype, int i, bool allowTransposed, int fixedDepthMask) const
void _OutputArray::create(Size _sz, int mtype, int i, bool allowTransposed, _OutputArray::DepthMask fixedDepthMask) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if( k == MAT && i < 0 && !allowTransposed && fixedDepthMask == 0 )
{
CV_Assert(!fixedSize() || ((Mat*)obj)->size.operator()() == _sz);
@ -1227,9 +1228,9 @@ void _OutputArray::create(Size _sz, int mtype, int i, bool allowTransposed, int
create(2, sizes, mtype, i, allowTransposed, fixedDepthMask);
}
void _OutputArray::create(int _rows, int _cols, int mtype, int i, bool allowTransposed, int fixedDepthMask) const
void _OutputArray::create(int _rows, int _cols, int mtype, int i, bool allowTransposed, _OutputArray::DepthMask fixedDepthMask) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if( k == MAT && i < 0 && !allowTransposed && fixedDepthMask == 0 )
{
CV_Assert(!fixedSize() || ((Mat*)obj)->size.operator()() == Size(_cols, _rows));
@ -1270,7 +1271,7 @@ void _OutputArray::create(int _rows, int _cols, int mtype, int i, bool allowTran
}
void _OutputArray::create(int d, const int* sizes, int mtype, int i,
bool allowTransposed, int fixedDepthMask) const
bool allowTransposed, _OutputArray::DepthMask fixedDepthMask) const
{
int sizebuf[2];
if(d == 1)
@ -1280,7 +1281,7 @@ void _OutputArray::create(int d, const int* sizes, int mtype, int i,
sizebuf[1] = 1;
sizes = sizebuf;
}
int k = kind();
_InputArray::KindFlag k = kind();
mtype = CV_MAT_TYPE(mtype);
if( k == MAT )
@ -1667,7 +1668,7 @@ void _OutputArray::release() const
{
CV_Assert(!fixedSize());
int k = kind();
_InputArray::KindFlag k = kind();
if( k == MAT )
{
@ -1735,7 +1736,7 @@ void _OutputArray::release() const
void _OutputArray::clear() const
{
int k = kind();
_InputArray::KindFlag k = kind();
if( k == MAT )
{
@ -1754,7 +1755,7 @@ bool _OutputArray::needed() const
Mat& _OutputArray::getMatRef(int i) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if( i < 0 )
{
CV_Assert( k == MAT );
@ -1779,7 +1780,7 @@ Mat& _OutputArray::getMatRef(int i) const
UMat& _OutputArray::getUMatRef(int i) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if( i < 0 )
{
CV_Assert( k == UMAT );
@ -1796,34 +1797,34 @@ UMat& _OutputArray::getUMatRef(int i) const
cuda::GpuMat& _OutputArray::getGpuMatRef() const
{
int k = kind();
_InputArray::KindFlag k = kind();
CV_Assert( k == CUDA_GPU_MAT );
return *(cuda::GpuMat*)obj;
}
std::vector<cuda::GpuMat>& _OutputArray::getGpuMatVecRef() const
{
int k = kind();
_InputArray::KindFlag k = kind();
CV_Assert(k == STD_VECTOR_CUDA_GPU_MAT);
return *(std::vector<cuda::GpuMat>*)obj;
}
ogl::Buffer& _OutputArray::getOGlBufferRef() const
{
int k = kind();
_InputArray::KindFlag k = kind();
CV_Assert( k == OPENGL_BUFFER );
return *(ogl::Buffer*)obj;
}
cuda::HostMem& _OutputArray::getHostMemRef() const
{
int k = kind();
_InputArray::KindFlag k = kind();
CV_Assert( k == CUDA_HOST_MEM );
return *(cuda::HostMem*)obj;
}
void _OutputArray::setTo(const _InputArray& arr, const _InputArray & mask) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if( k == NONE )
;
@ -1847,7 +1848,7 @@ void _OutputArray::setTo(const _InputArray& arr, const _InputArray & mask) const
void _OutputArray::assign(const UMat& u) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if (k == UMAT)
{
*(UMat*)obj = u;
@ -1869,7 +1870,7 @@ void _OutputArray::assign(const UMat& u) const
void _OutputArray::assign(const Mat& m) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if (k == UMAT)
{
m.copyTo(*(UMat*)obj); // TODO check m.getUMat()
@ -1891,7 +1892,7 @@ void _OutputArray::assign(const Mat& m) const
void _OutputArray::assign(const std::vector<UMat>& v) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if (k == STD_VECTOR_UMAT)
{
std::vector<UMat>& this_v = *(std::vector<UMat>*)obj;
@ -1929,7 +1930,7 @@ void _OutputArray::assign(const std::vector<UMat>& v) const
void _OutputArray::assign(const std::vector<Mat>& v) const
{
int k = kind();
_InputArray::KindFlag k = kind();
if (k == STD_VECTOR_UMAT)
{
std::vector<UMat>& this_v = *(std::vector<UMat>*)obj;

