2023-05-23 11:49:52 +08:00

12425 lines
359 KiB
Python

# This file was automatically generated by SWIG (http://www.swig.org).
# Version 4.0.2
#
# Do not make changes to this file unless you know what you are doing--modify
# the SWIG interface file instead.
from sys import version_info as _swig_python_version_info
if _swig_python_version_info < (2, 7, 0):
raise RuntimeError("Python 2.7 or later required")
# Import the low-level C/C++ module
if __package__ or "." in __name__:
from . import _AHT
else:
import _AHT
try:
import builtins as __builtin__
except ImportError:
import __builtin__
def _swig_repr(self):
try:
strthis = "proxy of " + self.this.__repr__()
except __builtin__.Exception:
strthis = ""
return "<%s.%s; %s >" % (self.__class__.__module__, self.__class__.__name__, strthis,)
def _swig_setattr_nondynamic_instance_variable(set):
def set_instance_attr(self, name, value):
if name == "thisown":
self.this.own(value)
elif name == "this":
set(self, name, value)
elif hasattr(self, name) and isinstance(getattr(type(self), name), property):
set(self, name, value)
else:
raise AttributeError("You cannot add instance attributes to %s" % self)
return set_instance_attr
def _swig_setattr_nondynamic_class_variable(set):
def set_class_attr(cls, name, value):
if hasattr(cls, name) and not isinstance(getattr(cls, name), property):
set(cls, name, value)
else:
raise AttributeError("You cannot add class attributes to %s" % cls)
return set_class_attr
def _swig_add_metaclass(metaclass):
"""Class decorator for adding a metaclass to a SWIG wrapped class - a slimmed down version of six.add_metaclass"""
def wrapper(cls):
return metaclass(cls.__name__, cls.__bases__, cls.__dict__.copy())
return wrapper
class _SwigNonDynamicMeta(type):
"""Meta class to enforce nondynamic attributes (no new attributes) for a class"""
__setattr__ = _swig_setattr_nondynamic_class_variable(type.__setattr__)
import sys as _sys
if _sys.byteorder == 'little':
_cv_numpy_endianess = '<'
else:
_cv_numpy_endianess = '>'
_cv_numpy_typestr_map = {}
_cv_numpy_bla = {}
CV_VERSION_MAJOR = _AHT.CV_VERSION_MAJOR
CV_VERSION_MINOR = _AHT.CV_VERSION_MINOR
CV_VERSION_REVISION = _AHT.CV_VERSION_REVISION
CV_VERSION_STATUS = _AHT.CV_VERSION_STATUS
CV_VERSION = _AHT.CV_VERSION
CV_MAJOR_VERSION = _AHT.CV_MAJOR_VERSION
CV_MINOR_VERSION = _AHT.CV_MINOR_VERSION
CV_SUBMINOR_VERSION = _AHT.CV_SUBMINOR_VERSION
class DataType_bool(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT.DataType_bool_generic_type
channels = _AHT.DataType_bool_channels
fmt = _AHT.DataType_bool_fmt
def __init__(self):
_AHT.DataType_bool_swiginit(self, _AHT.new_DataType_bool())
__swig_destroy__ = _AHT.delete_DataType_bool
# Register DataType_bool in _AHT:
_AHT.DataType_bool_swigregister(DataType_bool)
class DataType_uchar(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT.DataType_uchar_generic_type
channels = _AHT.DataType_uchar_channels
fmt = _AHT.DataType_uchar_fmt
def __init__(self):
_AHT.DataType_uchar_swiginit(self, _AHT.new_DataType_uchar())
__swig_destroy__ = _AHT.delete_DataType_uchar
# Register DataType_uchar in _AHT:
_AHT.DataType_uchar_swigregister(DataType_uchar)
class DataType_schar(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT.DataType_schar_generic_type
channels = _AHT.DataType_schar_channels
fmt = _AHT.DataType_schar_fmt
def __init__(self):
_AHT.DataType_schar_swiginit(self, _AHT.new_DataType_schar())
__swig_destroy__ = _AHT.delete_DataType_schar
# Register DataType_schar in _AHT:
_AHT.DataType_schar_swigregister(DataType_schar)
class DataType_char(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT.DataType_char_generic_type
channels = _AHT.DataType_char_channels
fmt = _AHT.DataType_char_fmt
def __init__(self):
_AHT.DataType_char_swiginit(self, _AHT.new_DataType_char())
__swig_destroy__ = _AHT.delete_DataType_char
# Register DataType_char in _AHT:
_AHT.DataType_char_swigregister(DataType_char)
class DataType_ushort(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT.DataType_ushort_generic_type
channels = _AHT.DataType_ushort_channels
fmt = _AHT.DataType_ushort_fmt
def __init__(self):
_AHT.DataType_ushort_swiginit(self, _AHT.new_DataType_ushort())
__swig_destroy__ = _AHT.delete_DataType_ushort
# Register DataType_ushort in _AHT:
_AHT.DataType_ushort_swigregister(DataType_ushort)
class DataType_short(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT.DataType_short_generic_type
channels = _AHT.DataType_short_channels
fmt = _AHT.DataType_short_fmt
def __init__(self):
_AHT.DataType_short_swiginit(self, _AHT.new_DataType_short())
__swig_destroy__ = _AHT.delete_DataType_short
# Register DataType_short in _AHT:
_AHT.DataType_short_swigregister(DataType_short)
class DataType_int(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT.DataType_int_generic_type
channels = _AHT.DataType_int_channels
fmt = _AHT.DataType_int_fmt
def __init__(self):
_AHT.DataType_int_swiginit(self, _AHT.new_DataType_int())
__swig_destroy__ = _AHT.delete_DataType_int
# Register DataType_int in _AHT:
_AHT.DataType_int_swigregister(DataType_int)
class DataType_float(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT.DataType_float_generic_type
channels = _AHT.DataType_float_channels
fmt = _AHT.DataType_float_fmt
def __init__(self):
_AHT.DataType_float_swiginit(self, _AHT.new_DataType_float())
__swig_destroy__ = _AHT.delete_DataType_float
# Register DataType_float in _AHT:
_AHT.DataType_float_swigregister(DataType_float)
class DataType_double(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT.DataType_double_generic_type
channels = _AHT.DataType_double_channels
fmt = _AHT.DataType_double_fmt
def __init__(self):
_AHT.DataType_double_swiginit(self, _AHT.new_DataType_double())
__swig_destroy__ = _AHT.delete_DataType_double
# Register DataType_double in _AHT:
_AHT.DataType_double_swigregister(DataType_double)
class Range(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self, *args):
_AHT.Range_swiginit(self, _AHT.new_Range(*args))
def size(self):
return _AHT.Range_size(self)
def empty(self):
return _AHT.Range_empty(self)
@staticmethod
def all():
return _AHT.Range_all()
start = property(_AHT.Range_start_get, _AHT.Range_start_set)
end = property(_AHT.Range_end_get, _AHT.Range_end_set)
__swig_destroy__ = _AHT.delete_Range
# Register Range in _AHT:
_AHT.Range_swigregister(Range)
def Range_all():
return _AHT.Range_all()
class SwigPyIterator(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
def __init__(self, *args, **kwargs):
raise AttributeError("No constructor defined - class is abstract")
__repr__ = _swig_repr
__swig_destroy__ = _AHT.delete_SwigPyIterator
def value(self):
return _AHT.SwigPyIterator_value(self)
def incr(self, n=1):
return _AHT.SwigPyIterator_incr(self, n)
def decr(self, n=1):
return _AHT.SwigPyIterator_decr(self, n)
def distance(self, x):
return _AHT.SwigPyIterator_distance(self, x)
def equal(self, x):
return _AHT.SwigPyIterator_equal(self, x)
def copy(self):
return _AHT.SwigPyIterator_copy(self)
def next(self):
return _AHT.SwigPyIterator_next(self)
def __next__(self):
return _AHT.SwigPyIterator___next__(self)
def previous(self):
return _AHT.SwigPyIterator_previous(self)
def advance(self, n):
return _AHT.SwigPyIterator_advance(self, n)
def __eq__(self, x):
return _AHT.SwigPyIterator___eq__(self, x)
def __ne__(self, x):
return _AHT.SwigPyIterator___ne__(self, x)
def __iadd__(self, n):
return _AHT.SwigPyIterator___iadd__(self, n)
def __isub__(self, n):
return _AHT.SwigPyIterator___isub__(self, n)
def __add__(self, n):
return _AHT.SwigPyIterator___add__(self, n)
def __sub__(self, *args):
return _AHT.SwigPyIterator___sub__(self, *args)
def __iter__(self):
return self
# Register SwigPyIterator in _AHT:
_AHT.SwigPyIterator_swigregister(SwigPyIterator)
_array_map = {}
class Matx_AddOp(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self):
_AHT.Matx_AddOp_swiginit(self, _AHT.new_Matx_AddOp())
__swig_destroy__ = _AHT.delete_Matx_AddOp
# Register Matx_AddOp in _AHT:
_AHT.Matx_AddOp_swigregister(Matx_AddOp)
class Matx_SubOp(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self):
_AHT.Matx_SubOp_swiginit(self, _AHT.new_Matx_SubOp())
__swig_destroy__ = _AHT.delete_Matx_SubOp
# Register Matx_SubOp in _AHT:
_AHT.Matx_SubOp_swigregister(Matx_SubOp)
class Matx_ScaleOp(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self):
_AHT.Matx_ScaleOp_swiginit(self, _AHT.new_Matx_ScaleOp())
__swig_destroy__ = _AHT.delete_Matx_ScaleOp
# Register Matx_ScaleOp in _AHT:
_AHT.Matx_ScaleOp_swigregister(Matx_ScaleOp)
class Matx_MulOp(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self):
_AHT.Matx_MulOp_swiginit(self, _AHT.new_Matx_MulOp())
__swig_destroy__ = _AHT.delete_Matx_MulOp
# Register Matx_MulOp in _AHT:
_AHT.Matx_MulOp_swigregister(Matx_MulOp)
class Matx_DivOp(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self):
_AHT.Matx_DivOp_swiginit(self, _AHT.new_Matx_DivOp())
__swig_destroy__ = _AHT.delete_Matx_DivOp
# Register Matx_DivOp in _AHT:
_AHT.Matx_DivOp_swigregister(Matx_DivOp)
class Matx_MatMulOp(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self):
_AHT.Matx_MatMulOp_swiginit(self, _AHT.new_Matx_MatMulOp())
__swig_destroy__ = _AHT.delete_Matx_MatMulOp
# Register Matx_MatMulOp in _AHT:
_AHT.Matx_MatMulOp_swigregister(Matx_MatMulOp)
class Matx_TOp(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self):
_AHT.Matx_TOp_swiginit(self, _AHT.new_Matx_TOp())
__swig_destroy__ = _AHT.delete_Matx_TOp
# Register Matx_TOp in _AHT:
_AHT.Matx_TOp_swigregister(Matx_TOp)
class Mat(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
__swig_destroy__ = _AHT.delete_Mat
def row(self, y):
return _AHT.Mat_row(self, y)
def col(self, x):
return _AHT.Mat_col(self, x)
def rowRange(self, *args):
return _AHT.Mat_rowRange(self, *args)
def colRange(self, *args):
return _AHT.Mat_colRange(self, *args)
def diag(self, d=0):
return _AHT.Mat_diag(self, d)
def clone(self):
return _AHT.Mat_clone(self)
def assignTo(self, m, type=-1):
return _AHT.Mat_assignTo(self, m, type)
def reshape(self, *args):
return _AHT.Mat_reshape(self, *args)
def create(self, *args):
return _AHT.Mat_create(self, *args)
def addref(self):
return _AHT.Mat_addref(self)
def release(self):
return _AHT.Mat_release(self)
def deallocate(self):
return _AHT.Mat_deallocate(self)
def copySize(self, m):
return _AHT.Mat_copySize(self, m)
def reserve(self, sz):
return _AHT.Mat_reserve(self, sz)
def resize(self, *args):
return _AHT.Mat_resize(self, *args)
def push_back_(self, elem):
return _AHT.Mat_push_back_(self, elem)
def push_back(self, m):
return _AHT.Mat_push_back(self, m)
def pop_back(self, nelems=1):
return _AHT.Mat_pop_back(self, nelems)
def locateROI(self, wholeSize, ofs):
return _AHT.Mat_locateROI(self, wholeSize, ofs)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT.Mat_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT.Mat___call__(self, *args)
def isContinuous(self):
return _AHT.Mat_isContinuous(self)
def isSubmatrix(self):
return _AHT.Mat_isSubmatrix(self)
def elemSize(self):
return _AHT.Mat_elemSize(self)
def elemSize1(self):
return _AHT.Mat_elemSize1(self)
def type(self):
return _AHT.Mat_type(self)
def depth(self):
return _AHT.Mat_depth(self)
def channels(self):
return _AHT.Mat_channels(self)
def step1(self, i=0):
return _AHT.Mat_step1(self, i)
def empty(self):
return _AHT.Mat_empty(self)
def total(self):
return _AHT.Mat_total(self)
def checkVector(self, elemChannels, depth=-1, requireContinuous=True):
return _AHT.Mat_checkVector(self, elemChannels, depth, requireContinuous)
def ptr(self, *args):
return _AHT.Mat_ptr(self, *args)
MAGIC_VAL = _AHT.Mat_MAGIC_VAL
AUTO_STEP = _AHT.Mat_AUTO_STEP
CONTINUOUS_FLAG = _AHT.Mat_CONTINUOUS_FLAG
SUBMATRIX_FLAG = _AHT.Mat_SUBMATRIX_FLAG
MAGIC_MASK = _AHT.Mat_MAGIC_MASK
TYPE_MASK = _AHT.Mat_TYPE_MASK
DEPTH_MASK = _AHT.Mat_DEPTH_MASK
flags = property(_AHT.Mat_flags_get, _AHT.Mat_flags_set)
dims = property(_AHT.Mat_dims_get, _AHT.Mat_dims_set)
rows = property(_AHT.Mat_rows_get, _AHT.Mat_rows_set)
cols = property(_AHT.Mat_cols_get, _AHT.Mat_cols_set)
data = property(_AHT.Mat_data_get, _AHT.Mat_data_set)
datastart = property(_AHT.Mat_datastart_get, _AHT.Mat_datastart_set)
dataend = property(_AHT.Mat_dataend_get, _AHT.Mat_dataend_set)
datalimit = property(_AHT.Mat_datalimit_get, _AHT.Mat_datalimit_set)
def __init__(self, *args):
_AHT.Mat_swiginit(self, _AHT.new_Mat(*args))
def _typestr(self):
typestr = _depthToDtype(self.depth())
if typestr[-1] == '1':
typestr = '|' + typestr
else:
typestr = _cv_numpy_endianess + typestr
return typestr
@classmethod
def __get_channels(cls, array):
if len(array.shape) == 3:
n_channel = array.shape[2]
if n_channel == 1:
raise ValueError("{} expects an one channel numpy ndarray be 2-dimensional.".format(cls))
elif len(array.shape) == 2:
n_channel = 1
else:
raise ValueError("{} supports only 2 or 3-dimensional numpy ndarray.".format(cls))
return n_channel
def __getattribute__(self, name):
if name == "__array_interface__":
n_channels = self.channels()
if n_channels == 1:
shape = (self.rows, self.cols)
else:
shape = (self.rows, self.cols, n_channels)
return {"shape": shape,
"typestr": self._typestr(),
"data": (int(self.data), False)}
else:
return object.__getattribute__(self, name)
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
dtype = array.__array_interface__['typestr']
dtype = dtype[1:]
n_channel = cls.__get_channels(array)
new_mat = Mat(array.shape[0],
array.shape[1],
_toCvType(dtype, n_channel),
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT.Mat___str__(self)
# Register Mat in _AHT:
_AHT.Mat_swigregister(Mat)
class _cv_numpy_sizeof_uint8_t(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_uint8_t_value
def __init__(self):
_AHT._cv_numpy_sizeof_uint8_t_swiginit(self, _AHT.new__cv_numpy_sizeof_uint8_t())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_uint8_t
# Register _cv_numpy_sizeof_uint8_t in _AHT:
_AHT._cv_numpy_sizeof_uint8_t_swigregister(_cv_numpy_sizeof_uint8_t)
if _cv_numpy_sizeof_uint8_t.value == 1:
_cv_numpy_typestr_map["uint8_t"] = "|" +"u" + "1"
else:
_cv_numpy_typestr_map["uint8_t"] = _cv_numpy_endianess +"u" + str(_cv_numpy_sizeof_uint8_t.value)
class uint8_tArray(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def iterator(self):
return _AHT.uint8_tArray_iterator(self)
def __iter__(self):
return self.iterator()
def __nonzero__(self):
return _AHT.uint8_tArray___nonzero__(self)
def __bool__(self):
return _AHT.uint8_tArray___bool__(self)
def __len__(self):
return _AHT.uint8_tArray___len__(self)
def __getslice__(self, i, j):
return _AHT.uint8_tArray___getslice__(self, i, j)
def __setslice__(self, *args):
return _AHT.uint8_tArray___setslice__(self, *args)
def __delslice__(self, i, j):
return _AHT.uint8_tArray___delslice__(self, i, j)
def __delitem__(self, *args):
return _AHT.uint8_tArray___delitem__(self, *args)
def __getitem__(self, *args):
return _AHT.uint8_tArray___getitem__(self, *args)
def __setitem__(self, *args):
return _AHT.uint8_tArray___setitem__(self, *args)
def pop(self):
return _AHT.uint8_tArray_pop(self)
def append(self, x):
return _AHT.uint8_tArray_append(self, x)
def empty(self):
return _AHT.uint8_tArray_empty(self)
def size(self):
return _AHT.uint8_tArray_size(self)
def swap(self, v):
return _AHT.uint8_tArray_swap(self, v)
def begin(self):
return _AHT.uint8_tArray_begin(self)
def end(self):
return _AHT.uint8_tArray_end(self)
def rbegin(self):
return _AHT.uint8_tArray_rbegin(self)
def rend(self):
return _AHT.uint8_tArray_rend(self)
def clear(self):
return _AHT.uint8_tArray_clear(self)
def get_allocator(self):
return _AHT.uint8_tArray_get_allocator(self)
def pop_back(self):
