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object --+ | ??.instance --+ | Mat
Property 'ndarray' provides a numpy.ndarray view on the object. If you create a reference to 'ndarray', you must keep the object unchanged until your reference is deleted, or Python may crash! Alternatively, you could create a reference to 'ndarray' by using 'asndarray(obj)', where 'obj' is an instance of this class.
To create an instance of Mat that shares the same data with an ndarray instance, use: 'asMat(a), where 'a' is an ndarray instance. Similarly, to avoid a potential Python crash, you must keep the current instance unchanged until the reference is deleted.
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Inherited from Inherited from |
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AUTO_STEP = 0
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CONTINUOUS_FLAG = 16384
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MAGIC_VAL = 1124007936
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__instance_size__ = 40
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Inherited from |
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__call__( (Mat)arg1, (Range)rowRange, (Range)colRange) -> Mat : Wrapped function: operator() C++ signature : cv::Mat __call__(cv::Mat {lvalue},cv::Range,cv::Range) __call__( (Mat)arg1, (Rect)roi) -> Mat : Wrapped function: operator() C++ signature : cv::Mat __call__(cv::Mat {lvalue},cv::Rect_<int>) |
__init__( (object)arg1) -> None : C++ signature : void __init__(_object*) __init__( (object)arg1, (object)_rows, (object)_cols, (object)_type) -> None : C++ signature : void __init__(_object*,int,int,int) __init__( (object)arg1, (object)_rows, (object)_cols, (object)_type, (Scalar)_s) -> None : C++ signature : void __init__(_object*,int,int,int,cv::Scalar_<double>) __init__( (object)arg1, (Size2i)_size, (object)_type) -> None : C++ signature : void __init__(_object*,cv::Size_<int>,int) __init__( (object)arg1, (Size2i)_size, (object)_type, (Scalar)_s) -> None : C++ signature : void __init__(_object*,cv::Size_<int>,int,cv::Scalar_<double>) __init__( (object)arg1, (Mat)m) -> None : C++ signature : void __init__(_object*,cv::Mat) __init__( (object)arg1, (Mat)m, (Range)rowRange, (Range)colRange) -> None : C++ signature : void __init__(_object*,cv::Mat,cv::Range,cv::Range) __init__( (object)arg1, (Mat)m, (Rect)roi) -> None : C++ signature : void __init__(_object*,cv::Mat,cv::Rect_<int>) __init__( (object)arg1, (object)arg1) -> object : C++ signature : void* __init__(boost::python::api::object,boost::python::api::object) __init__( (object)arg1, (object)arg1, (object)arg2) -> object : C++ signature : void* __init__(boost::python::api::object,boost::python::api::object,boost::python::api::object) __init__( (object)arg1, (object)arg1, (object)arg2, (object)arg3) -> object : C++ signature : void* __init__(boost::python::api::object,boost::python::api::object,boost::python::api::object,boost::python::api::object)
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helper for pickle
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repr(x)
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adjustROI( (Mat)arg1, (object)dtop, (object)dbottom, (object)dleft, (object)dright) -> Mat : C++ signature : cv::Mat {lvalue} adjustROI(cv::Mat {lvalue},int,int,int,int) |
assign( (Mat)arg1, (Mat)m) -> Mat : Wrapped function: operator= C++ signature : cv::Mat {lvalue} assign(cv::Mat {lvalue},cv::Mat) assign( (Mat)arg1, (Scalar)s) -> Mat : Wrapped function: operator= C++ signature : cv::Mat {lvalue} assign(cv::Mat {lvalue},cv::Scalar_<double>) |
assignTo( (Mat)arg1, (Mat)m [, (object)type=-1]) -> None : C++ signature : void assignTo(cv::Mat {lvalue},cv::Mat {lvalue} [,int=-1]) |
channels( (Mat)arg1) -> int : C++ signature : int channels(cv::Mat {lvalue}) |