36
modules/core/src/ocl.cpp
View File

@ -2972,8 +2972,8 @@ int Kernel::set(int i, const KernelArg& arg)
cl_int status = 0;
if( arg.m )
{
int accessFlags = ((arg.flags & KernelArg::READ_ONLY) ? ACCESS_READ : 0) +
((arg.flags & KernelArg::WRITE_ONLY) ? ACCESS_WRITE : 0);
AccessFlag accessFlags = ((arg.flags & KernelArg::READ_ONLY) ? ACCESS_READ : static_cast<AccessFlag>(0)) |
((arg.flags & KernelArg::WRITE_ONLY) ? ACCESS_WRITE : static_cast<AccessFlag>(0));
bool ptronly = (arg.flags & KernelArg::PTR_ONLY) != 0;
cl_mem h = (cl_mem)arg.m->handle(accessFlags);
@ -3050,7 +3050,7 @@ int Kernel::set(int i, const KernelArg& arg)
i += 3;
}
}
p->addUMat(*arg.m, (accessFlags & ACCESS_WRITE) != 0);
p->addUMat(*arg.m, !!(accessFlags & ACCESS_WRITE));
return i;
}
status = clSetKernelArg(p->handle, (cl_uint)i, arg.sz, arg.obj);
@ -4516,13 +4516,13 @@ public:
}
UMatData* defaultAllocate(int dims, const int* sizes, int type, void* data, size_t* step,
int flags, UMatUsageFlags usageFlags) const
AccessFlag flags, UMatUsageFlags usageFlags) const
{
UMatData* u = matStdAllocator->allocate(dims, sizes, type, data, step, flags, usageFlags);
return u;
}
void getBestFlags(const Context& ctx, int /*flags*/, UMatUsageFlags usageFlags, int& createFlags, int& flags0) const
void getBestFlags(const Context& ctx, AccessFlag /*flags*/, UMatUsageFlags usageFlags, int& createFlags, UMatData::MemoryFlag& flags0) const
{
const Device& dev = ctx.device(0);
createFlags = 0;
@ -4530,13 +4530,13 @@ public:
createFlags |= CL_MEM_ALLOC_HOST_PTR;
if( dev.hostUnifiedMemory() )
flags0 = 0;
flags0 = static_cast<UMatData::MemoryFlag>(0);
else
flags0 = UMatData::COPY_ON_MAP;
}
UMatData* allocate(int dims, const int* sizes, int type,
void* data, size_t* step, int flags, UMatUsageFlags usageFlags) const CV_OVERRIDE
void* data, size_t* step, AccessFlag flags, UMatUsageFlags usageFlags) const CV_OVERRIDE
{
if(!useOpenCL())
return defaultAllocate(dims, sizes, type, data, step, flags, usageFlags);
@ -4552,7 +4552,8 @@ public:
Context& ctx = Context::getDefault();
flushCleanupQueue();
int createFlags = 0, flags0 = 0;
int createFlags = 0;
UMatData::MemoryFlag flags0 = static_cast<UMatData::MemoryFlag>(0);
getBestFlags(ctx, flags, usageFlags, createFlags, flags0);
void* handle = NULL;
@ -4600,7 +4601,7 @@ public:
return u;
}
bool allocate(UMatData* u, int accessFlags, UMatUsageFlags usageFlags) const CV_OVERRIDE
bool allocate(UMatData* u, AccessFlag accessFlags, UMatUsageFlags usageFlags) const CV_OVERRIDE
{
if(!u)
return false;
@ -4613,12 +4614,13 @@ public:
{
CV_Assert(u->origdata != 0);
Context& ctx = Context::getDefault();
int createFlags = 0, flags0 = 0;
int createFlags = 0;
UMatData::MemoryFlag flags0 = static_cast<UMatData::MemoryFlag>(0);
getBestFlags(ctx, accessFlags, usageFlags, createFlags, flags0);
cl_context ctx_handle = (cl_context)ctx.ptr();
int allocatorFlags = 0;
int tempUMatFlags = 0;
UMatData::MemoryFlag tempUMatFlags = static_cast<UMatData::MemoryFlag>(0);
void* handle = NULL;
cl_int retval = CL_SUCCESS;
@ -4703,7 +4705,7 @@ public:
u->flags |= tempUMatFlags;
u->allocatorFlags_ = allocatorFlags;
}
if(accessFlags & ACCESS_WRITE)
if (!!(accessFlags & ACCESS_WRITE))
u->markHostCopyObsolete(true);
return true;
}
@ -4749,7 +4751,7 @@ public:
CV_Assert(u->handle != 0);
CV_Assert(u->mapcount == 0);
if (u->flags & UMatData::ASYNC_CLEANUP)
if (!!(u->flags & UMatData::ASYNC_CLEANUP))
addToCleanupQueue(u);
else
deallocate_(u);
@ -4924,11 +4926,11 @@ public:
}
// synchronized call (external UMatDataAutoLock, see UMat::getMat)
void map(UMatData* u, int accessFlags) const CV_OVERRIDE
void map(UMatData* u, AccessFlag accessFlags) const CV_OVERRIDE
{
CV_Assert(u && u->handle);
if(accessFlags & ACCESS_WRITE)
if (!!(accessFlags & ACCESS_WRITE))
u->markDeviceCopyObsolete(true);
cl_command_queue q = (cl_command_queue)Queue::getDefault().ptr();
@ -4995,7 +4997,7 @@ public:
}
}
if( (accessFlags & ACCESS_READ) != 0 && u->hostCopyObsolete() )
if (!!(accessFlags & ACCESS_READ) && u->hostCopyObsolete())
{
AlignedDataPtr<false, true> alignedPtr(u->data, u->size, CV_OPENCL_DATA_PTR_ALIGNMENT);
#ifdef HAVE_OPENCL_SVM
@ -5735,7 +5737,7 @@ void convertFromBuffer(void* cl_mem_buffer, size_t step, int rows, int cols, int
dst.u = new UMatData(getOpenCLAllocator());
dst.u->data = 0;
dst.u->allocatorFlags_ = 0; // not allocated from any OpenCV buffer pool
dst.u->flags = 0;
dst.u->flags = static_cast<UMatData::MemoryFlag>(0);
dst.u->handle = cl_mem_buffer;
dst.u->origdata = 0;
dst.u->prevAllocator = 0;

4
modules/core/src/opengl.cpp
View File

@ -1804,8 +1804,8 @@ void convertFromGLTexture2D(const Texture2D& texture, OutputArray dst)
#endif
}
//void mapGLBuffer(const Buffer& buffer, UMat& dst, int accessFlags)
UMat mapGLBuffer(const Buffer& buffer, int accessFlags)
//void mapGLBuffer(const Buffer& buffer, UMat& dst, AccessFlag accessFlags)
UMat mapGLBuffer(const Buffer& buffer, AccessFlag accessFlags)
{
CV_UNUSED(buffer); CV_UNUSED(accessFlags);
#if !defined(HAVE_OPENGL)

2
modules/core/src/out.cpp
View File

@ -372,7 +372,7 @@ namespace cv
Formatted::~Formatted() {}
Formatter::~Formatter() {}
Ptr<Formatter> Formatter::get(int fmt)
Ptr<Formatter> Formatter::get(Formatter::FormatType fmt)
{
switch(fmt)
{

4
modules/core/src/precomp.hpp
View File

@ -210,7 +210,7 @@ enum { BLOCK_SIZE = 1024 };
#define ARITHM_USE_IPP 0
#endif
inline bool checkScalar(const Mat& sc, int atype, int sckind, int akind)
inline bool checkScalar(const Mat& sc, int atype, _InputArray::KindFlag sckind, _InputArray::KindFlag akind)
{
if( sc.dims > 2 || !sc.isContinuous() )
return false;
@ -224,7 +224,7 @@ inline bool checkScalar(const Mat& sc, int atype, int sckind, int akind)
(sz == Size(1, 4) && sc.type() == CV_64F && cn <= 4);
}
inline bool checkScalar(InputArray sc, int atype, int sckind, int akind)
inline bool checkScalar(InputArray sc, int atype, _InputArray::KindFlag sckind, _InputArray::KindFlag akind)
{
if( sc.dims() > 2 || !sc.isContinuous() )
return false;