return _AHT.uint8_tArray_pop_back(self)
def erase(self, *args):
return _AHT.uint8_tArray_erase(self, *args)
def __init__(self, *args):
_AHT.uint8_tArray_swiginit(self, _AHT.new_uint8_tArray(*args))
def push_back(self, x):
return _AHT.uint8_tArray_push_back(self, x)
def front(self):
return _AHT.uint8_tArray_front(self)
def back(self):
return _AHT.uint8_tArray_back(self)
def assign(self, n, x):
return _AHT.uint8_tArray_assign(self, n, x)
def resize(self, *args):
return _AHT.uint8_tArray_resize(self, *args)
def insert(self, *args):
return _AHT.uint8_tArray_insert(self, *args)
def reserve(self, n):
return _AHT.uint8_tArray_reserve(self, n)
def capacity(self):
return _AHT.uint8_tArray_capacity(self)
__swig_destroy__ = _AHT.delete_uint8_tArray
# Register uint8_tArray in _AHT:
_AHT.uint8_tArray_swigregister(uint8_tArray)
_array_map["uint8_t"] =uint8_tArray
class _Matx_uint8_t_2_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_uint8_t_2_1_rows
cols = _AHT._Matx_uint8_t_2_1_cols
channels = _AHT._Matx_uint8_t_2_1_channels
shortdim = _AHT._Matx_uint8_t_2_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_uint8_t_2_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_uint8_t_2_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_uint8_t_2_1_ones()
@staticmethod
def eye():
return _AHT._Matx_uint8_t_2_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_uint8_t_2_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_uint8_t_2_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_uint8_t_2_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_uint8_t_2_1_ddot(self, v)
def t(self):
return _AHT._Matx_uint8_t_2_1_t(self)
def mul(self, a):
return _AHT._Matx_uint8_t_2_1_mul(self, a)
def div(self, a):
return _AHT._Matx_uint8_t_2_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_uint8_t_2_1___call__(self, i, j)
val = property(_AHT._Matx_uint8_t_2_1_val_get, _AHT._Matx_uint8_t_2_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_uint8_t_2_1_swiginit(self, _AHT.new__Matx_uint8_t_2_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_uint8_t_2_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_uint8_t_2_1
# Register _Matx_uint8_t_2_1 in _AHT:
_AHT._Matx_uint8_t_2_1_swigregister(_Matx_uint8_t_2_1)
def _Matx_uint8_t_2_1_all(alpha):
return _AHT._Matx_uint8_t_2_1_all(alpha)
def _Matx_uint8_t_2_1_zeros():
return _AHT._Matx_uint8_t_2_1_zeros()
def _Matx_uint8_t_2_1_ones():
return _AHT._Matx_uint8_t_2_1_ones()
def _Matx_uint8_t_2_1_eye():
return _AHT._Matx_uint8_t_2_1_eye()
def _Matx_uint8_t_2_1_randu(a, b):
return _AHT._Matx_uint8_t_2_1_randu(a, b)
def _Matx_uint8_t_2_1_randn(a, b):
return _AHT._Matx_uint8_t_2_1_randn(a, b)
Matx21b = _Matx_uint8_t_2_1
class _Vec_uint8_t_2(_Matx_uint8_t_2_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_uint8_t_2_channels
@staticmethod
def all(alpha):
return _AHT._Vec_uint8_t_2_all(alpha)
def mul(self, v):
return _AHT._Vec_uint8_t_2_mul(self, v)
def __call__(self, i):
return _AHT._Vec_uint8_t_2___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_uint8_t_2_swiginit(self, _AHT.new__Vec_uint8_t_2(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_uint8_t_2___str__(self)
__swig_destroy__ = _AHT.delete__Vec_uint8_t_2
# Register _Vec_uint8_t_2 in _AHT:
_AHT._Vec_uint8_t_2_swigregister(_Vec_uint8_t_2)
def _Vec_uint8_t_2_all(alpha):
return _AHT._Vec_uint8_t_2_all(alpha)
class _DataType_Vec_uint8_t_2(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_uint8_t_2_generic_type
channels = _AHT._DataType_Vec_uint8_t_2_channels
fmt = _AHT._DataType_Vec_uint8_t_2_fmt
def __init__(self):
_AHT._DataType_Vec_uint8_t_2_swiginit(self, _AHT.new__DataType_Vec_uint8_t_2())
__swig_destroy__ = _AHT.delete__DataType_Vec_uint8_t_2
# Register _DataType_Vec_uint8_t_2 in _AHT:
_AHT._DataType_Vec_uint8_t_2_swigregister(_DataType_Vec_uint8_t_2)
Vec2b = _Vec_uint8_t_2
DataType_Vec2b = _DataType_Vec_uint8_t_2
class _Matx_uint8_t_3_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_uint8_t_3_1_rows
cols = _AHT._Matx_uint8_t_3_1_cols
channels = _AHT._Matx_uint8_t_3_1_channels
shortdim = _AHT._Matx_uint8_t_3_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_uint8_t_3_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_uint8_t_3_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_uint8_t_3_1_ones()
@staticmethod
def eye():
return _AHT._Matx_uint8_t_3_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_uint8_t_3_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_uint8_t_3_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_uint8_t_3_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_uint8_t_3_1_ddot(self, v)
def t(self):
return _AHT._Matx_uint8_t_3_1_t(self)
def mul(self, a):
return _AHT._Matx_uint8_t_3_1_mul(self, a)
def div(self, a):
return _AHT._Matx_uint8_t_3_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_uint8_t_3_1___call__(self, i, j)
val = property(_AHT._Matx_uint8_t_3_1_val_get, _AHT._Matx_uint8_t_3_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_uint8_t_3_1_swiginit(self, _AHT.new__Matx_uint8_t_3_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_uint8_t_3_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_uint8_t_3_1
# Register _Matx_uint8_t_3_1 in _AHT:
_AHT._Matx_uint8_t_3_1_swigregister(_Matx_uint8_t_3_1)
def _Matx_uint8_t_3_1_all(alpha):
return _AHT._Matx_uint8_t_3_1_all(alpha)
def _Matx_uint8_t_3_1_zeros():
return _AHT._Matx_uint8_t_3_1_zeros()
def _Matx_uint8_t_3_1_ones():
return _AHT._Matx_uint8_t_3_1_ones()
def _Matx_uint8_t_3_1_eye():
return _AHT._Matx_uint8_t_3_1_eye()
def _Matx_uint8_t_3_1_randu(a, b):
return _AHT._Matx_uint8_t_3_1_randu(a, b)
def _Matx_uint8_t_3_1_randn(a, b):
return _AHT._Matx_uint8_t_3_1_randn(a, b)
Matx31b = _Matx_uint8_t_3_1
class _Vec_uint8_t_3(_Matx_uint8_t_3_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_uint8_t_3_channels
@staticmethod
def all(alpha):
return _AHT._Vec_uint8_t_3_all(alpha)
def mul(self, v):
return _AHT._Vec_uint8_t_3_mul(self, v)
def __call__(self, i):
return _AHT._Vec_uint8_t_3___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_uint8_t_3_swiginit(self, _AHT.new__Vec_uint8_t_3(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_uint8_t_3___str__(self)
__swig_destroy__ = _AHT.delete__Vec_uint8_t_3
# Register _Vec_uint8_t_3 in _AHT:
_AHT._Vec_uint8_t_3_swigregister(_Vec_uint8_t_3)
def _Vec_uint8_t_3_all(alpha):
return _AHT._Vec_uint8_t_3_all(alpha)
class _DataType_Vec_uint8_t_3(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_uint8_t_3_generic_type
channels = _AHT._DataType_Vec_uint8_t_3_channels
fmt = _AHT._DataType_Vec_uint8_t_3_fmt
def __init__(self):
_AHT._DataType_Vec_uint8_t_3_swiginit(self, _AHT.new__DataType_Vec_uint8_t_3())
__swig_destroy__ = _AHT.delete__DataType_Vec_uint8_t_3
# Register _DataType_Vec_uint8_t_3 in _AHT:
_AHT._DataType_Vec_uint8_t_3_swigregister(_DataType_Vec_uint8_t_3)
Vec3b = _Vec_uint8_t_3
DataType_Vec3b = _DataType_Vec_uint8_t_3
class _Matx_uint8_t_4_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_uint8_t_4_1_rows
cols = _AHT._Matx_uint8_t_4_1_cols
channels = _AHT._Matx_uint8_t_4_1_channels
shortdim = _AHT._Matx_uint8_t_4_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_uint8_t_4_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_uint8_t_4_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_uint8_t_4_1_ones()
@staticmethod
def eye():
return _AHT._Matx_uint8_t_4_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_uint8_t_4_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_uint8_t_4_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_uint8_t_4_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_uint8_t_4_1_ddot(self, v)
def t(self):
return _AHT._Matx_uint8_t_4_1_t(self)
def mul(self, a):
return _AHT._Matx_uint8_t_4_1_mul(self, a)
def div(self, a):
return _AHT._Matx_uint8_t_4_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_uint8_t_4_1___call__(self, i, j)
val = property(_AHT._Matx_uint8_t_4_1_val_get, _AHT._Matx_uint8_t_4_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_uint8_t_4_1_swiginit(self, _AHT.new__Matx_uint8_t_4_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_uint8_t_4_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_uint8_t_4_1
# Register _Matx_uint8_t_4_1 in _AHT:
_AHT._Matx_uint8_t_4_1_swigregister(_Matx_uint8_t_4_1)
def _Matx_uint8_t_4_1_all(alpha):
return _AHT._Matx_uint8_t_4_1_all(alpha)
def _Matx_uint8_t_4_1_zeros():
return _AHT._Matx_uint8_t_4_1_zeros()
def _Matx_uint8_t_4_1_ones():
return _AHT._Matx_uint8_t_4_1_ones()
def _Matx_uint8_t_4_1_eye():
return _AHT._Matx_uint8_t_4_1_eye()
def _Matx_uint8_t_4_1_randu(a, b):
return _AHT._Matx_uint8_t_4_1_randu(a, b)
def _Matx_uint8_t_4_1_randn(a, b):
return _AHT._Matx_uint8_t_4_1_randn(a, b)
Matx41b = _Matx_uint8_t_4_1
class _Vec_uint8_t_4(_Matx_uint8_t_4_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_uint8_t_4_channels
@staticmethod
def all(alpha):
return _AHT._Vec_uint8_t_4_all(alpha)
def mul(self, v):
return _AHT._Vec_uint8_t_4_mul(self, v)
def __call__(self, i):
return _AHT._Vec_uint8_t_4___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_uint8_t_4_swiginit(self, _AHT.new__Vec_uint8_t_4(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_uint8_t_4___str__(self)
__swig_destroy__ = _AHT.delete__Vec_uint8_t_4
# Register _Vec_uint8_t_4 in _AHT:
_AHT._Vec_uint8_t_4_swigregister(_Vec_uint8_t_4)
def _Vec_uint8_t_4_all(alpha):
return _AHT._Vec_uint8_t_4_all(alpha)
class _DataType_Vec_uint8_t_4(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_uint8_t_4_generic_type
channels = _AHT._DataType_Vec_uint8_t_4_channels
fmt = _AHT._DataType_Vec_uint8_t_4_fmt
def __init__(self):
_AHT._DataType_Vec_uint8_t_4_swiginit(self, _AHT.new__DataType_Vec_uint8_t_4())
__swig_destroy__ = _AHT.delete__DataType_Vec_uint8_t_4
# Register _DataType_Vec_uint8_t_4 in _AHT:
_AHT._DataType_Vec_uint8_t_4_swigregister(_DataType_Vec_uint8_t_4)
Vec4b = _Vec_uint8_t_4
DataType_Vec4b = _DataType_Vec_uint8_t_4
class _cv_numpy_sizeof_short(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_short_value
def __init__(self):
_AHT._cv_numpy_sizeof_short_swiginit(self, _AHT.new__cv_numpy_sizeof_short())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_short
# Register _cv_numpy_sizeof_short in _AHT:
_AHT._cv_numpy_sizeof_short_swigregister(_cv_numpy_sizeof_short)
if _cv_numpy_sizeof_short.value == 1:
_cv_numpy_typestr_map["short"] = "|" +"i" + "1"
else:
_cv_numpy_typestr_map["short"] = _cv_numpy_endianess +"i" + str(_cv_numpy_sizeof_short.value)
class shortArray(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def iterator(self):
return _AHT.shortArray_iterator(self)
def __iter__(self):
return self.iterator()
def __nonzero__(self):
return _AHT.shortArray___nonzero__(self)
def __bool__(self):
return _AHT.shortArray___bool__(self)
def __len__(self):
return _AHT.shortArray___len__(self)
def __getslice__(self, i, j):
return _AHT.shortArray___getslice__(self, i, j)
def __setslice__(self, *args):
return _AHT.shortArray___setslice__(self, *args)
def __delslice__(self, i, j):
return _AHT.shortArray___delslice__(self, i, j)
def __delitem__(self, *args):
return _AHT.shortArray___delitem__(self, *args)
def __getitem__(self, *args):
return _AHT.shortArray___getitem__(self, *args)
def __setitem__(self, *args):
return _AHT.shortArray___setitem__(self, *args)
def pop(self):
return _AHT.shortArray_pop(self)
def append(self, x):
return _AHT.shortArray_append(self, x)
def empty(self):
return _AHT.shortArray_empty(self)
def size(self):
return _AHT.shortArray_size(self)
def swap(self, v):
return _AHT.shortArray_swap(self, v)
def begin(self):
return _AHT.shortArray_begin(self)
def end(self):
return _AHT.shortArray_end(self)
def rbegin(self):
return _AHT.shortArray_rbegin(self)
def rend(self):
return _AHT.shortArray_rend(self)
def clear(self):
return _AHT.shortArray_clear(self)
def get_allocator(self):
return _AHT.shortArray_get_allocator(self)
def pop_back(self):
return _AHT.shortArray_pop_back(self)
def erase(self, *args):
return _AHT.shortArray_erase(self, *args)
def __init__(self, *args):
_AHT.shortArray_swiginit(self, _AHT.new_shortArray(*args))
def push_back(self, x):
return _AHT.shortArray_push_back(self, x)
def front(self):
return _AHT.shortArray_front(self)
def back(self):
return _AHT.shortArray_back(self)
def assign(self, n, x):
return _AHT.shortArray_assign(self, n, x)
def resize(self, *args):
return _AHT.shortArray_resize(self, *args)
def insert(self, *args):
return _AHT.shortArray_insert(self, *args)
def reserve(self, n):
return _AHT.shortArray_reserve(self, n)
def capacity(self):
return _AHT.shortArray_capacity(self)
__swig_destroy__ = _AHT.delete_shortArray
# Register shortArray in _AHT:
_AHT.shortArray_swigregister(shortArray)
_array_map["short"] =shortArray
class _Matx_short_2_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_short_2_1_rows
cols = _AHT._Matx_short_2_1_cols
channels = _AHT._Matx_short_2_1_channels
shortdim = _AHT._Matx_short_2_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_short_2_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_short_2_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_short_2_1_ones()
@staticmethod
def eye():
return _AHT._Matx_short_2_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_short_2_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_short_2_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_short_2_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_short_2_1_ddot(self, v)
def t(self):
return _AHT._Matx_short_2_1_t(self)
def mul(self, a):
return _AHT._Matx_short_2_1_mul(self, a)
def div(self, a):
return _AHT._Matx_short_2_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_short_2_1___call__(self, i, j)
val = property(_AHT._Matx_short_2_1_val_get, _AHT._Matx_short_2_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_short_2_1_swiginit(self, _AHT.new__Matx_short_2_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_short_2_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_short_2_1
# Register _Matx_short_2_1 in _AHT:
_AHT._Matx_short_2_1_swigregister(_Matx_short_2_1)
def _Matx_short_2_1_all(alpha):
return _AHT._Matx_short_2_1_all(alpha)
def _Matx_short_2_1_zeros():
return _AHT._Matx_short_2_1_zeros()
def _Matx_short_2_1_ones():
return _AHT._Matx_short_2_1_ones()
def _Matx_short_2_1_eye():
return _AHT._Matx_short_2_1_eye()
def _Matx_short_2_1_randu(a, b):
return _AHT._Matx_short_2_1_randu(a, b)
def _Matx_short_2_1_randn(a, b):
return _AHT._Matx_short_2_1_randn(a, b)
Matx21s = _Matx_short_2_1
class _Vec_short_2(_Matx_short_2_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_short_2_channels
@staticmethod
def all(alpha):
return _AHT._Vec_short_2_all(alpha)
def mul(self, v):
return _AHT._Vec_short_2_mul(self, v)
def __call__(self, i):
return _AHT._Vec_short_2___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_short_2_swiginit(self, _AHT.new__Vec_short_2(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_short_2___str__(self)
__swig_destroy__ = _AHT.delete__Vec_short_2
# Register _Vec_short_2 in _AHT:
_AHT._Vec_short_2_swigregister(_Vec_short_2)
def _Vec_short_2_all(alpha):
return _AHT._Vec_short_2_all(alpha)
class _DataType_Vec_short_2(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_short_2_generic_type
channels = _AHT._DataType_Vec_short_2_channels
fmt = _AHT._DataType_Vec_short_2_fmt
def __init__(self):
_AHT._DataType_Vec_short_2_swiginit(self, _AHT.new__DataType_Vec_short_2())
__swig_destroy__ = _AHT.delete__DataType_Vec_short_2
# Register _DataType_Vec_short_2 in _AHT:
_AHT._DataType_Vec_short_2_swigregister(_DataType_Vec_short_2)
Vec2s = _Vec_short_2