clone( (Mat)arg1) -> Mat : C++ signature : cv::Mat clone(cv::Mat {lvalue}) |
col( (Mat)arg1, (object)x) -> Mat : C++ signature : cv::Mat col(cv::Mat {lvalue},int) |
colRange( (Mat)arg1, (object)startcol, (object)endcol) -> Mat : C++ signature : cv::Mat colRange(cv::Mat {lvalue},int,int) colRange( (Mat)arg1, (Range)r) -> Mat : C++ signature : cv::Mat colRange(cv::Mat {lvalue},cv::Range) |
convertTo( (Mat)arg1, (Mat)m, (object)rtype [, (object)alpha=1 [, (object)beta=0]]) -> None : C++ signature : void convertTo(cv::Mat {lvalue},cv::Mat {lvalue},int [,double=1 [,double=0]]) |
copyTo( (Mat)arg1, (Mat)m) -> None : C++ signature : void copyTo(cv::Mat {lvalue},cv::Mat {lvalue}) copyTo( (Mat)arg1, (Mat)m, (Mat)mask) -> None : C++ signature : void copyTo(cv::Mat {lvalue},cv::Mat {lvalue},cv::Mat) |
create( (Mat)arg1, (object)_rows, (object)_cols, (object)_type) -> None : C++ signature : void create(cv::Mat {lvalue},int,int,int) create( (Mat)arg1, (Size2i)_size, (object)_type) -> None : C++ signature : void create(cv::Mat {lvalue},cv::Size_<int>,int) |
cross( (Mat)arg1, (Mat)m) -> Mat : C++ signature : cv::Mat cross(cv::Mat {lvalue},cv::Mat) |
depth( (Mat)arg1) -> int : C++ signature : int depth(cv::Mat {lvalue}) |
diag( (Mat)arg1 [, (object)d=0]) -> Mat : C++ signature : cv::Mat diag(cv::Mat {lvalue} [,int=0]) diag( (Mat)d) -> Mat : C++ signature : cv::Mat diag(cv::Mat) |
dot( (Mat)arg1, (Mat)m) -> float : C++ signature : double dot(cv::Mat {lvalue},cv::Mat) |
elemSize( (Mat)arg1) -> int : C++ signature : unsigned int elemSize(cv::Mat {lvalue}) |
elemSize1( (Mat)arg1) -> int : C++ signature : unsigned int elemSize1(cv::Mat {lvalue}) |
empty( (Mat)arg1) -> bool : C++ signature : bool empty(cv::Mat {lvalue}) |
Converts a PIL.Image into a Mat Right now, PyOpenCV can convert PIL.Images of band ('L'), ('I'), ('F'), ('R', 'G', 'B'), or ('R', 'G', 'B', 'A'). Whether the data array is copied from PIL.Image to IplImage or shared between the two images depends on how PIL converts the PIL.Image's data into a string (i.e. via function PIL.Image.tostring()). |
isContinuous( (Mat)arg1) -> bool : C++ signature : bool isContinuous(cv::Mat {lvalue}) |
locateROI( (Mat)arg1, (Size2i)wholeSize, (Point2i)ofs) -> None : C++ signature : void locateROI(cv::Mat {lvalue},cv::Size_<int> {lvalue},cv::Point_<int> {lvalue}) |
reshape( (Mat)arg1, (object)_cn [, (object)_rows=0]) -> Mat : C++ signature : cv::Mat reshape(cv::Mat {lvalue},int [,int=0]) |
row( (Mat)arg1, (object)y) -> Mat : C++ signature : cv::Mat row(cv::Mat {lvalue},int) |
rowRange( (Mat)arg1, (object)startrow, (object)endrow) -> Mat : C++ signature : cv::Mat rowRange(cv::Mat {lvalue},int,int) rowRange( (Mat)arg1, (Range)r) -> Mat : C++ signature : cv::Mat rowRange(cv::Mat {lvalue},cv::Range) |
setTo( (Mat)arg1, (Scalar)s [, (Mat)mask=Mat()]) -> Mat : C++ signature : cv::Mat {lvalue} setTo(cv::Mat {lvalue},cv::Scalar_<double> [,cv::Mat=Mat()]) |
size( (Mat)arg1) -> Size2i : C++ signature : cv::Size_<int> size(cv::Mat {lvalue}) |
step1( (Mat)arg1) -> int : C++ signature : unsigned int step1(cv::Mat {lvalue}) |
Converts a Mat into a PIL Image Right now, PyOpenCV can convert 1-channel (uint8|int32|float32) Mats or uint8 (BGR|BGRA) Mats. Whether the image's data array is shared or copied to PIL.Image depends on how PIL decodes the array (i.e. via function PIL.Image.fromstring()). |
type( (Mat)arg1) -> int : C++ signature : int type(cv::Mat {lvalue}) |
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cols
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data
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flags
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ndarray
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rows
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step
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this
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