16
modules/core/src/umatrix.cpp
View File

@ -64,7 +64,7 @@ UMatData::UMatData(const MatAllocator* allocator)
urefcount = refcount = mapcount = 0;
data = origdata = 0;
size = 0;
flags = 0;
flags = static_cast<UMatData::MemoryFlag>(0);
handle = 0;
userdata = 0;
allocatorFlags_ = 0;
@ -78,7 +78,7 @@ UMatData::~UMatData()
CV_Assert(mapcount == 0);
data = origdata = 0;
size = 0;
flags = 0;
flags = static_cast<UMatData::MemoryFlag>(0);
handle = 0;
userdata = 0;
allocatorFlags_ = 0;
@ -333,7 +333,7 @@ void finalizeHdr(UMat& m)
}
UMat Mat::getUMat(int accessFlags, UMatUsageFlags usageFlags) const
UMat Mat::getUMat(AccessFlag accessFlags, UMatUsageFlags usageFlags) const
{
UMat hdr;
if(!data)
@ -444,13 +444,13 @@ void UMat::create(int d, const int* _sizes, int _type, UMatUsageFlags _usageFlag
}
CV_TRY
{
u = a->allocate(dims, size, _type, 0, step.p, 0, usageFlags);
u = a->allocate(dims, size, _type, 0, step.p, ACCESS_RW /* ignored */, usageFlags);
CV_Assert(u != 0);
}
CV_CATCH_ALL
{
if(a != a0)
u = a0->allocate(dims, size, _type, 0, step.p, 0, usageFlags);
u = a0->allocate(dims, size, _type, 0, step.p, ACCESS_RW /* ignored */, usageFlags);
CV_Assert(u != 0);
}
CV_Assert( step[dims-1] == (size_t)CV_ELEM_SIZE(flags) );
@ -813,7 +813,7 @@ UMat UMat::reshape(int _cn, int _newndims, const int* _newsz) const
CV_Error(CV_StsNotImplemented, "Reshaping of n-dimensional non-continuous matrices is not supported yet");
}
Mat UMat::getMat(int accessFlags) const
Mat UMat::getMat(AccessFlag accessFlags) const
{
if(!u)
return Mat();
@ -840,7 +840,7 @@ Mat UMat::getMat(int accessFlags) const
}
}
void* UMat::handle(int accessFlags) const
void* UMat::handle(AccessFlag accessFlags) const
{
if( !u )
return 0;
@ -852,7 +852,7 @@ void* UMat::handle(int accessFlags) const
u->currAllocator->unmap(u);
}
if ((accessFlags & ACCESS_WRITE) != 0)
if (!!(accessFlags & ACCESS_WRITE))
u->markHostCopyObsolete(true);
return u->handle;

6
modules/core/test/test_mat.cpp
View File

@ -946,7 +946,7 @@ void Core_ArrayOpTest::run( int /* start_from */)
}
template <class ElemType>
template <class T>
int calcDiffElemCountImpl(const vector<Mat>& mv, const Mat& m)
{
int diffElemCount = 0;
@ -955,12 +955,12 @@ int calcDiffElemCountImpl(const vector<Mat>& mv, const Mat& m)
{
for(int x = 0; x < m.cols; x++)
{
const ElemType* mElem = &m.at<ElemType>(y,x*mChannels);
const T* mElem = &m.at<T>(y, x*mChannels);
size_t loc = 0;
for(size_t i = 0; i < mv.size(); i++)
{
const size_t mvChannel = mv[i].channels();
const ElemType* mvElem = &mv[i].at<ElemType>(y,x*(int)mvChannel);
const T* mvElem = &mv[i].at<T>(y, x*(int)mvChannel);
for(size_t li = 0; li < mvChannel; li++)
if(mElem[loc + li] != mvElem[li])
diffElemCount++;

4
modules/dnn/include/opencv2/dnn/dict.hpp
View File

@ -95,7 +95,7 @@ struct CV_EXPORTS_W DictValue
private:
int type;
Param type;
union
{
@ -105,7 +105,7 @@ private:
void *pv;
};
DictValue(int _type, void *_p) : type(_type), pv(_p) {}
DictValue(Param _type, void *_p) : type(_type), pv(_p) {}
void release();
};

22
modules/dnn/include/opencv2/dnn/dnn.inl.hpp
View File

@ -199,6 +199,16 @@ inline void DictValue::release()
case Param::REAL:
delete pd;
break;
case Param::BOOLEAN:
case Param::MAT:
case Param::MAT_VECTOR:
case Param::ALGORITHM:
case Param::FLOAT:
case Param::UNSIGNED_INT:
case Param::UINT64:
case Param::UCHAR:
case Param::SCALAR:
break; // unhandled
}
}
@ -273,8 +283,18 @@ inline int DictValue::size() const
return (int)ps->size();
case Param::REAL:
return (int)pd->size();
case Param::BOOLEAN:
case Param::MAT:
case Param::MAT_VECTOR:
case Param::ALGORITHM:
case Param::FLOAT:
case Param::UNSIGNED_INT:
case Param::UINT64:
case Param::UCHAR:
case Param::SCALAR:
break; // unhandled
}
CV_Error(Error::StsInternal, "");
CV_Error_(Error::StsInternal, ("Unhandled type (%d)", static_cast<int>(type)));
}
inline std::ostream &operator<<(std::ostream &stream, const DictValue &dictv)

165
modules/features2d/include/opencv2/features2d.hpp
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

21
modules/features2d/misc/python/pyopencv_features2d.hpp
View File

@ -1,3 +1,24 @@
#ifdef HAVE_OPENCV_FEATURES2D
typedef SimpleBlobDetector::Params SimpleBlobDetector_Params;
typedef AKAZE::DescriptorType AKAZE_DescriptorType;
typedef AgastFeatureDetector::DetectorType AgastFeatureDetector_DetectorType;
typedef FastFeatureDetector::DetectorType FastFeatureDetector_DetectorType;
typedef DescriptorMatcher::MatcherType DescriptorMatcher_MatcherType;
typedef KAZE::DiffusivityType KAZE_DiffusivityType;
typedef ORB::ScoreType ORB_ScoreType;
CV_PY_FROM_ENUM(AKAZE::DescriptorType);
CV_PY_TO_ENUM(AKAZE::DescriptorType);
CV_PY_FROM_ENUM(AgastFeatureDetector::DetectorType);
CV_PY_TO_ENUM(AgastFeatureDetector::DetectorType);
CV_PY_FROM_ENUM(DrawMatchesFlags);
CV_PY_TO_ENUM(DrawMatchesFlags);
CV_PY_FROM_ENUM(FastFeatureDetector::DetectorType);
CV_PY_TO_ENUM(FastFeatureDetector::DetectorType);
CV_PY_FROM_ENUM(DescriptorMatcher::MatcherType);
CV_PY_TO_ENUM(DescriptorMatcher::MatcherType);
CV_PY_FROM_ENUM(KAZE::DiffusivityType);
CV_PY_TO_ENUM(KAZE::DiffusivityType);
CV_PY_FROM_ENUM(ORB::ScoreType);
CV_PY_TO_ENUM(ORB::ScoreType);
#endif