DataType_Vec2s = _DataType_Vec_short_2
class _Matx_short_3_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_short_3_1_rows
cols = _AHT._Matx_short_3_1_cols
channels = _AHT._Matx_short_3_1_channels
shortdim = _AHT._Matx_short_3_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_short_3_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_short_3_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_short_3_1_ones()
@staticmethod
def eye():
return _AHT._Matx_short_3_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_short_3_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_short_3_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_short_3_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_short_3_1_ddot(self, v)
def t(self):
return _AHT._Matx_short_3_1_t(self)
def mul(self, a):
return _AHT._Matx_short_3_1_mul(self, a)
def div(self, a):
return _AHT._Matx_short_3_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_short_3_1___call__(self, i, j)
val = property(_AHT._Matx_short_3_1_val_get, _AHT._Matx_short_3_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_short_3_1_swiginit(self, _AHT.new__Matx_short_3_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_short_3_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_short_3_1
# Register _Matx_short_3_1 in _AHT:
_AHT._Matx_short_3_1_swigregister(_Matx_short_3_1)
def _Matx_short_3_1_all(alpha):
return _AHT._Matx_short_3_1_all(alpha)
def _Matx_short_3_1_zeros():
return _AHT._Matx_short_3_1_zeros()
def _Matx_short_3_1_ones():
return _AHT._Matx_short_3_1_ones()
def _Matx_short_3_1_eye():
return _AHT._Matx_short_3_1_eye()
def _Matx_short_3_1_randu(a, b):
return _AHT._Matx_short_3_1_randu(a, b)
def _Matx_short_3_1_randn(a, b):
return _AHT._Matx_short_3_1_randn(a, b)
Matx31s = _Matx_short_3_1
class _Vec_short_3(_Matx_short_3_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_short_3_channels
@staticmethod
def all(alpha):
return _AHT._Vec_short_3_all(alpha)
def mul(self, v):
return _AHT._Vec_short_3_mul(self, v)
def __call__(self, i):
return _AHT._Vec_short_3___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_short_3_swiginit(self, _AHT.new__Vec_short_3(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_short_3___str__(self)
__swig_destroy__ = _AHT.delete__Vec_short_3
# Register _Vec_short_3 in _AHT:
_AHT._Vec_short_3_swigregister(_Vec_short_3)
def _Vec_short_3_all(alpha):
return _AHT._Vec_short_3_all(alpha)
class _DataType_Vec_short_3(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_short_3_generic_type
channels = _AHT._DataType_Vec_short_3_channels
fmt = _AHT._DataType_Vec_short_3_fmt
def __init__(self):
_AHT._DataType_Vec_short_3_swiginit(self, _AHT.new__DataType_Vec_short_3())
__swig_destroy__ = _AHT.delete__DataType_Vec_short_3
# Register _DataType_Vec_short_3 in _AHT:
_AHT._DataType_Vec_short_3_swigregister(_DataType_Vec_short_3)
Vec3s = _Vec_short_3
DataType_Vec3s = _DataType_Vec_short_3
class _Matx_short_4_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_short_4_1_rows
cols = _AHT._Matx_short_4_1_cols
channels = _AHT._Matx_short_4_1_channels
shortdim = _AHT._Matx_short_4_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_short_4_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_short_4_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_short_4_1_ones()
@staticmethod
def eye():
return _AHT._Matx_short_4_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_short_4_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_short_4_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_short_4_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_short_4_1_ddot(self, v)
def t(self):
return _AHT._Matx_short_4_1_t(self)
def mul(self, a):
return _AHT._Matx_short_4_1_mul(self, a)
def div(self, a):
return _AHT._Matx_short_4_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_short_4_1___call__(self, i, j)
val = property(_AHT._Matx_short_4_1_val_get, _AHT._Matx_short_4_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_short_4_1_swiginit(self, _AHT.new__Matx_short_4_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_short_4_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_short_4_1
# Register _Matx_short_4_1 in _AHT:
_AHT._Matx_short_4_1_swigregister(_Matx_short_4_1)
def _Matx_short_4_1_all(alpha):
return _AHT._Matx_short_4_1_all(alpha)
def _Matx_short_4_1_zeros():
return _AHT._Matx_short_4_1_zeros()
def _Matx_short_4_1_ones():
return _AHT._Matx_short_4_1_ones()
def _Matx_short_4_1_eye():
return _AHT._Matx_short_4_1_eye()
def _Matx_short_4_1_randu(a, b):
return _AHT._Matx_short_4_1_randu(a, b)
def _Matx_short_4_1_randn(a, b):
return _AHT._Matx_short_4_1_randn(a, b)
Matx41s = _Matx_short_4_1
class _Vec_short_4(_Matx_short_4_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_short_4_channels
@staticmethod
def all(alpha):
return _AHT._Vec_short_4_all(alpha)
def mul(self, v):
return _AHT._Vec_short_4_mul(self, v)
def __call__(self, i):
return _AHT._Vec_short_4___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_short_4_swiginit(self, _AHT.new__Vec_short_4(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_short_4___str__(self)
__swig_destroy__ = _AHT.delete__Vec_short_4
# Register _Vec_short_4 in _AHT:
_AHT._Vec_short_4_swigregister(_Vec_short_4)
def _Vec_short_4_all(alpha):
return _AHT._Vec_short_4_all(alpha)
class _DataType_Vec_short_4(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_short_4_generic_type
channels = _AHT._DataType_Vec_short_4_channels
fmt = _AHT._DataType_Vec_short_4_fmt
def __init__(self):
_AHT._DataType_Vec_short_4_swiginit(self, _AHT.new__DataType_Vec_short_4())
__swig_destroy__ = _AHT.delete__DataType_Vec_short_4
# Register _DataType_Vec_short_4 in _AHT:
_AHT._DataType_Vec_short_4_swigregister(_DataType_Vec_short_4)
Vec4s = _Vec_short_4
DataType_Vec4s = _DataType_Vec_short_4
class _cv_numpy_sizeof_ushort(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_ushort_value
def __init__(self):
_AHT._cv_numpy_sizeof_ushort_swiginit(self, _AHT.new__cv_numpy_sizeof_ushort())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_ushort
# Register _cv_numpy_sizeof_ushort in _AHT:
_AHT._cv_numpy_sizeof_ushort_swigregister(_cv_numpy_sizeof_ushort)
if _cv_numpy_sizeof_ushort.value == 1:
_cv_numpy_typestr_map["ushort"] = "|" +"u" + "1"
else:
_cv_numpy_typestr_map["ushort"] = _cv_numpy_endianess +"u" + str(_cv_numpy_sizeof_ushort.value)
class ushortArray(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def iterator(self):
return _AHT.ushortArray_iterator(self)
def __iter__(self):
return self.iterator()
def __nonzero__(self):
return _AHT.ushortArray___nonzero__(self)
def __bool__(self):
return _AHT.ushortArray___bool__(self)
def __len__(self):
return _AHT.ushortArray___len__(self)
def __getslice__(self, i, j):
return _AHT.ushortArray___getslice__(self, i, j)
def __setslice__(self, *args):
return _AHT.ushortArray___setslice__(self, *args)
def __delslice__(self, i, j):
return _AHT.ushortArray___delslice__(self, i, j)
def __delitem__(self, *args):
return _AHT.ushortArray___delitem__(self, *args)
def __getitem__(self, *args):
return _AHT.ushortArray___getitem__(self, *args)
def __setitem__(self, *args):
return _AHT.ushortArray___setitem__(self, *args)
def pop(self):
return _AHT.ushortArray_pop(self)
def append(self, x):
return _AHT.ushortArray_append(self, x)
def empty(self):
return _AHT.ushortArray_empty(self)
def size(self):
return _AHT.ushortArray_size(self)
def swap(self, v):
return _AHT.ushortArray_swap(self, v)
def begin(self):
return _AHT.ushortArray_begin(self)
def end(self):
return _AHT.ushortArray_end(self)
def rbegin(self):
return _AHT.ushortArray_rbegin(self)
def rend(self):
return _AHT.ushortArray_rend(self)
def clear(self):
return _AHT.ushortArray_clear(self)
def get_allocator(self):
return _AHT.ushortArray_get_allocator(self)
def pop_back(self):
return _AHT.ushortArray_pop_back(self)
def erase(self, *args):
return _AHT.ushortArray_erase(self, *args)
def __init__(self, *args):
_AHT.ushortArray_swiginit(self, _AHT.new_ushortArray(*args))
def push_back(self, x):
return _AHT.ushortArray_push_back(self, x)
def front(self):
return _AHT.ushortArray_front(self)
def back(self):
return _AHT.ushortArray_back(self)
def assign(self, n, x):
return _AHT.ushortArray_assign(self, n, x)
def resize(self, *args):
return _AHT.ushortArray_resize(self, *args)
def insert(self, *args):
return _AHT.ushortArray_insert(self, *args)
def reserve(self, n):
return _AHT.ushortArray_reserve(self, n)
def capacity(self):
return _AHT.ushortArray_capacity(self)
__swig_destroy__ = _AHT.delete_ushortArray
# Register ushortArray in _AHT:
_AHT.ushortArray_swigregister(ushortArray)
_array_map["ushort"] =ushortArray
class _Matx_ushort_2_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_ushort_2_1_rows
cols = _AHT._Matx_ushort_2_1_cols
channels = _AHT._Matx_ushort_2_1_channels
shortdim = _AHT._Matx_ushort_2_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_ushort_2_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_ushort_2_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_ushort_2_1_ones()
@staticmethod
def eye():
return _AHT._Matx_ushort_2_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_ushort_2_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_ushort_2_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_ushort_2_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_ushort_2_1_ddot(self, v)
def t(self):
return _AHT._Matx_ushort_2_1_t(self)
def mul(self, a):
return _AHT._Matx_ushort_2_1_mul(self, a)
def div(self, a):
return _AHT._Matx_ushort_2_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_ushort_2_1___call__(self, i, j)
val = property(_AHT._Matx_ushort_2_1_val_get, _AHT._Matx_ushort_2_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_ushort_2_1_swiginit(self, _AHT.new__Matx_ushort_2_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_ushort_2_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_ushort_2_1
# Register _Matx_ushort_2_1 in _AHT:
_AHT._Matx_ushort_2_1_swigregister(_Matx_ushort_2_1)
def _Matx_ushort_2_1_all(alpha):
return _AHT._Matx_ushort_2_1_all(alpha)
def _Matx_ushort_2_1_zeros():
return _AHT._Matx_ushort_2_1_zeros()
def _Matx_ushort_2_1_ones():
return _AHT._Matx_ushort_2_1_ones()
def _Matx_ushort_2_1_eye():
return _AHT._Matx_ushort_2_1_eye()
def _Matx_ushort_2_1_randu(a, b):
return _AHT._Matx_ushort_2_1_randu(a, b)
def _Matx_ushort_2_1_randn(a, b):
return _AHT._Matx_ushort_2_1_randn(a, b)
Matx21w = _Matx_ushort_2_1
class _Vec_ushort_2(_Matx_ushort_2_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_ushort_2_channels
@staticmethod
def all(alpha):
return _AHT._Vec_ushort_2_all(alpha)
def mul(self, v):
return _AHT._Vec_ushort_2_mul(self, v)
def __call__(self, i):
return _AHT._Vec_ushort_2___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_ushort_2_swiginit(self, _AHT.new__Vec_ushort_2(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_ushort_2___str__(self)
__swig_destroy__ = _AHT.delete__Vec_ushort_2
# Register _Vec_ushort_2 in _AHT:
_AHT._Vec_ushort_2_swigregister(_Vec_ushort_2)
def _Vec_ushort_2_all(alpha):
return _AHT._Vec_ushort_2_all(alpha)
class _DataType_Vec_ushort_2(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_ushort_2_generic_type
channels = _AHT._DataType_Vec_ushort_2_channels
fmt = _AHT._DataType_Vec_ushort_2_fmt
def __init__(self):
_AHT._DataType_Vec_ushort_2_swiginit(self, _AHT.new__DataType_Vec_ushort_2())
__swig_destroy__ = _AHT.delete__DataType_Vec_ushort_2
# Register _DataType_Vec_ushort_2 in _AHT:
_AHT._DataType_Vec_ushort_2_swigregister(_DataType_Vec_ushort_2)
Vec2w = _Vec_ushort_2
DataType_Vec2w = _DataType_Vec_ushort_2
class _Matx_ushort_3_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_ushort_3_1_rows
cols = _AHT._Matx_ushort_3_1_cols
channels = _AHT._Matx_ushort_3_1_channels
shortdim = _AHT._Matx_ushort_3_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_ushort_3_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_ushort_3_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_ushort_3_1_ones()
@staticmethod
def eye():
return _AHT._Matx_ushort_3_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_ushort_3_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_ushort_3_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_ushort_3_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_ushort_3_1_ddot(self, v)
def t(self):
return _AHT._Matx_ushort_3_1_t(self)
def mul(self, a):
return _AHT._Matx_ushort_3_1_mul(self, a)
def div(self, a):
return _AHT._Matx_ushort_3_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_ushort_3_1___call__(self, i, j)
val = property(_AHT._Matx_ushort_3_1_val_get, _AHT._Matx_ushort_3_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_ushort_3_1_swiginit(self, _AHT.new__Matx_ushort_3_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_ushort_3_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_ushort_3_1
# Register _Matx_ushort_3_1 in _AHT:
_AHT._Matx_ushort_3_1_swigregister(_Matx_ushort_3_1)
def _Matx_ushort_3_1_all(alpha):
return _AHT._Matx_ushort_3_1_all(alpha)
def _Matx_ushort_3_1_zeros():
return _AHT._Matx_ushort_3_1_zeros()
def _Matx_ushort_3_1_ones():
return _AHT._Matx_ushort_3_1_ones()
def _Matx_ushort_3_1_eye():
return _AHT._Matx_ushort_3_1_eye()
def _Matx_ushort_3_1_randu(a, b):
return _AHT._Matx_ushort_3_1_randu(a, b)
def _Matx_ushort_3_1_randn(a, b):
return _AHT._Matx_ushort_3_1_randn(a, b)
Matx31w = _Matx_ushort_3_1
class _Vec_ushort_3(_Matx_ushort_3_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_ushort_3_channels
@staticmethod
def all(alpha):
return _AHT._Vec_ushort_3_all(alpha)
def mul(self, v):
return _AHT._Vec_ushort_3_mul(self, v)
def __call__(self, i):
return _AHT._Vec_ushort_3___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_ushort_3_swiginit(self, _AHT.new__Vec_ushort_3(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_ushort_3___str__(self)
__swig_destroy__ = _AHT.delete__Vec_ushort_3
# Register _Vec_ushort_3 in _AHT:
_AHT._Vec_ushort_3_swigregister(_Vec_ushort_3)
def _Vec_ushort_3_all(alpha):
return _AHT._Vec_ushort_3_all(alpha)
class _DataType_Vec_ushort_3(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_ushort_3_generic_type
channels = _AHT._DataType_Vec_ushort_3_channels
fmt = _AHT._DataType_Vec_ushort_3_fmt
def __init__(self):
_AHT._DataType_Vec_ushort_3_swiginit(self, _AHT.new__DataType_Vec_ushort_3())
__swig_destroy__ = _AHT.delete__DataType_Vec_ushort_3
# Register _DataType_Vec_ushort_3 in _AHT:
_AHT._DataType_Vec_ushort_3_swigregister(_DataType_Vec_ushort_3)
Vec3w = _Vec_ushort_3
DataType_Vec3w = _DataType_Vec_ushort_3
class _Matx_ushort_4_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_ushort_4_1_rows
cols = _AHT._Matx_ushort_4_1_cols
channels = _AHT._Matx_ushort_4_1_channels
shortdim = _AHT._Matx_ushort_4_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_ushort_4_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_ushort_4_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_ushort_4_1_ones()
@staticmethod
def eye():
return _AHT._Matx_ushort_4_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_ushort_4_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_ushort_4_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_ushort_4_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_ushort_4_1_ddot(self, v)
def t(self):
return _AHT._Matx_ushort_4_1_t(self)
def mul(self, a):
return _AHT._Matx_ushort_4_1_mul(self, a)
def div(self, a):
return _AHT._Matx_ushort_4_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_ushort_4_1___call__(self, i, j)
val = property(_AHT._Matx_ushort_4_1_val_get, _AHT._Matx_ushort_4_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_ushort_4_1_swiginit(self, _AHT.new__Matx_ushort_4_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_ushort_4_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_ushort_4_1
# Register _Matx_ushort_4_1 in _AHT:
_AHT._Matx_ushort_4_1_swigregister(_Matx_ushort_4_1)
def _Matx_ushort_4_1_all(alpha):
return _AHT._Matx_ushort_4_1_all(alpha)
def _Matx_ushort_4_1_zeros():
return _AHT._Matx_ushort_4_1_zeros()
def _Matx_ushort_4_1_ones():
return _AHT._Matx_ushort_4_1_ones()
def _Matx_ushort_4_1_eye():
return _AHT._Matx_ushort_4_1_eye()
def _Matx_ushort_4_1_randu(a, b):
return _AHT._Matx_ushort_4_1_randu(a, b)
def _Matx_ushort_4_1_randn(a, b):
return _AHT._Matx_ushort_4_1_randn(a, b)
Matx41w = _Matx_ushort_4_1
class _Vec_ushort_4(_Matx_ushort_4_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_ushort_4_channels
@staticmethod
def all(alpha):
return _AHT._Vec_ushort_4_all(alpha)
def mul(self, v):
return _AHT._Vec_ushort_4_mul(self, v)
def __call__(self, i):
return _AHT._Vec_ushort_4___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_ushort_4_swiginit(self, _AHT.new__Vec_ushort_4(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_ushort_4___str__(self)
__swig_destroy__ = _AHT.delete__Vec_ushort_4
# Register _Vec_ushort_4 in _AHT:
_AHT._Vec_ushort_4_swigregister(_Vec_ushort_4)
def _Vec_ushort_4_all(alpha):
return _AHT._Vec_ushort_4_all(alpha)
class _DataType_Vec_ushort_4(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_ushort_4_generic_type
channels = _AHT._DataType_Vec_ushort_4_channels
fmt = _AHT._DataType_Vec_ushort_4_fmt
def __init__(self):
_AHT._DataType_Vec_ushort_4_swiginit(self, _AHT.new__DataType_Vec_ushort_4())
__swig_destroy__ = _AHT.delete__DataType_Vec_ushort_4
# Register _DataType_Vec_ushort_4 in _AHT:
_AHT._DataType_Vec_ushort_4_swigregister(_DataType_Vec_ushort_4)
Vec4w = _Vec_ushort_4
DataType_Vec4w = _DataType_Vec_ushort_4
class _cv_numpy_sizeof_int(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_int_value
def __init__(self):
_AHT._cv_numpy_sizeof_int_swiginit(self, _AHT.new__cv_numpy_sizeof_int())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_int
# Register _cv_numpy_sizeof_int in _AHT:
_AHT._cv_numpy_sizeof_int_swigregister(_cv_numpy_sizeof_int)
if _cv_numpy_sizeof_int.value == 1:
_cv_numpy_typestr_map["int"] = "|" +"i" + "1"
else:
_cv_numpy_typestr_map["int"] = _cv_numpy_endianess +"i" + str(_cv_numpy_sizeof_int.value)
class intArray(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def iterator(self):
return _AHT.intArray_iterator(self)
def __iter__(self):
return self.iterator()
def __nonzero__(self):
return _AHT.intArray___nonzero__(self)
def __bool__(self):
return _AHT.intArray___bool__(self)
def __len__(self):
return _AHT.intArray___len__(self)
def __getslice__(self, i, j):
return _AHT.intArray___getslice__(self, i, j)
def __setslice__(self, *args):
return _AHT.intArray___setslice__(self, *args)
def __delslice__(self, i, j):
return _AHT.intArray___delslice__(self, i, j)
def __delitem__(self, *args):
return _AHT.intArray___delitem__(self, *args)
def __getitem__(self, *args):
return _AHT.intArray___getitem__(self, *args)
def __setitem__(self, *args):
return _AHT.intArray___setitem__(self, *args)
def pop(self):
return _AHT.intArray_pop(self)
def append(self, x):
return _AHT.intArray_append(self, x)
def empty(self):
return _AHT.intArray_empty(self)
def size(self):
return _AHT.intArray_size(self)
def swap(self, v):
return _AHT.intArray_swap(self, v)
def begin(self):
return _AHT.intArray_begin(self)
def end(self):
return _AHT.intArray_end(self)
def rbegin(self):
return _AHT.intArray_rbegin(self)
def rend(self):
return _AHT.intArray_rend(self)
def clear(self):
return _AHT.intArray_clear(self)
def get_allocator(self):
return _AHT.intArray_get_allocator(self)
def pop_back(self):
return _AHT.intArray_pop_back(self)
def erase(self, *args):
return _AHT.intArray_erase(self, *args)
def __init__(self, *args):
_AHT.intArray_swiginit(self, _AHT.new_intArray(*args))
def push_back(self, x):
return _AHT.intArray_push_back(self, x)
def front(self):
return _AHT.intArray_front(self)
def back(self):
return _AHT.intArray_back(self)
def assign(self, n, x):
return _AHT.intArray_assign(self, n, x)
def resize(self, *args):
return _AHT.intArray_resize(self, *args)
def insert(self, *args):
return _AHT.intArray_insert(self, *args)
def reserve(self, n):
return _AHT.intArray_reserve(self, n)
def capacity(self):
return _AHT.intArray_capacity(self)
__swig_destroy__ = _AHT.delete_intArray
# Register intArray in _AHT:
_AHT.intArray_swigregister(intArray)
_array_map["int"] =intArray
class _Matx_int_2_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_int_2_1_rows
cols = _AHT._Matx_int_2_1_cols
channels = _AHT._Matx_int_2_1_channels
shortdim = _AHT._Matx_int_2_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_int_2_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_int_2_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_int_2_1_ones()
@staticmethod
def eye():
return _AHT._Matx_int_2_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_int_2_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_int_2_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_int_2_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_int_2_1_ddot(self, v)
def t(self):
return _AHT._Matx_int_2_1_t(self)
def mul(self, a):
return _AHT._Matx_int_2_1_mul(self, a)
def div(self, a):
return _AHT._Matx_int_2_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_int_2_1___call__(self, i, j)
val = property(_AHT._Matx_int_2_1_val_get, _AHT._Matx_int_2_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_int_2_1_swiginit(self, _AHT.new__Matx_int_2_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_int_2_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_int_2_1
# Register _Matx_int_2_1 in _AHT:
_AHT._Matx_int_2_1_swigregister(_Matx_int_2_1)
def _Matx_int_2_1_all(alpha):
return _AHT._Matx_int_2_1_all(alpha)
def _Matx_int_2_1_zeros():
return _AHT._Matx_int_2_1_zeros()
def _Matx_int_2_1_ones():
return _AHT._Matx_int_2_1_ones()
def _Matx_int_2_1_eye():
return _AHT._Matx_int_2_1_eye()
def _Matx_int_2_1_randu(a, b):
return _AHT._Matx_int_2_1_randu(a, b)
def _Matx_int_2_1_randn(a, b):
return _AHT._Matx_int_2_1_randn(a, b)
Matx21i = _Matx_int_2_1
class _Vec_int_2(_Matx_int_2_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_int_2_channels
@staticmethod
def all(alpha):
return _AHT._Vec_int_2_all(alpha)
def mul(self, v):
return _AHT._Vec_int_2_mul(self, v)
def __call__(self, i):
return _AHT._Vec_int_2___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_int_2_swiginit(self, _AHT.new__Vec_int_2(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_int_2___str__(self)
__swig_destroy__ = _AHT.delete__Vec_int_2
# Register _Vec_int_2 in _AHT:
_AHT._Vec_int_2_swigregister(_Vec_int_2)
def _Vec_int_2_all(alpha):
return _AHT._Vec_int_2_all(alpha)
class _DataType_Vec_int_2(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_int_2_generic_type
channels = _AHT._DataType_Vec_int_2_channels
fmt = _AHT._DataType_Vec_int_2_fmt
def __init__(self):
_AHT._DataType_Vec_int_2_swiginit(self, _AHT.new__DataType_Vec_int_2())
__swig_destroy__ = _AHT.delete__DataType_Vec_int_2
# Register _DataType_Vec_int_2 in _AHT:
_AHT._DataType_Vec_int_2_swigregister(_DataType_Vec_int_2)
Vec2i = _Vec_int_2
DataType_Vec2i = _DataType_Vec_int_2
class _Matx_int_3_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_int_3_1_rows
cols = _AHT._Matx_int_3_1_cols
channels = _AHT._Matx_int_3_1_channels
shortdim = _AHT._Matx_int_3_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_int_3_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_int_3_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_int_3_1_ones()
@staticmethod
def eye():
return _AHT._Matx_int_3_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_int_3_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_int_3_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_int_3_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_int_3_1_ddot(self, v)
def t(self):
return _AHT._Matx_int_3_1_t(self)
def mul(self, a):
return _AHT._Matx_int_3_1_mul(self, a)
def div(self, a):
return _AHT._Matx_int_3_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_int_3_1___call__(self, i, j)
val = property(_AHT._Matx_int_3_1_val_get, _AHT._Matx_int_3_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_int_3_1_swiginit(self, _AHT.new__Matx_int_3_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_int_3_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_int_3_1
# Register _Matx_int_3_1 in _AHT:
_AHT._Matx_int_3_1_swigregister(_Matx_int_3_1)
def _Matx_int_3_1_all(alpha):
return _AHT._Matx_int_3_1_all(alpha)
def _Matx_int_3_1_zeros():
return _AHT._Matx_int_3_1_zeros()
def _Matx_int_3_1_ones():
return _AHT._Matx_int_3_1_ones()
def _Matx_int_3_1_eye():
return _AHT._Matx_int_3_1_eye()
def _Matx_int_3_1_randu(a, b):
return _AHT._Matx_int_3_1_randu(a, b)
def _Matx_int_3_1_randn(a, b):
return _AHT._Matx_int_3_1_randn(a, b)
Matx31i = _Matx_int_3_1
class _Vec_int_3(_Matx_int_3_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_int_3_channels
@staticmethod
def all(alpha):
return _AHT._Vec_int_3_all(alpha)
def mul(self, v):
return _AHT._Vec_int_3_mul(self, v)
def __call__(self, i):
return _AHT._Vec_int_3___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_int_3_swiginit(self, _AHT.new__Vec_int_3(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_int_3___str__(self)
__swig_destroy__ = _AHT.delete__Vec_int_3
# Register _Vec_int_3 in _AHT:
_AHT._Vec_int_3_swigregister(_Vec_int_3)
def _Vec_int_3_all(alpha):
return _AHT._Vec_int_3_all(alpha)
class _DataType_Vec_int_3(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_int_3_generic_type
channels = _AHT._DataType_Vec_int_3_channels
fmt = _AHT._DataType_Vec_int_3_fmt
def __init__(self):
_AHT._DataType_Vec_int_3_swiginit(self, _AHT.new__DataType_Vec_int_3())
__swig_destroy__ = _AHT.delete__DataType_Vec_int_3
# Register _DataType_Vec_int_3 in _AHT:
_AHT._DataType_Vec_int_3_swigregister(_DataType_Vec_int_3)
Vec3i = _Vec_int_3
DataType_Vec3i = _DataType_Vec_int_3
class _Matx_int_4_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_int_4_1_rows
cols = _AHT._Matx_int_4_1_cols
channels = _AHT._Matx_int_4_1_channels
shortdim = _AHT._Matx_int_4_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_int_4_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_int_4_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_int_4_1_ones()
@staticmethod
def eye():
return _AHT._Matx_int_4_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_int_4_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_int_4_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_int_4_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_int_4_1_ddot(self, v)
def t(self):
return _AHT._Matx_int_4_1_t(self)
def mul(self, a):
return _AHT._Matx_int_4_1_mul(self, a)
def div(self, a):
return _AHT._Matx_int_4_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_int_4_1___call__(self, i, j)
val = property(_AHT._Matx_int_4_1_val_get, _AHT._Matx_int_4_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_int_4_1_swiginit(self, _AHT.new__Matx_int_4_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_int_4_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_int_4_1
# Register _Matx_int_4_1 in _AHT:
_AHT._Matx_int_4_1_swigregister(_Matx_int_4_1)
def _Matx_int_4_1_all(alpha):
return _AHT._Matx_int_4_1_all(alpha)
def _Matx_int_4_1_zeros():
return _AHT._Matx_int_4_1_zeros()
def _Matx_int_4_1_ones():
return _AHT._Matx_int_4_1_ones()
def _Matx_int_4_1_eye():
return _AHT._Matx_int_4_1_eye()
def _Matx_int_4_1_randu(a, b):
return _AHT._Matx_int_4_1_randu(a, b)
def _Matx_int_4_1_randn(a, b):
return _AHT._Matx_int_4_1_randn(a, b)
Matx41i = _Matx_int_4_1
class _Vec_int_4(_Matx_int_4_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_int_4_channels
@staticmethod
def all(alpha):
return _AHT._Vec_int_4_all(alpha)
def mul(self, v):
return _AHT._Vec_int_4_mul(self, v)
def __call__(self, i):
return _AHT._Vec_int_4___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_int_4_swiginit(self, _AHT.new__Vec_int_4(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_int_4___str__(self)
__swig_destroy__ = _AHT.delete__Vec_int_4
# Register _Vec_int_4 in _AHT:
_AHT._Vec_int_4_swigregister(_Vec_int_4)
def _Vec_int_4_all(alpha):
return _AHT._Vec_int_4_all(alpha)
class _DataType_Vec_int_4(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_int_4_generic_type
channels = _AHT._DataType_Vec_int_4_channels
fmt = _AHT._DataType_Vec_int_4_fmt
def __init__(self):
_AHT._DataType_Vec_int_4_swiginit(self, _AHT.new__DataType_Vec_int_4())
__swig_destroy__ = _AHT.delete__DataType_Vec_int_4
# Register _DataType_Vec_int_4 in _AHT:
_AHT._DataType_Vec_int_4_swigregister(_DataType_Vec_int_4)
Vec4i = _Vec_int_4
DataType_Vec4i = _DataType_Vec_int_4
class _Matx_int_6_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_int_6_1_rows
cols = _AHT._Matx_int_6_1_cols
channels = _AHT._Matx_int_6_1_channels
shortdim = _AHT._Matx_int_6_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_int_6_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_int_6_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_int_6_1_ones()
@staticmethod
def eye():
return _AHT._Matx_int_6_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_int_6_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_int_6_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_int_6_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_int_6_1_ddot(self, v)
def t(self):
return _AHT._Matx_int_6_1_t(self)
def mul(self, a):
return _AHT._Matx_int_6_1_mul(self, a)
def div(self, a):
return _AHT._Matx_int_6_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_int_6_1___call__(self, i, j)
val = property(_AHT._Matx_int_6_1_val_get, _AHT._Matx_int_6_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_int_6_1_swiginit(self, _AHT.new__Matx_int_6_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_int_6_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_int_6_1
# Register _Matx_int_6_1 in _AHT:
_AHT._Matx_int_6_1_swigregister(_Matx_int_6_1)
def _Matx_int_6_1_all(alpha):
return _AHT._Matx_int_6_1_all(alpha)
def _Matx_int_6_1_zeros():
return _AHT._Matx_int_6_1_zeros()
def _Matx_int_6_1_ones():
return _AHT._Matx_int_6_1_ones()
def _Matx_int_6_1_eye():
return _AHT._Matx_int_6_1_eye()
def _Matx_int_6_1_randu(a, b):
return _AHT._Matx_int_6_1_randu(a, b)
def _Matx_int_6_1_randn(a, b):
return _AHT._Matx_int_6_1_randn(a, b)
Matx61i = _Matx_int_6_1
class _Vec_int_6(_Matx_int_6_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_int_6_channels
@staticmethod
def all(alpha):
return _AHT._Vec_int_6_all(alpha)
def mul(self, v):
return _AHT._Vec_int_6_mul(self, v)
def __call__(self, i):
return _AHT._Vec_int_6___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_int_6_swiginit(self, _AHT.new__Vec_int_6(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_int_6___str__(self)
__swig_destroy__ = _AHT.delete__Vec_int_6
# Register _Vec_int_6 in _AHT:
_AHT._Vec_int_6_swigregister(_Vec_int_6)
def _Vec_int_6_all(alpha):
return _AHT._Vec_int_6_all(alpha)
class _DataType_Vec_int_6(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_int_6_generic_type
channels = _AHT._DataType_Vec_int_6_channels
fmt = _AHT._DataType_Vec_int_6_fmt
def __init__(self):
_AHT._DataType_Vec_int_6_swiginit(self, _AHT.new__DataType_Vec_int_6())
__swig_destroy__ = _AHT.delete__DataType_Vec_int_6
# Register _DataType_Vec_int_6 in _AHT:
_AHT._DataType_Vec_int_6_swigregister(_DataType_Vec_int_6)