16
modules/features2d/src/agast.cpp
View File

@ -7446,7 +7446,7 @@ static void OAST_9_16(InputArray _img, std::vector<KeyPoint>& keypoints, int thr
#else // !(defined __i386__ || defined(_M_IX86) || defined __x86_64__ || defined(_M_X64))
static void AGAST_ALL(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, int agasttype)
static void AGAST_ALL(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, AgastFeatureDetector::DetectorType agasttype)
{
cv::Mat img;
if(!_img.getMat().isContinuous())
@ -7944,8 +7944,8 @@ void AGAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, boo
class AgastFeatureDetector_Impl CV_FINAL : public AgastFeatureDetector
{
public:
AgastFeatureDetector_Impl( int _threshold, bool _nonmaxSuppression, int _type )
: threshold(_threshold), nonmaxSuppression(_nonmaxSuppression), type((short)_type)
AgastFeatureDetector_Impl( int _threshold, bool _nonmaxSuppression, DetectorType _type )
: threshold(_threshold), nonmaxSuppression(_nonmaxSuppression), type(_type)
{}
void detect( InputArray _image, std::vector<KeyPoint>& keypoints, InputArray _mask ) CV_OVERRIDE
@ -7998,20 +7998,20 @@ public:
void setNonmaxSuppression(bool f) CV_OVERRIDE { nonmaxSuppression = f; }
bool getNonmaxSuppression() const CV_OVERRIDE { return nonmaxSuppression; }
void setType(int type_) CV_OVERRIDE { type = type_; }
int getType() const CV_OVERRIDE { return type; }
void setType(DetectorType type_) CV_OVERRIDE{ type = type_; }
DetectorType getType() const CV_OVERRIDE{ return type; }
int threshold;
bool nonmaxSuppression;
int type;
DetectorType type;
};
Ptr<AgastFeatureDetector> AgastFeatureDetector::create( int threshold, bool nonmaxSuppression, int type )
Ptr<AgastFeatureDetector> AgastFeatureDetector::create( int threshold, bool nonmaxSuppression, AgastFeatureDetector::DetectorType type )
{
return makePtr<AgastFeatureDetector_Impl>(threshold, nonmaxSuppression, type);
}
void AGAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool nonmax_suppression, int type)
void AGAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool nonmax_suppression, AgastFeatureDetector::DetectorType type)
{
CV_INSTRUMENT_REGION();

4
modules/features2d/src/agast_score.cpp
View File

@ -47,7 +47,7 @@ The references are:
namespace cv
{
void makeAgastOffsets(int pixel[16], int rowStride, int type)
void makeAgastOffsets(int pixel[16], int rowStride, AgastFeatureDetector::DetectorType type)
{
static const int offsets16[][2] =
{
@ -9400,7 +9400,7 @@ int agast_tree_search(const uint32_t table_struct32[], int pixel_[], const unsig
}
// universal pixel mask
int AGAST_ALL_SCORE(const uchar* ptr, const int pixel[], int threshold, int agasttype)
int AGAST_ALL_SCORE(const uchar* ptr, const int pixel[], int threshold, AgastFeatureDetector::DetectorType agasttype)
{
int bmin = threshold;
int bmax = 255;

6
modules/features2d/src/agast_score.hpp
View File

@ -54,13 +54,13 @@ namespace cv
#if !(defined __i386__ || defined(_M_IX86) || defined __x86_64__ || defined(_M_X64))
int agast_tree_search(const uint32_t table_struct32[], int pixel_[], const unsigned char* const ptr, int threshold);
int AGAST_ALL_SCORE(const uchar* ptr, const int pixel[], int threshold, int agasttype);
int AGAST_ALL_SCORE(const uchar* ptr, const int pixel[], int threshold, AgastFeatureDetector::DetectorType agasttype);
#endif //!(defined __i386__ || defined(_M_IX86) || defined __x86_64__ || defined(_M_X64))
void makeAgastOffsets(int pixel[16], int row_stride, int type);
void makeAgastOffsets(int pixel[16], int row_stride, AgastFeatureDetector::DetectorType type);
template<int type>
template<AgastFeatureDetector::DetectorType type>
int agast_cornerScore(const uchar* ptr, const int pixel[], int threshold);

24
modules/features2d/src/akaze.cpp
View File

@ -60,8 +60,8 @@ namespace cv
class AKAZE_Impl : public AKAZE
{
public:
AKAZE_Impl(int _descriptor_type, int _descriptor_size, int _descriptor_channels,
float _threshold, int _octaves, int _sublevels, int _diffusivity)
AKAZE_Impl(DescriptorType _descriptor_type, int _descriptor_size, int _descriptor_channels,
float _threshold, int _octaves, int _sublevels, KAZE::DiffusivityType _diffusivity)
: descriptor(_descriptor_type)
, descriptor_channels(_descriptor_channels)
, descriptor_size(_descriptor_size)
@ -77,8 +77,8 @@ namespace cv
}
void setDescriptorType(int dtype) CV_OVERRIDE { descriptor = dtype; }
int getDescriptorType() const CV_OVERRIDE { return descriptor; }
void setDescriptorType(DescriptorType dtype) CV_OVERRIDE{ descriptor = dtype; }
DescriptorType getDescriptorType() const CV_OVERRIDE{ return descriptor; }
void setDescriptorSize(int dsize) CV_OVERRIDE { descriptor_size = dsize; }
int getDescriptorSize() const CV_OVERRIDE { return descriptor_size; }
@ -95,8 +95,8 @@ namespace cv
void setNOctaveLayers(int octaveLayers_) CV_OVERRIDE { sublevels = octaveLayers_; }
int getNOctaveLayers() const CV_OVERRIDE { return sublevels; }
void setDiffusivity(int diff_) CV_OVERRIDE { diffusivity = diff_; }
int getDiffusivity() const CV_OVERRIDE { return diffusivity; }
void setDiffusivity(KAZE::DiffusivityType diff_) CV_OVERRIDE{ diffusivity = diff_; }
KAZE::DiffusivityType getDiffusivity() const CV_OVERRIDE{ return diffusivity; }
// returns the descriptor size in bytes
int descriptorSize() const CV_OVERRIDE
@ -218,28 +218,28 @@ namespace cv
void read(const FileNode& fn) CV_OVERRIDE
{
descriptor = (int)fn["descriptor"];
descriptor = static_cast<DescriptorType>((int)fn["descriptor"]);
descriptor_channels = (int)fn["descriptor_channels"];
descriptor_size = (int)fn["descriptor_size"];
threshold = (float)fn["threshold"];
octaves = (int)fn["octaves"];
sublevels = (int)fn["sublevels"];
diffusivity = (int)fn["diffusivity"];
diffusivity = static_cast<KAZE::DiffusivityType>((int)fn["diffusivity"]);
}
int descriptor;
DescriptorType descriptor;
int descriptor_channels;
int descriptor_size;
float threshold;
int octaves;
int sublevels;
int diffusivity;
KAZE::DiffusivityType diffusivity;
};
Ptr<AKAZE> AKAZE::create(int descriptor_type,
Ptr<AKAZE> AKAZE::create(DescriptorType descriptor_type,
int descriptor_size, int descriptor_channels,
float threshold, int octaves,
int sublevels, int diffusivity)
int sublevels, KAZE::DiffusivityType diffusivity)
{
return makePtr<AKAZE_Impl>(descriptor_type, descriptor_size, descriptor_channels,
threshold, octaves, sublevels, diffusivity);

16
modules/features2d/src/draw.cpp
View File

@ -50,12 +50,12 @@ namespace cv
/*
* Functions to draw keypoints and matches.
*/
static inline void _drawKeypoint( InputOutputArray img, const KeyPoint& p, const Scalar& color, int flags )
static inline void _drawKeypoint( InputOutputArray img, const KeyPoint& p, const Scalar& color, DrawMatchesFlags flags )
{
CV_Assert( !img.empty() );
Point center( cvRound(p.pt.x * draw_multiplier), cvRound(p.pt.y * draw_multiplier) );
if( flags & DrawMatchesFlags::DRAW_RICH_KEYPOINTS )
if( !!(flags & DrawMatchesFlags::DRAW_RICH_KEYPOINTS) )
{
int radius = cvRound(p.size/2 * draw_multiplier); // KeyPoint::size is a diameter
@ -89,7 +89,7 @@ static inline void _drawKeypoint( InputOutputArray img, const KeyPoint& p, const
}
void drawKeypoints( InputArray image, const std::vector<KeyPoint>& keypoints, InputOutputArray outImage,
const Scalar& _color, int flags )
const Scalar& _color, DrawMatchesFlags flags )
{
CV_INSTRUMENT_REGION();
@ -125,12 +125,12 @@ void drawKeypoints( InputArray image, const std::vector<KeyPoint>& keypoints, In
static void _prepareImgAndDrawKeypoints( InputArray img1, const std::vector<KeyPoint>& keypoints1,
InputArray img2, const std::vector<KeyPoint>& keypoints2,
InputOutputArray _outImg, Mat& outImg1, Mat& outImg2,
const Scalar& singlePointColor, int flags )
const Scalar& singlePointColor, DrawMatchesFlags flags )
{
Mat outImg;
Size img1size = img1.size(), img2size = img2.size();
Size size( img1size.width + img2size.width, MAX(img1size.height, img2size.height) );
if( flags & DrawMatchesFlags::DRAW_OVER_OUTIMG )
if( !!(flags & DrawMatchesFlags::DRAW_OVER_OUTIMG) )
{
outImg = _outImg.getMat();
if( size.width > outImg.cols || size.height > outImg.rows )
@ -169,7 +169,7 @@ static void _prepareImgAndDrawKeypoints( InputArray img1, const std::vector<KeyP
}
static inline void _drawMatch( InputOutputArray outImg, InputOutputArray outImg1, InputOutputArray outImg2 ,
const KeyPoint& kp1, const KeyPoint& kp2, const Scalar& matchColor, int flags )
const KeyPoint& kp1, const KeyPoint& kp2, const Scalar& matchColor, DrawMatchesFlags flags )
{
RNG& rng = theRNG();
bool isRandMatchColor = matchColor == Scalar::all(-1);
@ -192,7 +192,7 @@ void drawMatches( InputArray img1, const std::vector<KeyPoint>& keypoints1,
InputArray img2, const std::vector<KeyPoint>& keypoints2,
const std::vector<DMatch>& matches1to2, InputOutputArray outImg,
const Scalar& matchColor, const Scalar& singlePointColor,
const std::vector<char>& matchesMask, int flags )
const std::vector<char>& matchesMask, DrawMatchesFlags flags )
{
if( !matchesMask.empty() && matchesMask.size() != matches1to2.size() )
CV_Error( Error::StsBadSize, "matchesMask must have the same size as matches1to2" );
@ -221,7 +221,7 @@ 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, const Scalar& singlePointColor,
const std::vector<std::vector<char> >& matchesMask, int flags )
const std::vector<std::vector<char> >& matchesMask, DrawMatchesFlags flags )
{
if( !matchesMask.empty() && matchesMask.size() != matches1to2.size() )
CV_Error( Error::StsBadSize, "matchesMask must have the same size as matches1to2" );

20
modules/features2d/src/fast.cpp
View File

@ -415,7 +415,7 @@ static bool openvx_FAST(InputArray _img, std::vector<KeyPoint>& keypoints,
#endif
static inline int hal_FAST(cv::Mat& src, std::vector<KeyPoint>& keypoints, int threshold, bool nonmax_suppression, int type)
static inline int hal_FAST(cv::Mat& src, std::vector<KeyPoint>& keypoints, int threshold, bool nonmax_suppression, FastFeatureDetector::DetectorType type)
{
if (threshold > 20)
return CV_HAL_ERROR_NOT_IMPLEMENTED;
@ -472,7 +472,7 @@ static inline int hal_FAST(cv::Mat& src, std::vector<KeyPoint>& keypoints, int t
return CV_HAL_ERROR_OK;
}
void FAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool nonmax_suppression, int type)
void FAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool nonmax_suppression, FastFeatureDetector::DetectorType type)
{
CV_INSTRUMENT_REGION();
@ -514,8 +514,8 @@ void FAST(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool
class FastFeatureDetector_Impl CV_FINAL : public FastFeatureDetector
{
public:
FastFeatureDetector_Impl( int _threshold, bool _nonmaxSuppression, int _type )
: threshold(_threshold), nonmaxSuppression(_nonmaxSuppression), type((short)_type)
FastFeatureDetector_Impl( int _threshold, bool _nonmaxSuppression, FastFeatureDetector::DetectorType _type )
: threshold(_threshold), nonmaxSuppression(_nonmaxSuppression), type(_type)
{}
void detect( InputArray _image, std::vector<KeyPoint>& keypoints, InputArray _mask ) CV_OVERRIDE
@ -548,7 +548,7 @@ public:
else if(prop == NONMAX_SUPPRESSION)
nonmaxSuppression = value != 0;
else if(prop == FAST_N)
type = cvRound(value);
type = static_cast<FastFeatureDetector::DetectorType>(cvRound(value));
else
CV_Error(Error::StsBadArg, "");
}
@ -560,7 +560,7 @@ public:
if(prop == NONMAX_SUPPRESSION)
return nonmaxSuppression;
if(prop == FAST_N)
return type;
return static_cast<int>(type);
CV_Error(Error::StsBadArg, "");
return 0;
}
@ -571,15 +571,15 @@ public:
void setNonmaxSuppression(bool f) CV_OVERRIDE { nonmaxSuppression = f; }
bool getNonmaxSuppression() const CV_OVERRIDE { return nonmaxSuppression; }
void setType(int type_) CV_OVERRIDE { type = type_; }
int getType() const CV_OVERRIDE { return type; }
void setType(FastFeatureDetector::DetectorType type_) CV_OVERRIDE{ type = type_; }
FastFeatureDetector::DetectorType getType() const CV_OVERRIDE{ return type; }
int threshold;
bool nonmaxSuppression;
int type;
FastFeatureDetector::DetectorType type;
};
Ptr<FastFeatureDetector> FastFeatureDetector::create( int threshold, bool nonmaxSuppression, int type )
Ptr<FastFeatureDetector> FastFeatureDetector::create( int threshold, bool nonmaxSuppression, FastFeatureDetector::DetectorType type )
{
return makePtr<FastFeatureDetector_Impl>(threshold, nonmaxSuppression, type);
}