Vec6i = _Vec_int_6
DataType_Vec6i = _DataType_Vec_int_6
class _Matx_int_8_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_int_8_1_rows
cols = _AHT._Matx_int_8_1_cols
channels = _AHT._Matx_int_8_1_channels
shortdim = _AHT._Matx_int_8_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_int_8_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_int_8_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_int_8_1_ones()
@staticmethod
def eye():
return _AHT._Matx_int_8_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_int_8_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_int_8_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_int_8_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_int_8_1_ddot(self, v)
def t(self):
return _AHT._Matx_int_8_1_t(self)
def mul(self, a):
return _AHT._Matx_int_8_1_mul(self, a)
def div(self, a):
return _AHT._Matx_int_8_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_int_8_1___call__(self, i, j)
val = property(_AHT._Matx_int_8_1_val_get, _AHT._Matx_int_8_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_int_8_1_swiginit(self, _AHT.new__Matx_int_8_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_int_8_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_int_8_1
# Register _Matx_int_8_1 in _AHT:
_AHT._Matx_int_8_1_swigregister(_Matx_int_8_1)
def _Matx_int_8_1_all(alpha):
return _AHT._Matx_int_8_1_all(alpha)
def _Matx_int_8_1_zeros():
return _AHT._Matx_int_8_1_zeros()
def _Matx_int_8_1_ones():
return _AHT._Matx_int_8_1_ones()
def _Matx_int_8_1_eye():
return _AHT._Matx_int_8_1_eye()
def _Matx_int_8_1_randu(a, b):
return _AHT._Matx_int_8_1_randu(a, b)
def _Matx_int_8_1_randn(a, b):
return _AHT._Matx_int_8_1_randn(a, b)
Matx81i = _Matx_int_8_1
class _Vec_int_8(_Matx_int_8_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_int_8_channels
@staticmethod
def all(alpha):
return _AHT._Vec_int_8_all(alpha)
def mul(self, v):
return _AHT._Vec_int_8_mul(self, v)
def __call__(self, i):
return _AHT._Vec_int_8___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_int_8_swiginit(self, _AHT.new__Vec_int_8(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_int_8___str__(self)
__swig_destroy__ = _AHT.delete__Vec_int_8
# Register _Vec_int_8 in _AHT:
_AHT._Vec_int_8_swigregister(_Vec_int_8)
def _Vec_int_8_all(alpha):
return _AHT._Vec_int_8_all(alpha)
class _DataType_Vec_int_8(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_int_8_generic_type
channels = _AHT._DataType_Vec_int_8_channels
fmt = _AHT._DataType_Vec_int_8_fmt
def __init__(self):
_AHT._DataType_Vec_int_8_swiginit(self, _AHT.new__DataType_Vec_int_8())
__swig_destroy__ = _AHT.delete__DataType_Vec_int_8
# Register _DataType_Vec_int_8 in _AHT:
_AHT._DataType_Vec_int_8_swigregister(_DataType_Vec_int_8)
Vec8i = _Vec_int_8
DataType_Vec8i = _DataType_Vec_int_8
class _cv_numpy_sizeof_float(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_float_value
def __init__(self):
_AHT._cv_numpy_sizeof_float_swiginit(self, _AHT.new__cv_numpy_sizeof_float())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_float
# Register _cv_numpy_sizeof_float in _AHT:
_AHT._cv_numpy_sizeof_float_swigregister(_cv_numpy_sizeof_float)
if _cv_numpy_sizeof_float.value == 1:
_cv_numpy_typestr_map["float"] = "|" +"f" + "1"
else:
_cv_numpy_typestr_map["float"] = _cv_numpy_endianess +"f" + str(_cv_numpy_sizeof_float.value)
class floatArray(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def iterator(self):
return _AHT.floatArray_iterator(self)
def __iter__(self):
return self.iterator()
def __nonzero__(self):
return _AHT.floatArray___nonzero__(self)
def __bool__(self):
return _AHT.floatArray___bool__(self)
def __len__(self):
return _AHT.floatArray___len__(self)
def __getslice__(self, i, j):
return _AHT.floatArray___getslice__(self, i, j)
def __setslice__(self, *args):
return _AHT.floatArray___setslice__(self, *args)
def __delslice__(self, i, j):
return _AHT.floatArray___delslice__(self, i, j)
def __delitem__(self, *args):
return _AHT.floatArray___delitem__(self, *args)
def __getitem__(self, *args):
return _AHT.floatArray___getitem__(self, *args)
def __setitem__(self, *args):
return _AHT.floatArray___setitem__(self, *args)
def pop(self):
return _AHT.floatArray_pop(self)
def append(self, x):
return _AHT.floatArray_append(self, x)
def empty(self):
return _AHT.floatArray_empty(self)
def size(self):
return _AHT.floatArray_size(self)
def swap(self, v):
return _AHT.floatArray_swap(self, v)
def begin(self):
return _AHT.floatArray_begin(self)
def end(self):
return _AHT.floatArray_end(self)
def rbegin(self):
return _AHT.floatArray_rbegin(self)
def rend(self):
return _AHT.floatArray_rend(self)
def clear(self):
return _AHT.floatArray_clear(self)
def get_allocator(self):
return _AHT.floatArray_get_allocator(self)
def pop_back(self):
return _AHT.floatArray_pop_back(self)
def erase(self, *args):
return _AHT.floatArray_erase(self, *args)
def __init__(self, *args):
_AHT.floatArray_swiginit(self, _AHT.new_floatArray(*args))
def push_back(self, x):
return _AHT.floatArray_push_back(self, x)
def front(self):
return _AHT.floatArray_front(self)
def back(self):
return _AHT.floatArray_back(self)
def assign(self, n, x):
return _AHT.floatArray_assign(self, n, x)
def resize(self, *args):
return _AHT.floatArray_resize(self, *args)
def insert(self, *args):
return _AHT.floatArray_insert(self, *args)
def reserve(self, n):
return _AHT.floatArray_reserve(self, n)
def capacity(self):
return _AHT.floatArray_capacity(self)
__swig_destroy__ = _AHT.delete_floatArray
# Register floatArray in _AHT:
_AHT.floatArray_swigregister(floatArray)
_array_map["float"] =floatArray
class _Matx_float_2_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_float_2_1_rows
cols = _AHT._Matx_float_2_1_cols
channels = _AHT._Matx_float_2_1_channels
shortdim = _AHT._Matx_float_2_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_float_2_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_float_2_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_float_2_1_ones()
@staticmethod
def eye():
return _AHT._Matx_float_2_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_float_2_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_float_2_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_float_2_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_float_2_1_ddot(self, v)
def t(self):
return _AHT._Matx_float_2_1_t(self)
def mul(self, a):
return _AHT._Matx_float_2_1_mul(self, a)
def div(self, a):
return _AHT._Matx_float_2_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_float_2_1___call__(self, i, j)
val = property(_AHT._Matx_float_2_1_val_get, _AHT._Matx_float_2_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_float_2_1_swiginit(self, _AHT.new__Matx_float_2_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_float_2_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_float_2_1
# Register _Matx_float_2_1 in _AHT:
_AHT._Matx_float_2_1_swigregister(_Matx_float_2_1)
def _Matx_float_2_1_all(alpha):
return _AHT._Matx_float_2_1_all(alpha)
def _Matx_float_2_1_zeros():
return _AHT._Matx_float_2_1_zeros()
def _Matx_float_2_1_ones():
return _AHT._Matx_float_2_1_ones()
def _Matx_float_2_1_eye():
return _AHT._Matx_float_2_1_eye()
def _Matx_float_2_1_randu(a, b):
return _AHT._Matx_float_2_1_randu(a, b)
def _Matx_float_2_1_randn(a, b):
return _AHT._Matx_float_2_1_randn(a, b)
Matx21f = _Matx_float_2_1
class _Vec_float_2(_Matx_float_2_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_float_2_channels
@staticmethod
def all(alpha):
return _AHT._Vec_float_2_all(alpha)
def mul(self, v):
return _AHT._Vec_float_2_mul(self, v)
def __call__(self, i):
return _AHT._Vec_float_2___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_float_2_swiginit(self, _AHT.new__Vec_float_2(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_float_2___str__(self)
__swig_destroy__ = _AHT.delete__Vec_float_2
# Register _Vec_float_2 in _AHT:
_AHT._Vec_float_2_swigregister(_Vec_float_2)
def _Vec_float_2_all(alpha):
return _AHT._Vec_float_2_all(alpha)
class _DataType_Vec_float_2(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_float_2_generic_type
channels = _AHT._DataType_Vec_float_2_channels
fmt = _AHT._DataType_Vec_float_2_fmt
def __init__(self):
_AHT._DataType_Vec_float_2_swiginit(self, _AHT.new__DataType_Vec_float_2())
__swig_destroy__ = _AHT.delete__DataType_Vec_float_2
# Register _DataType_Vec_float_2 in _AHT:
_AHT._DataType_Vec_float_2_swigregister(_DataType_Vec_float_2)
Vec2f = _Vec_float_2
DataType_Vec2f = _DataType_Vec_float_2
class _Matx_float_3_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_float_3_1_rows
cols = _AHT._Matx_float_3_1_cols
channels = _AHT._Matx_float_3_1_channels
shortdim = _AHT._Matx_float_3_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_float_3_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_float_3_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_float_3_1_ones()
@staticmethod
def eye():
return _AHT._Matx_float_3_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_float_3_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_float_3_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_float_3_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_float_3_1_ddot(self, v)
def t(self):
return _AHT._Matx_float_3_1_t(self)
def mul(self, a):
return _AHT._Matx_float_3_1_mul(self, a)
def div(self, a):
return _AHT._Matx_float_3_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_float_3_1___call__(self, i, j)
val = property(_AHT._Matx_float_3_1_val_get, _AHT._Matx_float_3_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_float_3_1_swiginit(self, _AHT.new__Matx_float_3_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_float_3_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_float_3_1
# Register _Matx_float_3_1 in _AHT:
_AHT._Matx_float_3_1_swigregister(_Matx_float_3_1)
def _Matx_float_3_1_all(alpha):
return _AHT._Matx_float_3_1_all(alpha)
def _Matx_float_3_1_zeros():
return _AHT._Matx_float_3_1_zeros()
def _Matx_float_3_1_ones():
return _AHT._Matx_float_3_1_ones()
def _Matx_float_3_1_eye():
return _AHT._Matx_float_3_1_eye()
def _Matx_float_3_1_randu(a, b):
return _AHT._Matx_float_3_1_randu(a, b)
def _Matx_float_3_1_randn(a, b):
return _AHT._Matx_float_3_1_randn(a, b)
Matx31f = _Matx_float_3_1
class _Vec_float_3(_Matx_float_3_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_float_3_channels
@staticmethod
def all(alpha):
return _AHT._Vec_float_3_all(alpha)
def mul(self, v):
return _AHT._Vec_float_3_mul(self, v)
def __call__(self, i):
return _AHT._Vec_float_3___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_float_3_swiginit(self, _AHT.new__Vec_float_3(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_float_3___str__(self)
__swig_destroy__ = _AHT.delete__Vec_float_3
# Register _Vec_float_3 in _AHT:
_AHT._Vec_float_3_swigregister(_Vec_float_3)
def _Vec_float_3_all(alpha):
return _AHT._Vec_float_3_all(alpha)
class _DataType_Vec_float_3(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_float_3_generic_type
channels = _AHT._DataType_Vec_float_3_channels
fmt = _AHT._DataType_Vec_float_3_fmt
def __init__(self):
_AHT._DataType_Vec_float_3_swiginit(self, _AHT.new__DataType_Vec_float_3())
__swig_destroy__ = _AHT.delete__DataType_Vec_float_3
# Register _DataType_Vec_float_3 in _AHT:
_AHT._DataType_Vec_float_3_swigregister(_DataType_Vec_float_3)
Vec3f = _Vec_float_3
DataType_Vec3f = _DataType_Vec_float_3
class _Matx_float_4_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_float_4_1_rows
cols = _AHT._Matx_float_4_1_cols
channels = _AHT._Matx_float_4_1_channels
shortdim = _AHT._Matx_float_4_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_float_4_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_float_4_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_float_4_1_ones()
@staticmethod
def eye():
return _AHT._Matx_float_4_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_float_4_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_float_4_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_float_4_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_float_4_1_ddot(self, v)
def t(self):
return _AHT._Matx_float_4_1_t(self)
def mul(self, a):
return _AHT._Matx_float_4_1_mul(self, a)
def div(self, a):
return _AHT._Matx_float_4_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_float_4_1___call__(self, i, j)
val = property(_AHT._Matx_float_4_1_val_get, _AHT._Matx_float_4_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_float_4_1_swiginit(self, _AHT.new__Matx_float_4_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_float_4_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_float_4_1
# Register _Matx_float_4_1 in _AHT:
_AHT._Matx_float_4_1_swigregister(_Matx_float_4_1)
def _Matx_float_4_1_all(alpha):
return _AHT._Matx_float_4_1_all(alpha)
def _Matx_float_4_1_zeros():
return _AHT._Matx_float_4_1_zeros()
def _Matx_float_4_1_ones():
return _AHT._Matx_float_4_1_ones()
def _Matx_float_4_1_eye():
return _AHT._Matx_float_4_1_eye()
def _Matx_float_4_1_randu(a, b):
return _AHT._Matx_float_4_1_randu(a, b)
def _Matx_float_4_1_randn(a, b):
return _AHT._Matx_float_4_1_randn(a, b)
Matx41f = _Matx_float_4_1
class _Vec_float_4(_Matx_float_4_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_float_4_channels
@staticmethod
def all(alpha):
return _AHT._Vec_float_4_all(alpha)
def mul(self, v):
return _AHT._Vec_float_4_mul(self, v)
def __call__(self, i):
return _AHT._Vec_float_4___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_float_4_swiginit(self, _AHT.new__Vec_float_4(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_float_4___str__(self)
__swig_destroy__ = _AHT.delete__Vec_float_4
# Register _Vec_float_4 in _AHT:
_AHT._Vec_float_4_swigregister(_Vec_float_4)
def _Vec_float_4_all(alpha):
return _AHT._Vec_float_4_all(alpha)
class _DataType_Vec_float_4(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_float_4_generic_type
channels = _AHT._DataType_Vec_float_4_channels
fmt = _AHT._DataType_Vec_float_4_fmt
def __init__(self):
_AHT._DataType_Vec_float_4_swiginit(self, _AHT.new__DataType_Vec_float_4())
__swig_destroy__ = _AHT.delete__DataType_Vec_float_4
# Register _DataType_Vec_float_4 in _AHT:
_AHT._DataType_Vec_float_4_swigregister(_DataType_Vec_float_4)
Vec4f = _Vec_float_4
DataType_Vec4f = _DataType_Vec_float_4
class _Matx_float_6_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_float_6_1_rows
cols = _AHT._Matx_float_6_1_cols
channels = _AHT._Matx_float_6_1_channels
shortdim = _AHT._Matx_float_6_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_float_6_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_float_6_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_float_6_1_ones()
@staticmethod
def eye():
return _AHT._Matx_float_6_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_float_6_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_float_6_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_float_6_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_float_6_1_ddot(self, v)
def t(self):
return _AHT._Matx_float_6_1_t(self)
def mul(self, a):
return _AHT._Matx_float_6_1_mul(self, a)
def div(self, a):
return _AHT._Matx_float_6_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_float_6_1___call__(self, i, j)
val = property(_AHT._Matx_float_6_1_val_get, _AHT._Matx_float_6_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_float_6_1_swiginit(self, _AHT.new__Matx_float_6_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_float_6_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_float_6_1
# Register _Matx_float_6_1 in _AHT:
_AHT._Matx_float_6_1_swigregister(_Matx_float_6_1)
def _Matx_float_6_1_all(alpha):
return _AHT._Matx_float_6_1_all(alpha)
def _Matx_float_6_1_zeros():
return _AHT._Matx_float_6_1_zeros()
def _Matx_float_6_1_ones():
return _AHT._Matx_float_6_1_ones()
def _Matx_float_6_1_eye():
return _AHT._Matx_float_6_1_eye()
def _Matx_float_6_1_randu(a, b):
return _AHT._Matx_float_6_1_randu(a, b)
def _Matx_float_6_1_randn(a, b):
return _AHT._Matx_float_6_1_randn(a, b)
Matx61f = _Matx_float_6_1
class _Vec_float_6(_Matx_float_6_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_float_6_channels
@staticmethod
def all(alpha):
return _AHT._Vec_float_6_all(alpha)
def mul(self, v):
return _AHT._Vec_float_6_mul(self, v)
def __call__(self, i):
return _AHT._Vec_float_6___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_float_6_swiginit(self, _AHT.new__Vec_float_6(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_float_6___str__(self)
__swig_destroy__ = _AHT.delete__Vec_float_6
# Register _Vec_float_6 in _AHT:
_AHT._Vec_float_6_swigregister(_Vec_float_6)
def _Vec_float_6_all(alpha):
return _AHT._Vec_float_6_all(alpha)
class _DataType_Vec_float_6(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_float_6_generic_type
channels = _AHT._DataType_Vec_float_6_channels
fmt = _AHT._DataType_Vec_float_6_fmt
def __init__(self):
_AHT._DataType_Vec_float_6_swiginit(self, _AHT.new__DataType_Vec_float_6())
__swig_destroy__ = _AHT.delete__DataType_Vec_float_6
# Register _DataType_Vec_float_6 in _AHT:
_AHT._DataType_Vec_float_6_swigregister(_DataType_Vec_float_6)
Vec6f = _Vec_float_6
DataType_Vec6f = _DataType_Vec_float_6
class _cv_numpy_sizeof_double(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_double_value
def __init__(self):
_AHT._cv_numpy_sizeof_double_swiginit(self, _AHT.new__cv_numpy_sizeof_double())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_double
# Register _cv_numpy_sizeof_double in _AHT:
_AHT._cv_numpy_sizeof_double_swigregister(_cv_numpy_sizeof_double)
if _cv_numpy_sizeof_double.value == 1:
_cv_numpy_typestr_map["double"] = "|" +"f" + "1"
else:
_cv_numpy_typestr_map["double"] = _cv_numpy_endianess +"f" + str(_cv_numpy_sizeof_double.value)
class doubleArray(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def iterator(self):
return _AHT.doubleArray_iterator(self)
def __iter__(self):
return self.iterator()
def __nonzero__(self):
return _AHT.doubleArray___nonzero__(self)
def __bool__(self):
return _AHT.doubleArray___bool__(self)
def __len__(self):
return _AHT.doubleArray___len__(self)
def __getslice__(self, i, j):
return _AHT.doubleArray___getslice__(self, i, j)
def __setslice__(self, *args):
return _AHT.doubleArray___setslice__(self, *args)
def __delslice__(self, i, j):
return _AHT.doubleArray___delslice__(self, i, j)
def __delitem__(self, *args):
return _AHT.doubleArray___delitem__(self, *args)
def __getitem__(self, *args):
return _AHT.doubleArray___getitem__(self, *args)
def __setitem__(self, *args):
return _AHT.doubleArray___setitem__(self, *args)
def pop(self):
return _AHT.doubleArray_pop(self)
def append(self, x):
return _AHT.doubleArray_append(self, x)
def empty(self):
return _AHT.doubleArray_empty(self)
def size(self):
return _AHT.doubleArray_size(self)
def swap(self, v):
return _AHT.doubleArray_swap(self, v)
def begin(self):
return _AHT.doubleArray_begin(self)
def end(self):
return _AHT.doubleArray_end(self)
def rbegin(self):
return _AHT.doubleArray_rbegin(self)
def rend(self):
return _AHT.doubleArray_rend(self)
def clear(self):
return _AHT.doubleArray_clear(self)
def get_allocator(self):
return _AHT.doubleArray_get_allocator(self)
def pop_back(self):
return _AHT.doubleArray_pop_back(self)
def erase(self, *args):
return _AHT.doubleArray_erase(self, *args)
def __init__(self, *args):
_AHT.doubleArray_swiginit(self, _AHT.new_doubleArray(*args))
def push_back(self, x):
return _AHT.doubleArray_push_back(self, x)
def front(self):
return _AHT.doubleArray_front(self)
def back(self):
return _AHT.doubleArray_back(self)
def assign(self, n, x):
return _AHT.doubleArray_assign(self, n, x)
def resize(self, *args):
return _AHT.doubleArray_resize(self, *args)
def insert(self, *args):
return _AHT.doubleArray_insert(self, *args)
def reserve(self, n):
return _AHT.doubleArray_reserve(self, n)
def capacity(self):
return _AHT.doubleArray_capacity(self)
__swig_destroy__ = _AHT.delete_doubleArray
# Register doubleArray in _AHT:
_AHT.doubleArray_swigregister(doubleArray)
_array_map["double"] =doubleArray
class _Matx_double_2_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_double_2_1_rows
cols = _AHT._Matx_double_2_1_cols
channels = _AHT._Matx_double_2_1_channels
shortdim = _AHT._Matx_double_2_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_double_2_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_double_2_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_double_2_1_ones()
@staticmethod
def eye():
return _AHT._Matx_double_2_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_double_2_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_double_2_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_double_2_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_double_2_1_ddot(self, v)
def t(self):
return _AHT._Matx_double_2_1_t(self)
def mul(self, a):
return _AHT._Matx_double_2_1_mul(self, a)
def div(self, a):
return _AHT._Matx_double_2_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_double_2_1___call__(self, i, j)
val = property(_AHT._Matx_double_2_1_val_get, _AHT._Matx_double_2_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_double_2_1_swiginit(self, _AHT.new__Matx_double_2_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_double_2_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_double_2_1
# Register _Matx_double_2_1 in _AHT:
_AHT._Matx_double_2_1_swigregister(_Matx_double_2_1)
def _Matx_double_2_1_all(alpha):
return _AHT._Matx_double_2_1_all(alpha)
def _Matx_double_2_1_zeros():
return _AHT._Matx_double_2_1_zeros()
def _Matx_double_2_1_ones():
return _AHT._Matx_double_2_1_ones()
def _Matx_double_2_1_eye():
return _AHT._Matx_double_2_1_eye()
def _Matx_double_2_1_randu(a, b):
return _AHT._Matx_double_2_1_randu(a, b)
def _Matx_double_2_1_randn(a, b):
return _AHT._Matx_double_2_1_randn(a, b)
Matx21d = _Matx_double_2_1
class _Vec_double_2(_Matx_double_2_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_double_2_channels
@staticmethod
def all(alpha):
return _AHT._Vec_double_2_all(alpha)
def mul(self, v):
return _AHT._Vec_double_2_mul(self, v)
def __call__(self, i):
return _AHT._Vec_double_2___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_double_2_swiginit(self, _AHT.new__Vec_double_2(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_double_2___str__(self)
__swig_destroy__ = _AHT.delete__Vec_double_2
# Register _Vec_double_2 in _AHT:
_AHT._Vec_double_2_swigregister(_Vec_double_2)
def _Vec_double_2_all(alpha):
return _AHT._Vec_double_2_all(alpha)
class _DataType_Vec_double_2(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_double_2_generic_type
channels = _AHT._DataType_Vec_double_2_channels
fmt = _AHT._DataType_Vec_double_2_fmt
def __init__(self):
_AHT._DataType_Vec_double_2_swiginit(self, _AHT.new__DataType_Vec_double_2())
__swig_destroy__ = _AHT.delete__DataType_Vec_double_2
# Register _DataType_Vec_double_2 in _AHT:
_AHT._DataType_Vec_double_2_swigregister(_DataType_Vec_double_2)
Vec2d = _Vec_double_2
DataType_Vec2d = _DataType_Vec_double_2
class _Matx_double_3_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_double_3_1_rows
cols = _AHT._Matx_double_3_1_cols
channels = _AHT._Matx_double_3_1_channels
shortdim = _AHT._Matx_double_3_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_double_3_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_double_3_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_double_3_1_ones()
@staticmethod
def eye():
return _AHT._Matx_double_3_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_double_3_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_double_3_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_double_3_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_double_3_1_ddot(self, v)
def t(self):
return _AHT._Matx_double_3_1_t(self)
def mul(self, a):
return _AHT._Matx_double_3_1_mul(self, a)
def div(self, a):
return _AHT._Matx_double_3_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_double_3_1___call__(self, i, j)
val = property(_AHT._Matx_double_3_1_val_get, _AHT._Matx_double_3_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_double_3_1_swiginit(self, _AHT.new__Matx_double_3_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_double_3_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_double_3_1
# Register _Matx_double_3_1 in _AHT:
_AHT._Matx_double_3_1_swigregister(_Matx_double_3_1)
def _Matx_double_3_1_all(alpha):
return _AHT._Matx_double_3_1_all(alpha)
def _Matx_double_3_1_zeros():
return _AHT._Matx_double_3_1_zeros()
def _Matx_double_3_1_ones():
return _AHT._Matx_double_3_1_ones()
def _Matx_double_3_1_eye():
return _AHT._Matx_double_3_1_eye()
def _Matx_double_3_1_randu(a, b):
return _AHT._Matx_double_3_1_randu(a, b)
def _Matx_double_3_1_randn(a, b):
return _AHT._Matx_double_3_1_randn(a, b)
Matx31d = _Matx_double_3_1
class _Vec_double_3(_Matx_double_3_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_double_3_channels
@staticmethod
def all(alpha):
return _AHT._Vec_double_3_all(alpha)
def mul(self, v):
return _AHT._Vec_double_3_mul(self, v)
def __call__(self, i):
return _AHT._Vec_double_3___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_double_3_swiginit(self, _AHT.new__Vec_double_3(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_double_3___str__(self)
__swig_destroy__ = _AHT.delete__Vec_double_3
# Register _Vec_double_3 in _AHT:
_AHT._Vec_double_3_swigregister(_Vec_double_3)
def _Vec_double_3_all(alpha):
return _AHT._Vec_double_3_all(alpha)
class _DataType_Vec_double_3(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_double_3_generic_type
channels = _AHT._DataType_Vec_double_3_channels
fmt = _AHT._DataType_Vec_double_3_fmt
def __init__(self):
_AHT._DataType_Vec_double_3_swiginit(self, _AHT.new__DataType_Vec_double_3())
__swig_destroy__ = _AHT.delete__DataType_Vec_double_3
# Register _DataType_Vec_double_3 in _AHT:
_AHT._DataType_Vec_double_3_swigregister(_DataType_Vec_double_3)
Vec3d = _Vec_double_3
DataType_Vec3d = _DataType_Vec_double_3
class _Matx_double_4_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_double_4_1_rows
cols = _AHT._Matx_double_4_1_cols
channels = _AHT._Matx_double_4_1_channels
shortdim = _AHT._Matx_double_4_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_double_4_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_double_4_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_double_4_1_ones()
@staticmethod
def eye():
return _AHT._Matx_double_4_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_double_4_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_double_4_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_double_4_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_double_4_1_ddot(self, v)
def t(self):
return _AHT._Matx_double_4_1_t(self)
def mul(self, a):
return _AHT._Matx_double_4_1_mul(self, a)
def div(self, a):
return _AHT._Matx_double_4_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_double_4_1___call__(self, i, j)
val = property(_AHT._Matx_double_4_1_val_get, _AHT._Matx_double_4_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_double_4_1_swiginit(self, _AHT.new__Matx_double_4_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_double_4_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_double_4_1
# Register _Matx_double_4_1 in _AHT:
_AHT._Matx_double_4_1_swigregister(_Matx_double_4_1)
def _Matx_double_4_1_all(alpha):
return _AHT._Matx_double_4_1_all(alpha)
def _Matx_double_4_1_zeros():
return _AHT._Matx_double_4_1_zeros()
def _Matx_double_4_1_ones():
return _AHT._Matx_double_4_1_ones()
def _Matx_double_4_1_eye():
return _AHT._Matx_double_4_1_eye()
def _Matx_double_4_1_randu(a, b):
return _AHT._Matx_double_4_1_randu(a, b)
def _Matx_double_4_1_randn(a, b):
return _AHT._Matx_double_4_1_randn(a, b)
Matx41d = _Matx_double_4_1
class _Vec_double_4(_Matx_double_4_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_double_4_channels
@staticmethod
def all(alpha):
return _AHT._Vec_double_4_all(alpha)
def mul(self, v):
return _AHT._Vec_double_4_mul(self, v)
def __call__(self, i):
return _AHT._Vec_double_4___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_double_4_swiginit(self, _AHT.new__Vec_double_4(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_double_4___str__(self)
__swig_destroy__ = _AHT.delete__Vec_double_4
# Register _Vec_double_4 in _AHT:
_AHT._Vec_double_4_swigregister(_Vec_double_4)
def _Vec_double_4_all(alpha):
return _AHT._Vec_double_4_all(alpha)
class _DataType_Vec_double_4(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_double_4_generic_type
channels = _AHT._DataType_Vec_double_4_channels
fmt = _AHT._DataType_Vec_double_4_fmt
def __init__(self):
_AHT._DataType_Vec_double_4_swiginit(self, _AHT.new__DataType_Vec_double_4())
__swig_destroy__ = _AHT.delete__DataType_Vec_double_4
# Register _DataType_Vec_double_4 in _AHT:
_AHT._DataType_Vec_double_4_swigregister(_DataType_Vec_double_4)
Vec4d = _Vec_double_4
DataType_Vec4d = _DataType_Vec_double_4
class _Matx_double_6_1(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_double_6_1_rows
cols = _AHT._Matx_double_6_1_cols
channels = _AHT._Matx_double_6_1_channels
shortdim = _AHT._Matx_double_6_1_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_double_6_1_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_double_6_1_zeros()
@staticmethod
def ones():
return _AHT._Matx_double_6_1_ones()
@staticmethod
def eye():
return _AHT._Matx_double_6_1_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_double_6_1_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_double_6_1_randn(a, b)
def dot(self, v):
return _AHT._Matx_double_6_1_dot(self, v)
def ddot(self, v):
return _AHT._Matx_double_6_1_ddot(self, v)
def t(self):
return _AHT._Matx_double_6_1_t(self)
def mul(self, a):
return _AHT._Matx_double_6_1_mul(self, a)
def div(self, a):
return _AHT._Matx_double_6_1_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_double_6_1___call__(self, i, j)
val = property(_AHT._Matx_double_6_1_val_get, _AHT._Matx_double_6_1_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_double_6_1_swiginit(self, _AHT.new__Matx_double_6_1(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_double_6_1___str__(self)
__swig_destroy__ = _AHT.delete__Matx_double_6_1
# Register _Matx_double_6_1 in _AHT:
_AHT._Matx_double_6_1_swigregister(_Matx_double_6_1)
def _Matx_double_6_1_all(alpha):
return _AHT._Matx_double_6_1_all(alpha)
def _Matx_double_6_1_zeros():
return _AHT._Matx_double_6_1_zeros()
def _Matx_double_6_1_ones():
return _AHT._Matx_double_6_1_ones()
def _Matx_double_6_1_eye():
return _AHT._Matx_double_6_1_eye()
def _Matx_double_6_1_randu(a, b):
return _AHT._Matx_double_6_1_randu(a, b)
def _Matx_double_6_1_randn(a, b):
return _AHT._Matx_double_6_1_randn(a, b)
Matx61d = _Matx_double_6_1
class _Vec_double_6(_Matx_double_6_1):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
channels = _AHT._Vec_double_6_channels
@staticmethod
def all(alpha):
return _AHT._Vec_double_6_all(alpha)
def mul(self, v):
return _AHT._Vec_double_6_mul(self, v)
def __call__(self, i):
return _AHT._Vec_double_6___call__(self, i)
import re
_re_pattern = re.compile("^_Vec_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