4
modules/features2d/src/hal_replacement.hpp
View File

@ -66,7 +66,7 @@
@param width,height Source image dimensions
@param type FAST type
*/
inline int hal_ni_FAST_dense(const uchar* src_data, size_t src_step, uchar* dst_data, size_t dst_step, int width, int height, int type) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
inline int hal_ni_FAST_dense(const uchar* src_data, size_t src_step, uchar* dst_data, size_t dst_step, int width, int height, cv::FastFeatureDetector::DetectorType type) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
//! @cond IGNORED
#define cv_hal_FAST_dense hal_ni_FAST_dense
@ -94,7 +94,7 @@ inline int hal_ni_FAST_NMS(const uchar* src_data, size_t src_step, uchar* dst_da
@param nonmax_suppression Indicates if make nonmaxima suppression or not.
@param type FAST type
*/
inline int hal_ni_FAST(const uchar* src_data, size_t src_step, int width, int height, uchar* keypoints_data, size_t* keypoints_count, int threshold, bool nonmax_suppression, int type) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
inline int hal_ni_FAST(const uchar* src_data, size_t src_step, int width, int height, uchar* keypoints_data, size_t* keypoints_count, int threshold, bool nonmax_suppression, int /*cv::FastFeatureDetector::DetectorType*/ type) { return CV_HAL_ERROR_NOT_IMPLEMENTED; }
//! @cond IGNORED
#define cv_hal_FAST hal_ni_FAST

12
modules/features2d/src/kaze.cpp
View File

@ -57,7 +57,7 @@ namespace cv
{
public:
KAZE_Impl(bool _extended, bool _upright, float _threshold, int _octaves,
int _sublevels, int _diffusivity)
int _sublevels, KAZE::DiffusivityType _diffusivity)
: extended(_extended)
, upright(_upright)
, threshold(_threshold)
@ -84,8 +84,8 @@ namespace cv
void setNOctaveLayers(int octaveLayers_) CV_OVERRIDE { sublevels = octaveLayers_; }
int getNOctaveLayers() const CV_OVERRIDE { return sublevels; }
void setDiffusivity(int diff_) CV_OVERRIDE { diffusivity = diff_; }
int getDiffusivity() const CV_OVERRIDE { return diffusivity; }
void setDiffusivity(KAZE::DiffusivityType diff_) CV_OVERRIDE{ diffusivity = diff_; }
KAZE::DiffusivityType getDiffusivity() const CV_OVERRIDE{ return diffusivity; }
// returns the descriptor size in bytes
int descriptorSize() const CV_OVERRIDE
@ -178,7 +178,7 @@ namespace cv
threshold = (float)fn["threshold"];
octaves = (int)fn["octaves"];
sublevels = (int)fn["sublevels"];
diffusivity = (int)fn["diffusivity"];
diffusivity = static_cast<KAZE::DiffusivityType>((int)fn["diffusivity"]);
}
bool extended;
@ -186,13 +186,13 @@ namespace cv
float threshold;
int octaves;
int sublevels;
int diffusivity;
KAZE::DiffusivityType diffusivity;
};
Ptr<KAZE> KAZE::create(bool extended, bool upright,
float threshold,
int octaves, int sublevels,
int diffusivity)
KAZE::DiffusivityType diffusivity)
{
return makePtr<KAZE_Impl>(extended, upright, threshold, octaves, sublevels, diffusivity);
}

4
modules/features2d/src/kaze/AKAZEConfig.h
View File

@ -45,12 +45,12 @@ struct AKAZEOptions {
float soffset; ///< Base scale offset (sigma units)
float derivative_factor; ///< Factor for the multiscale derivatives
float sderivatives; ///< Smoothing factor for the derivatives
int diffusivity; ///< Diffusivity type
KAZE::DiffusivityType diffusivity; ///< Diffusivity type
float dthreshold; ///< Detector response threshold to accept point
float min_dthreshold; ///< Minimum detector threshold to accept a point
int descriptor; ///< Type of descriptor
AKAZE::DescriptorType descriptor; ///< Type of descriptor
int descriptor_size; ///< Size of the descriptor in bits. 0->Full size
int descriptor_channels; ///< Number of channels in the descriptor (1, 2, 3)
int descriptor_pattern_size; ///< Actual patch size is 2*pattern_size*point.scale

4
modules/features2d/src/kaze/AKAZEFeatures.cpp
View File

@ -377,7 +377,7 @@ ocl_pm_g2(InputArray Lx_, InputArray Ly_, OutputArray Lflow_, float kcontrast)
#endif // HAVE_OPENCL
static inline void
compute_diffusivity(InputArray Lx, InputArray Ly, OutputArray Lflow, float kcontrast, int diffusivity)
compute_diffusivity(InputArray Lx, InputArray Ly, OutputArray Lflow, float kcontrast, KAZE::DiffusivityType diffusivity)
{
CV_INSTRUMENT_REGION();
@ -398,7 +398,7 @@ compute_diffusivity(InputArray Lx, InputArray Ly, OutputArray Lflow, float kcont
charbonnier_diffusivity(Lx, Ly, Lflow, kcontrast);
break;
default:
CV_Error(diffusivity, "Diffusivity is not supported");
CV_Error_(Error::StsError, ("Diffusivity is not supported: %d", static_cast<int>(diffusivity)));
break;
}
}

2
modules/features2d/src/kaze/KAZEConfig.h
View File

@ -36,7 +36,7 @@ struct KAZEOptions {
{
}
int diffusivity;
KAZE::DiffusivityType diffusivity;
float soffset;
int omax;
int nsublevels;

2
modules/features2d/src/matchers.cpp
View File

@ -1049,7 +1049,7 @@ Ptr<DescriptorMatcher> DescriptorMatcher::create( const String& descriptorMatche
return dm;
}
Ptr<DescriptorMatcher> DescriptorMatcher::create(int matcherType)
Ptr<DescriptorMatcher> DescriptorMatcher::create( const MatcherType& matcherType )
{