array = _array_map[value_type](rows)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Vec_double_6_swiginit(self, _AHT.new__Vec_double_6(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
return {"shape": (rows, 1),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
if not isinstance(key, int):
raise TypeError
if key >= rows:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Vec_double_6___str__(self)
__swig_destroy__ = _AHT.delete__Vec_double_6
# Register _Vec_double_6 in _AHT:
_AHT._Vec_double_6_swigregister(_Vec_double_6)
def _Vec_double_6_all(alpha):
return _AHT._Vec_double_6_all(alpha)
class _DataType_Vec_double_6(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
generic_type = _AHT._DataType_Vec_double_6_generic_type
channels = _AHT._DataType_Vec_double_6_channels
fmt = _AHT._DataType_Vec_double_6_fmt
def __init__(self):
_AHT._DataType_Vec_double_6_swiginit(self, _AHT.new__DataType_Vec_double_6())
__swig_destroy__ = _AHT.delete__DataType_Vec_double_6
# Register _DataType_Vec_double_6 in _AHT:
_AHT._DataType_Vec_double_6_swigregister(_DataType_Vec_double_6)
Vec6d = _Vec_double_6
DataType_Vec6d = _DataType_Vec_double_6
class _mat__np_array_constructor(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self):
_AHT._mat__np_array_constructor_swiginit(self, _AHT.new__mat__np_array_constructor())
__swig_destroy__ = _AHT.delete__mat__np_array_constructor
# Register _mat__np_array_constructor in _AHT:
_AHT._mat__np_array_constructor_swigregister(_mat__np_array_constructor)
def _depthToDtype(depth):
return _AHT._depthToDtype(depth)
def _toCvType(dtype, nChannel):
return _AHT._toCvType(dtype, nChannel)
class _cv_numpy_sizeof_uchar(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_uchar_value
def __init__(self):
_AHT._cv_numpy_sizeof_uchar_swiginit(self, _AHT.new__cv_numpy_sizeof_uchar())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_uchar
# Register _cv_numpy_sizeof_uchar in _AHT:
_AHT._cv_numpy_sizeof_uchar_swigregister(_cv_numpy_sizeof_uchar)
if _cv_numpy_sizeof_uchar.value == 1:
_cv_numpy_typestr_map["uchar"] = "|" +"u" + "1"
else:
_cv_numpy_typestr_map["uchar"] = _cv_numpy_endianess +"u" + str(_cv_numpy_sizeof_uchar.value)
class _Mat__uchar(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__uchar_create(self, *args)
def cross(self, m):
return _AHT._Mat__uchar_cross(self, m)
def row(self, y):
return _AHT._Mat__uchar_row(self, y)
def col(self, x):
return _AHT._Mat__uchar_col(self, x)
def diag(self, d=0):
return _AHT._Mat__uchar_diag(self, d)
def clone(self):
return _AHT._Mat__uchar_clone(self)
def elemSize(self):
return _AHT._Mat__uchar_elemSize(self)
def elemSize1(self):
return _AHT._Mat__uchar_elemSize1(self)
def type(self):
return _AHT._Mat__uchar_type(self)
def depth(self):
return _AHT._Mat__uchar_depth(self)
def channels(self):
return _AHT._Mat__uchar_channels(self)
def step1(self, i=0):
return _AHT._Mat__uchar_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__uchar_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__uchar_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__uchar___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__uchar_swiginit(self, _AHT.new__Mat__uchar(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__uchar___str__(self)
__swig_destroy__ = _AHT.delete__Mat__uchar
# Register _Mat__uchar in _AHT:
_AHT._Mat__uchar_swigregister(_Mat__uchar)
Mat1b = _Mat__uchar
class _cv_numpy_sizeof_Vec2b(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec2b_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec2b_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec2b())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec2b
# Register _cv_numpy_sizeof_Vec2b in _AHT:
_AHT._cv_numpy_sizeof_Vec2b_swigregister(_cv_numpy_sizeof_Vec2b)
if _cv_numpy_sizeof_Vec2b.value == 1:
_cv_numpy_typestr_map["Vec2b"] = "|" +"u" + "1"
else:
_cv_numpy_typestr_map["Vec2b"] = _cv_numpy_endianess +"u" + str(_cv_numpy_sizeof_Vec2b.value)
class _Mat__Vec2b(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec2b_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec2b_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec2b_row(self, y)
def col(self, x):
return _AHT._Mat__Vec2b_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec2b_diag(self, d)
def clone(self):
return _AHT._Mat__Vec2b_clone(self)
def elemSize(self):
return _AHT._Mat__Vec2b_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec2b_elemSize1(self)
def type(self):
return _AHT._Mat__Vec2b_type(self)
def depth(self):
return _AHT._Mat__Vec2b_depth(self)
def channels(self):
return _AHT._Mat__Vec2b_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec2b_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec2b_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec2b_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec2b___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec2b_swiginit(self, _AHT.new__Mat__Vec2b(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec2b___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec2b
# Register _Mat__Vec2b in _AHT:
_AHT._Mat__Vec2b_swigregister(_Mat__Vec2b)
Mat2b = _Mat__Vec2b
class _cv_numpy_sizeof_Vec3b(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec3b_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec3b_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec3b())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec3b
# Register _cv_numpy_sizeof_Vec3b in _AHT:
_AHT._cv_numpy_sizeof_Vec3b_swigregister(_cv_numpy_sizeof_Vec3b)
if _cv_numpy_sizeof_Vec3b.value == 1:
_cv_numpy_typestr_map["Vec3b"] = "|" +"u" + "1"
else:
_cv_numpy_typestr_map["Vec3b"] = _cv_numpy_endianess +"u" + str(_cv_numpy_sizeof_Vec3b.value)
class _Mat__Vec3b(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec3b_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec3b_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec3b_row(self, y)
def col(self, x):
return _AHT._Mat__Vec3b_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec3b_diag(self, d)
def clone(self):
return _AHT._Mat__Vec3b_clone(self)
def elemSize(self):
return _AHT._Mat__Vec3b_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec3b_elemSize1(self)
def type(self):
return _AHT._Mat__Vec3b_type(self)
def depth(self):
return _AHT._Mat__Vec3b_depth(self)
def channels(self):
return _AHT._Mat__Vec3b_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec3b_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec3b_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec3b_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec3b___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec3b_swiginit(self, _AHT.new__Mat__Vec3b(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec3b___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec3b
# Register _Mat__Vec3b in _AHT:
_AHT._Mat__Vec3b_swigregister(_Mat__Vec3b)
Mat3b = _Mat__Vec3b
class _cv_numpy_sizeof_Vec4b(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec4b_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec4b_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec4b())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec4b
# Register _cv_numpy_sizeof_Vec4b in _AHT:
_AHT._cv_numpy_sizeof_Vec4b_swigregister(_cv_numpy_sizeof_Vec4b)
if _cv_numpy_sizeof_Vec4b.value == 1:
_cv_numpy_typestr_map["Vec4b"] = "|" +"u" + "1"
else:
_cv_numpy_typestr_map["Vec4b"] = _cv_numpy_endianess +"u" + str(_cv_numpy_sizeof_Vec4b.value)
class _Mat__Vec4b(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec4b_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec4b_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec4b_row(self, y)
def col(self, x):
return _AHT._Mat__Vec4b_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec4b_diag(self, d)
def clone(self):
return _AHT._Mat__Vec4b_clone(self)
def elemSize(self):
return _AHT._Mat__Vec4b_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec4b_elemSize1(self)
def type(self):
return _AHT._Mat__Vec4b_type(self)
def depth(self):
return _AHT._Mat__Vec4b_depth(self)
def channels(self):
return _AHT._Mat__Vec4b_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec4b_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec4b_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec4b_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec4b___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec4b_swiginit(self, _AHT.new__Mat__Vec4b(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec4b___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec4b
# Register _Mat__Vec4b in _AHT:
_AHT._Mat__Vec4b_swigregister(_Mat__Vec4b)
Mat4b = _Mat__Vec4b
class _Mat__short(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__short_create(self, *args)
def cross(self, m):
return _AHT._Mat__short_cross(self, m)
def row(self, y):
return _AHT._Mat__short_row(self, y)
def col(self, x):
return _AHT._Mat__short_col(self, x)
def diag(self, d=0):
return _AHT._Mat__short_diag(self, d)
def clone(self):
return _AHT._Mat__short_clone(self)
def elemSize(self):
return _AHT._Mat__short_elemSize(self)
def elemSize1(self):
return _AHT._Mat__short_elemSize1(self)
def type(self):
return _AHT._Mat__short_type(self)
def depth(self):
return _AHT._Mat__short_depth(self)
def channels(self):
return _AHT._Mat__short_channels(self)
def step1(self, i=0):
return _AHT._Mat__short_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__short_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__short_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__short___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__short_swiginit(self, _AHT.new__Mat__short(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__short___str__(self)
__swig_destroy__ = _AHT.delete__Mat__short
# Register _Mat__short in _AHT:
_AHT._Mat__short_swigregister(_Mat__short)
Mat1s = _Mat__short
class _cv_numpy_sizeof_Vec2s(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec2s_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec2s_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec2s())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec2s
# Register _cv_numpy_sizeof_Vec2s in _AHT:
_AHT._cv_numpy_sizeof_Vec2s_swigregister(_cv_numpy_sizeof_Vec2s)
if _cv_numpy_sizeof_Vec2s.value == 1:
_cv_numpy_typestr_map["Vec2s"] = "|" +"i" + "1"
else:
_cv_numpy_typestr_map["Vec2s"] = _cv_numpy_endianess +"i" + str(_cv_numpy_sizeof_Vec2s.value)
class _Mat__Vec2s(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec2s_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec2s_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec2s_row(self, y)
def col(self, x):
return _AHT._Mat__Vec2s_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec2s_diag(self, d)
def clone(self):
return _AHT._Mat__Vec2s_clone(self)
def elemSize(self):
return _AHT._Mat__Vec2s_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec2s_elemSize1(self)
def type(self):
return _AHT._Mat__Vec2s_type(self)
def depth(self):
return _AHT._Mat__Vec2s_depth(self)
def channels(self):
return _AHT._Mat__Vec2s_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec2s_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec2s_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec2s_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec2s___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec2s_swiginit(self, _AHT.new__Mat__Vec2s(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec2s___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec2s
# Register _Mat__Vec2s in _AHT:
_AHT._Mat__Vec2s_swigregister(_Mat__Vec2s)
Mat2s = _Mat__Vec2s
class _cv_numpy_sizeof_Vec3s(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec3s_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec3s_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec3s())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec3s
# Register _cv_numpy_sizeof_Vec3s in _AHT:
_AHT._cv_numpy_sizeof_Vec3s_swigregister(_cv_numpy_sizeof_Vec3s)
if _cv_numpy_sizeof_Vec3s.value == 1:
_cv_numpy_typestr_map["Vec3s"] = "|" +"i" + "1"
else:
_cv_numpy_typestr_map["Vec3s"] = _cv_numpy_endianess +"i" + str(_cv_numpy_sizeof_Vec3s.value)
class _Mat__Vec3s(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec3s_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec3s_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec3s_row(self, y)
def col(self, x):
return _AHT._Mat__Vec3s_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec3s_diag(self, d)
def clone(self):
return _AHT._Mat__Vec3s_clone(self)
def elemSize(self):
return _AHT._Mat__Vec3s_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec3s_elemSize1(self)
def type(self):
return _AHT._Mat__Vec3s_type(self)
def depth(self):
return _AHT._Mat__Vec3s_depth(self)
def channels(self):
return _AHT._Mat__Vec3s_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec3s_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec3s_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec3s_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec3s___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec3s_swiginit(self, _AHT.new__Mat__Vec3s(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec3s___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec3s
# Register _Mat__Vec3s in _AHT:
_AHT._Mat__Vec3s_swigregister(_Mat__Vec3s)
Mat3s = _Mat__Vec3s
class _cv_numpy_sizeof_Vec4s(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec4s_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec4s_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec4s())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec4s
# Register _cv_numpy_sizeof_Vec4s in _AHT:
_AHT._cv_numpy_sizeof_Vec4s_swigregister(_cv_numpy_sizeof_Vec4s)
if _cv_numpy_sizeof_Vec4s.value == 1:
_cv_numpy_typestr_map["Vec4s"] = "|" +"i" + "1"
else:
_cv_numpy_typestr_map["Vec4s"] = _cv_numpy_endianess +"i" + str(_cv_numpy_sizeof_Vec4s.value)
class _Mat__Vec4s(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec4s_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec4s_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec4s_row(self, y)
def col(self, x):
return _AHT._Mat__Vec4s_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec4s_diag(self, d)
def clone(self):
return _AHT._Mat__Vec4s_clone(self)
def elemSize(self):
return _AHT._Mat__Vec4s_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec4s_elemSize1(self)
def type(self):
return _AHT._Mat__Vec4s_type(self)
def depth(self):
return _AHT._Mat__Vec4s_depth(self)
def channels(self):
return _AHT._Mat__Vec4s_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec4s_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec4s_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec4s_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec4s___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec4s_swiginit(self, _AHT.new__Mat__Vec4s(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec4s___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec4s
# Register _Mat__Vec4s in _AHT:
_AHT._Mat__Vec4s_swigregister(_Mat__Vec4s)
Mat4s = _Mat__Vec4s
class _Mat__ushort(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__ushort_create(self, *args)
def cross(self, m):
return _AHT._Mat__ushort_cross(self, m)
def row(self, y):
return _AHT._Mat__ushort_row(self, y)
def col(self, x):
return _AHT._Mat__ushort_col(self, x)
def diag(self, d=0):
return _AHT._Mat__ushort_diag(self, d)
def clone(self):
return _AHT._Mat__ushort_clone(self)
def elemSize(self):
return _AHT._Mat__ushort_elemSize(self)
def elemSize1(self):
return _AHT._Mat__ushort_elemSize1(self)
def type(self):
return _AHT._Mat__ushort_type(self)
def depth(self):
return _AHT._Mat__ushort_depth(self)