12
modules/features2d/src/orb.cpp
View File

@ -655,7 +655,7 @@ class ORB_Impl CV_FINAL : public ORB
{
public:
explicit ORB_Impl(int _nfeatures, float _scaleFactor, int _nlevels, int _edgeThreshold,
int _firstLevel, int _WTA_K, int _scoreType, int _patchSize, int _fastThreshold) :
int _firstLevel, int _WTA_K, ORB::ScoreType _scoreType, int _patchSize, int _fastThreshold) :
nfeatures(_nfeatures), scaleFactor(_scaleFactor), nlevels(_nlevels),
edgeThreshold(_edgeThreshold), firstLevel(_firstLevel), wta_k(_WTA_K),
scoreType(_scoreType), patchSize(_patchSize), fastThreshold(_fastThreshold)
@ -679,8 +679,8 @@ public:
void setWTA_K(int wta_k_) CV_OVERRIDE { wta_k = wta_k_; }
int getWTA_K() const CV_OVERRIDE { return wta_k; }
void setScoreType(int scoreType_) CV_OVERRIDE { scoreType = scoreType_; }
int getScoreType() const CV_OVERRIDE { return scoreType; }
void setScoreType(ORB::ScoreType scoreType_) CV_OVERRIDE{ scoreType = scoreType_; }
ORB::ScoreType getScoreType() const CV_OVERRIDE{ return scoreType; }
void setPatchSize(int patchSize_) CV_OVERRIDE { patchSize = patchSize_; }
int getPatchSize() const CV_OVERRIDE { return patchSize; }
@ -707,7 +707,7 @@ protected:
int edgeThreshold;
int firstLevel;
int wta_k;
int scoreType;
ORB::ScoreType scoreType;
int patchSize;
int fastThreshold;
};
@ -775,7 +775,7 @@ static void computeKeyPoints(const Mat& imagePyramid,
const std::vector<float>& layerScale,
std::vector<KeyPoint>& allKeypoints,
int nfeatures, double scaleFactor,
int edgeThreshold, int patchSize, int scoreType,
int edgeThreshold, int patchSize, ORB::ScoreType scoreType,
bool useOCL, int fastThreshold )
{
#ifndef HAVE_OPENCL
@ -1195,7 +1195,7 @@ void ORB_Impl::detectAndCompute( InputArray _image, InputArray _mask,
}
Ptr<ORB> ORB::create(int nfeatures, float scaleFactor, int nlevels, int edgeThreshold,
int firstLevel, int wta_k, int scoreType, int patchSize, int fastThreshold)
int firstLevel, int wta_k, ORB::ScoreType scoreType, int patchSize, int fastThreshold)
{
CV_Assert(firstLevel >= 0);
return makePtr<ORB_Impl>(nfeatures, scaleFactor, nlevels, edgeThreshold,

4
modules/features2d/test/test_agast.cpp
View File

@ -75,8 +75,8 @@ void CV_AgastTest::run( int )
vector<KeyPoint> keypoints1;
vector<KeyPoint> keypoints2;
AGAST(gray1, keypoints1, 30, true, type);
AGAST(gray2, keypoints2, (type > 0 ? 30 : 20), true, type);
AGAST(gray1, keypoints1, 30, true, static_cast<AgastFeatureDetector::DetectorType>(type));
AGAST(gray2, keypoints2, (type > 0 ? 30 : 20), true, static_cast<AgastFeatureDetector::DetectorType>(type));
for(size_t i = 0; i < keypoints1.size(); ++i)
{

4
modules/features2d/test/test_fast.cpp
View File

@ -75,8 +75,8 @@ void CV_FastTest::run( int )
vector<KeyPoint> keypoints1;
vector<KeyPoint> keypoints2;
FAST(gray1, keypoints1, 30, true, type);
FAST(gray2, keypoints2, (type > 0 ? 30 : 20), true, type);
FAST(gray1, keypoints1, 30, true, static_cast<FastFeatureDetector::DetectorType>(type));
FAST(gray2, keypoints2, (type > 0 ? 30 : 20), true, static_cast<FastFeatureDetector::DetectorType>(type));
for(size_t i = 0; i < keypoints1.size(); ++i)
{

2
modules/features2d/test/test_orb.cpp
View File

@ -100,7 +100,7 @@ TEST(Features2D_ORB, crash)
int edgeThreshold = 4;
int firstLevel = 0;
int WTA_K = 2;
int scoreType = cv::ORB::HARRIS_SCORE;
ORB::ScoreType scoreType = cv::ORB::HARRIS_SCORE;
int patchSize = 47;
int fastThreshold = 20;

8
modules/objdetect/include/opencv2/objdetect.hpp
View File

@ -372,10 +372,12 @@ http://www.learnopencv.com/handwritten-digits-classification-an-opencv-c-python-
struct CV_EXPORTS_W HOGDescriptor
{
public:
enum { L2Hys = 0 //!< Default histogramNormType
enum HistogramNormType { L2Hys = 0 //!< Default histogramNormType
};
enum { DEFAULT_NLEVELS = 64 //!< Default nlevels value.
};
enum DescriptorStorageFormat { DESCR_FORMAT_COL_BY_COL, DESCR_FORMAT_ROW_BY_ROW };
/**@brief Creates the HOG descriptor and detector with default params.
aqual to HOGDescriptor(Size(64,128), Size(16,16), Size(8,8), Size(8,8), 9, 1 )
@ -402,7 +404,7 @@ public:
*/
CV_WRAP HOGDescriptor(Size _winSize, Size _blockSize, Size _blockStride,
Size _cellSize, int _nbins, int _derivAperture=1, double _winSigma=-1,
int _histogramNormType=HOGDescriptor::L2Hys,
HOGDescriptor::HistogramNormType _histogramNormType=HOGDescriptor::L2Hys,
double _L2HysThreshold=0.2, bool _gammaCorrection=false,
int _nlevels=HOGDescriptor::DEFAULT_NLEVELS, bool _signedGradient=false)
: winSize(_winSize), blockSize(_blockSize), blockStride(_blockStride), cellSize(_cellSize),
@ -603,7 +605,7 @@ public:
CV_PROP double winSigma;
//! histogramNormType
CV_PROP int histogramNormType;
CV_PROP HOGDescriptor::HistogramNormType histogramNormType;
//! L2-Hys normalization method shrinkage.
CV_PROP double L2HysThreshold;

13
modules/objdetect/misc/python/pyopencv_objdetect.hpp Normal file
View File

@ -0,0 +1,13 @@
#ifdef HAVE_OPENCV_OBJDETECT
#include "opencv2/objdetect.hpp"
typedef HOGDescriptor::HistogramNormType HOGDescriptor_HistogramNormType;
typedef HOGDescriptor::DescriptorStorageFormat HOGDescriptor_DescriptorStorageFormat;
CV_PY_FROM_ENUM(HOGDescriptor::HistogramNormType);
CV_PY_TO_ENUM(HOGDescriptor::HistogramNormType);
CV_PY_FROM_ENUM(HOGDescriptor::DescriptorStorageFormat);
CV_PY_TO_ENUM(HOGDescriptor::DescriptorStorageFormat);
#endif

10
modules/objdetect/src/hog.cpp
View File

@ -63,8 +63,6 @@ namespace cv
#define NTHREADS 256
enum {DESCR_FORMAT_COL_BY_COL, DESCR_FORMAT_ROW_BY_ROW};
static int numPartsWithin(int size, int part_size, int stride)
{
return (size - part_size + stride) / stride;
@ -1515,7 +1513,7 @@ static bool ocl_extract_descrs_by_cols(int win_height, int win_width, int block_
return k.run(2, globalThreads, localThreads, false);
}
static bool ocl_compute(InputArray _img, Size win_stride, std::vector<float>& _descriptors, int descr_format, Size blockSize,
static bool ocl_compute(InputArray _img, Size win_stride, std::vector<float>& _descriptors, HOGDescriptor::DescriptorStorageFormat descr_format, Size blockSize,
Size cellSize, int nbins, Size blockStride, Size winSize, float sigma, bool gammaCorrection, double L2HysThreshold, bool signedGradient)
{
Size imgSize = _img.size();
@ -1564,13 +1562,13 @@ static bool ocl_compute(InputArray _img, Size win_stride, std::vector<float>& _d
UMat descriptors(wins_per_img.area(), static_cast<int>(blocks_per_win.area() * block_hist_size), CV_32F);
switch (descr_format)
{
case DESCR_FORMAT_ROW_BY_ROW:
case HOGDescriptor::DESCR_FORMAT_ROW_BY_ROW:
if(!ocl_extract_descrs_by_rows(winSize.height, winSize.width,
blockStride.height, blockStride.width, win_stride.height, win_stride.width, effect_size.height,
effect_size.width, block_hists, descriptors, (int)block_hist_size, descr_size, descr_width))
return false;
break;
case DESCR_FORMAT_COL_BY_COL:
case HOGDescriptor::DESCR_FORMAT_COL_BY_COL:
if(!ocl_extract_descrs_by_cols(winSize.height, winSize.width,
blockStride.height, blockStride.width, win_stride.height, win_stride.width, effect_size.height, effect_size.width,
block_hists, descriptors, (int)block_hist_size, descr_size, blocks_per_win.width, blocks_per_win.height))
@ -1602,7 +1600,7 @@ void HOGDescriptor::compute(InputArray _img, std::vector<float>& descriptors,
Size paddedImgSize(imgSize.width + padding.width*2, imgSize.height + padding.height*2);
CV_OCL_RUN(_img.dims() <= 2 && _img.type() == CV_8UC1 && _img.isUMat(),
ocl_compute(_img, winStride, descriptors, DESCR_FORMAT_COL_BY_COL, blockSize,
ocl_compute(_img, winStride, descriptors, HOGDescriptor::DESCR_FORMAT_COL_BY_COL, blockSize,
cellSize, nbins, blockStride, winSize, (float)getWinSigma(), gammaCorrection, L2HysThreshold, signedGradient))
Mat img = _img.getMat();

4
modules/python/src2/cv2.cpp
View File

@ -252,7 +252,7 @@ public:
return u;
}
UMatData* allocate(int dims0, const int* sizes, int type, void* data, size_t* step, int flags, UMatUsageFlags usageFlags) const CV_OVERRIDE
UMatData* allocate(int dims0, const int* sizes, int type, void* data, size_t* step, AccessFlag flags, UMatUsageFlags usageFlags) const CV_OVERRIDE
{
if( data != 0 )
{
@ -281,7 +281,7 @@ public:
return allocate(o, dims0, sizes, type, step);
}
bool allocate(UMatData* u, int accessFlags, UMatUsageFlags usageFlags) const CV_OVERRIDE
bool allocate(UMatData* u, AccessFlag accessFlags, UMatUsageFlags usageFlags) const CV_OVERRIDE
{
return stdAllocator->allocate(u, accessFlags, usageFlags);
}

4
modules/stitching/include/opencv2/stitching/detail/matchers.hpp
View File

@ -175,13 +175,13 @@ private:
class CV_EXPORTS AKAZEFeaturesFinder : public detail::FeaturesFinder
{
public:
AKAZEFeaturesFinder(int descriptor_type = AKAZE::DESCRIPTOR_MLDB,
AKAZEFeaturesFinder(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);
KAZE::DiffusivityType diffusivity = KAZE::DIFF_PM_G2);
private:
void find(InputArray image, ImageFeatures &features) CV_OVERRIDE;

4
modules/stitching/src/matchers.cpp
View File

@ -576,13 +576,13 @@ void OrbFeaturesFinder::find(InputArray image, ImageFeatures &features)
}
}
AKAZEFeaturesFinder::AKAZEFeaturesFinder(int descriptor_type,
AKAZEFeaturesFinder::AKAZEFeaturesFinder(AKAZE::DescriptorType descriptor_type,
int descriptor_size,
int descriptor_channels,
float threshold,
int nOctaves,
int nOctaveLayers,
int diffusivity)
KAZE::DiffusivityType diffusivity)
{
akaze = AKAZE::create(descriptor_type, descriptor_size, descriptor_channels,
threshold, nOctaves, nOctaveLayers, diffusivity);

2
modules/ts/include/opencv2/ts.hpp
View File

@ -184,7 +184,7 @@ double getMaxVal(int depth);
Size randomSize(RNG& rng, double maxSizeLog);
void randomSize(RNG& rng, int minDims, int maxDims, double maxSizeLog, vector<int>& sz);
int randomType(RNG& rng, int typeMask, int minChannels, int maxChannels);
int randomType(RNG& rng, cv::_OutputArray::DepthMask typeMask, int minChannels, int maxChannels);
Mat randomMat(RNG& rng, Size size, int type, double minVal, double maxVal, bool useRoi);
Mat randomMat(RNG& rng, const vector<int>& size, int type, double minVal, double maxVal, bool useRoi);
void add(const Mat& a, double alpha, const Mat& b, double beta,

2
modules/ts/src/ts_func.cpp
View File

@ -68,7 +68,7 @@ void randomSize(RNG& rng, int minDims, int maxDims, double maxSizeLog, vector<in
}
}
int randomType(RNG& rng, int typeMask, int minChannels, int maxChannels)
int randomType(RNG& rng, _OutputArray::DepthMask typeMask, int minChannels, int maxChannels)
{
int channels = rng.uniform(minChannels, maxChannels+1);
int depth = 0;

4
modules/video/src/lkpyramid.cpp
View File

@ -704,7 +704,7 @@ int cv::buildOpticalFlowPyramid(InputArray _img, OutputArrayOfArrays pyramid, Si
CV_Assert(img.depth() == CV_8U && winSize.width > 2 && winSize.height > 2 );
int pyrstep = withDerivatives ? 2 : 1;
pyramid.create(1, (maxLevel + 1) * pyrstep, 0 /*type*/, -1, true, 0);
pyramid.create(1, (maxLevel + 1) * pyrstep, 0 /*type*/, -1, true);
int derivType = CV_MAKETYPE(DataType<cv::detail::deriv_type>::depth, img.channels() * 2);
@ -783,7 +783,7 @@ int cv::buildOpticalFlowPyramid(InputArray _img, OutputArrayOfArrays pyramid, Si
sz = Size((sz.width+1)/2, (sz.height+1)/2);
if( sz.width <= winSize.width || sz.height <= winSize.height )
{
pyramid.create(1, (level + 1) * pyrstep, 0 /*type*/, -1, true, 0);//check this
pyramid.create(1, (level + 1) * pyrstep, 0 /*type*/, -1, true);//check this
return level;
}