def channels(self):
return _AHT._Mat__ushort_channels(self)
def step1(self, i=0):
return _AHT._Mat__ushort_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__ushort_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__ushort_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__ushort___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__ushort_swiginit(self, _AHT.new__Mat__ushort(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__ushort___str__(self)
__swig_destroy__ = _AHT.delete__Mat__ushort
# Register _Mat__ushort in _AHT:
_AHT._Mat__ushort_swigregister(_Mat__ushort)
Mat1w = _Mat__ushort
class _cv_numpy_sizeof_Vec2w(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec2w_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec2w_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec2w())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec2w
# Register _cv_numpy_sizeof_Vec2w in _AHT:
_AHT._cv_numpy_sizeof_Vec2w_swigregister(_cv_numpy_sizeof_Vec2w)
if _cv_numpy_sizeof_Vec2w.value == 1:
_cv_numpy_typestr_map["Vec2w"] = "|" +"u" + "1"
else:
_cv_numpy_typestr_map["Vec2w"] = _cv_numpy_endianess +"u" + str(_cv_numpy_sizeof_Vec2w.value)
class _Mat__Vec2w(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec2w_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec2w_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec2w_row(self, y)
def col(self, x):
return _AHT._Mat__Vec2w_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec2w_diag(self, d)
def clone(self):
return _AHT._Mat__Vec2w_clone(self)
def elemSize(self):
return _AHT._Mat__Vec2w_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec2w_elemSize1(self)
def type(self):
return _AHT._Mat__Vec2w_type(self)
def depth(self):
return _AHT._Mat__Vec2w_depth(self)
def channels(self):
return _AHT._Mat__Vec2w_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec2w_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec2w_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec2w_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec2w___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec2w_swiginit(self, _AHT.new__Mat__Vec2w(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec2w___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec2w
# Register _Mat__Vec2w in _AHT:
_AHT._Mat__Vec2w_swigregister(_Mat__Vec2w)
Mat2w = _Mat__Vec2w
class _cv_numpy_sizeof_Vec3w(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec3w_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec3w_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec3w())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec3w
# Register _cv_numpy_sizeof_Vec3w in _AHT:
_AHT._cv_numpy_sizeof_Vec3w_swigregister(_cv_numpy_sizeof_Vec3w)
if _cv_numpy_sizeof_Vec3w.value == 1:
_cv_numpy_typestr_map["Vec3w"] = "|" +"u" + "1"
else:
_cv_numpy_typestr_map["Vec3w"] = _cv_numpy_endianess +"u" + str(_cv_numpy_sizeof_Vec3w.value)
class _Mat__Vec3w(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec3w_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec3w_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec3w_row(self, y)
def col(self, x):
return _AHT._Mat__Vec3w_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec3w_diag(self, d)
def clone(self):
return _AHT._Mat__Vec3w_clone(self)
def elemSize(self):
return _AHT._Mat__Vec3w_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec3w_elemSize1(self)
def type(self):
return _AHT._Mat__Vec3w_type(self)
def depth(self):
return _AHT._Mat__Vec3w_depth(self)
def channels(self):
return _AHT._Mat__Vec3w_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec3w_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec3w_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec3w_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec3w___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec3w_swiginit(self, _AHT.new__Mat__Vec3w(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec3w___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec3w
# Register _Mat__Vec3w in _AHT:
_AHT._Mat__Vec3w_swigregister(_Mat__Vec3w)
Mat3w = _Mat__Vec3w
class _cv_numpy_sizeof_Vec4w(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec4w_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec4w_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec4w())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec4w
# Register _cv_numpy_sizeof_Vec4w in _AHT:
_AHT._cv_numpy_sizeof_Vec4w_swigregister(_cv_numpy_sizeof_Vec4w)
if _cv_numpy_sizeof_Vec4w.value == 1:
_cv_numpy_typestr_map["Vec4w"] = "|" +"u" + "1"
else:
_cv_numpy_typestr_map["Vec4w"] = _cv_numpy_endianess +"u" + str(_cv_numpy_sizeof_Vec4w.value)
class _Mat__Vec4w(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec4w_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec4w_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec4w_row(self, y)
def col(self, x):
return _AHT._Mat__Vec4w_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec4w_diag(self, d)
def clone(self):
return _AHT._Mat__Vec4w_clone(self)
def elemSize(self):
return _AHT._Mat__Vec4w_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec4w_elemSize1(self)
def type(self):
return _AHT._Mat__Vec4w_type(self)
def depth(self):
return _AHT._Mat__Vec4w_depth(self)
def channels(self):
return _AHT._Mat__Vec4w_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec4w_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec4w_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec4w_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec4w___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec4w_swiginit(self, _AHT.new__Mat__Vec4w(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec4w___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec4w
# Register _Mat__Vec4w in _AHT:
_AHT._Mat__Vec4w_swigregister(_Mat__Vec4w)
Mat4w = _Mat__Vec4w
class _Mat__int(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__int_create(self, *args)
def cross(self, m):
return _AHT._Mat__int_cross(self, m)
def row(self, y):
return _AHT._Mat__int_row(self, y)
def col(self, x):
return _AHT._Mat__int_col(self, x)
def diag(self, d=0):
return _AHT._Mat__int_diag(self, d)
def clone(self):
return _AHT._Mat__int_clone(self)
def elemSize(self):
return _AHT._Mat__int_elemSize(self)
def elemSize1(self):
return _AHT._Mat__int_elemSize1(self)
def type(self):
return _AHT._Mat__int_type(self)
def depth(self):
return _AHT._Mat__int_depth(self)
def channels(self):
return _AHT._Mat__int_channels(self)
def step1(self, i=0):
return _AHT._Mat__int_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__int_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__int_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__int___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__int_swiginit(self, _AHT.new__Mat__int(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__int___str__(self)
__swig_destroy__ = _AHT.delete__Mat__int
# Register _Mat__int in _AHT:
_AHT._Mat__int_swigregister(_Mat__int)
Mat1i = _Mat__int
class _cv_numpy_sizeof_Vec2i(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec2i_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec2i_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec2i())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec2i
# Register _cv_numpy_sizeof_Vec2i in _AHT:
_AHT._cv_numpy_sizeof_Vec2i_swigregister(_cv_numpy_sizeof_Vec2i)
if _cv_numpy_sizeof_Vec2i.value == 1:
_cv_numpy_typestr_map["Vec2i"] = "|" +"i" + "1"
else:
_cv_numpy_typestr_map["Vec2i"] = _cv_numpy_endianess +"i" + str(_cv_numpy_sizeof_Vec2i.value)
class _Mat__Vec2i(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec2i_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec2i_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec2i_row(self, y)
def col(self, x):
return _AHT._Mat__Vec2i_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec2i_diag(self, d)
def clone(self):
return _AHT._Mat__Vec2i_clone(self)
def elemSize(self):
return _AHT._Mat__Vec2i_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec2i_elemSize1(self)
def type(self):
return _AHT._Mat__Vec2i_type(self)
def depth(self):
return _AHT._Mat__Vec2i_depth(self)
def channels(self):
return _AHT._Mat__Vec2i_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec2i_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec2i_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec2i_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec2i___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec2i_swiginit(self, _AHT.new__Mat__Vec2i(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec2i___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec2i
# Register _Mat__Vec2i in _AHT:
_AHT._Mat__Vec2i_swigregister(_Mat__Vec2i)
Mat2i = _Mat__Vec2i
class _cv_numpy_sizeof_Vec3i(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec3i_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec3i_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec3i())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec3i
# Register _cv_numpy_sizeof_Vec3i in _AHT:
_AHT._cv_numpy_sizeof_Vec3i_swigregister(_cv_numpy_sizeof_Vec3i)
if _cv_numpy_sizeof_Vec3i.value == 1:
_cv_numpy_typestr_map["Vec3i"] = "|" +"i" + "1"
else:
_cv_numpy_typestr_map["Vec3i"] = _cv_numpy_endianess +"i" + str(_cv_numpy_sizeof_Vec3i.value)
class _Mat__Vec3i(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec3i_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec3i_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec3i_row(self, y)
def col(self, x):
return _AHT._Mat__Vec3i_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec3i_diag(self, d)
def clone(self):
return _AHT._Mat__Vec3i_clone(self)
def elemSize(self):
return _AHT._Mat__Vec3i_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec3i_elemSize1(self)
def type(self):
return _AHT._Mat__Vec3i_type(self)
def depth(self):
return _AHT._Mat__Vec3i_depth(self)
def channels(self):
return _AHT._Mat__Vec3i_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec3i_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec3i_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec3i_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec3i___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec3i_swiginit(self, _AHT.new__Mat__Vec3i(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec3i___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec3i
# Register _Mat__Vec3i in _AHT:
_AHT._Mat__Vec3i_swigregister(_Mat__Vec3i)
Mat3i = _Mat__Vec3i
class _cv_numpy_sizeof_Vec4i(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec4i_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec4i_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec4i())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec4i
# Register _cv_numpy_sizeof_Vec4i in _AHT:
_AHT._cv_numpy_sizeof_Vec4i_swigregister(_cv_numpy_sizeof_Vec4i)
if _cv_numpy_sizeof_Vec4i.value == 1:
_cv_numpy_typestr_map["Vec4i"] = "|" +"i" + "1"
else:
_cv_numpy_typestr_map["Vec4i"] = _cv_numpy_endianess +"i" + str(_cv_numpy_sizeof_Vec4i.value)
class _Mat__Vec4i(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec4i_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec4i_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec4i_row(self, y)
def col(self, x):
return _AHT._Mat__Vec4i_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec4i_diag(self, d)
def clone(self):
return _AHT._Mat__Vec4i_clone(self)
def elemSize(self):
return _AHT._Mat__Vec4i_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec4i_elemSize1(self)
def type(self):
return _AHT._Mat__Vec4i_type(self)
def depth(self):
return _AHT._Mat__Vec4i_depth(self)
def channels(self):
return _AHT._Mat__Vec4i_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec4i_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec4i_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec4i_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec4i___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec4i_swiginit(self, _AHT.new__Mat__Vec4i(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec4i___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec4i
# Register _Mat__Vec4i in _AHT:
_AHT._Mat__Vec4i_swigregister(_Mat__Vec4i)
Mat4i = _Mat__Vec4i
class _Mat__float(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__float_create(self, *args)
def cross(self, m):
return _AHT._Mat__float_cross(self, m)
def row(self, y):
return _AHT._Mat__float_row(self, y)
def col(self, x):
return _AHT._Mat__float_col(self, x)
def diag(self, d=0):
return _AHT._Mat__float_diag(self, d)
def clone(self):
return _AHT._Mat__float_clone(self)
def elemSize(self):
return _AHT._Mat__float_elemSize(self)
def elemSize1(self):
return _AHT._Mat__float_elemSize1(self)
def type(self):
return _AHT._Mat__float_type(self)
def depth(self):
return _AHT._Mat__float_depth(self)
def channels(self):
return _AHT._Mat__float_channels(self)
def step1(self, i=0):
return _AHT._Mat__float_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__float_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__float_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__float___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__float_swiginit(self, _AHT.new__Mat__float(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__float___str__(self)
__swig_destroy__ = _AHT.delete__Mat__float
# Register _Mat__float in _AHT:
_AHT._Mat__float_swigregister(_Mat__float)
Mat1f = _Mat__float
class _cv_numpy_sizeof_Vec2f(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec2f_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec2f_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec2f())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec2f
# Register _cv_numpy_sizeof_Vec2f in _AHT:
_AHT._cv_numpy_sizeof_Vec2f_swigregister(_cv_numpy_sizeof_Vec2f)
if _cv_numpy_sizeof_Vec2f.value == 1:
_cv_numpy_typestr_map["Vec2f"] = "|" +"f" + "1"
else:
_cv_numpy_typestr_map["Vec2f"] = _cv_numpy_endianess +"f" + str(_cv_numpy_sizeof_Vec2f.value)
class _Mat__Vec2f(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec2f_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec2f_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec2f_row(self, y)
def col(self, x):
return _AHT._Mat__Vec2f_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec2f_diag(self, d)
def clone(self):
return _AHT._Mat__Vec2f_clone(self)
def elemSize(self):
return _AHT._Mat__Vec2f_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec2f_elemSize1(self)
def type(self):
return _AHT._Mat__Vec2f_type(self)
def depth(self):
return _AHT._Mat__Vec2f_depth(self)
def channels(self):
return _AHT._Mat__Vec2f_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec2f_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec2f_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec2f_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec2f___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec2f_swiginit(self, _AHT.new__Mat__Vec2f(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec2f___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec2f
# Register _Mat__Vec2f in _AHT:
_AHT._Mat__Vec2f_swigregister(_Mat__Vec2f)
Mat2f = _Mat__Vec2f
class _cv_numpy_sizeof_Vec3f(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec3f_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec3f_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec3f())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec3f
# Register _cv_numpy_sizeof_Vec3f in _AHT:
_AHT._cv_numpy_sizeof_Vec3f_swigregister(_cv_numpy_sizeof_Vec3f)
if _cv_numpy_sizeof_Vec3f.value == 1:
_cv_numpy_typestr_map["Vec3f"] = "|" +"f" + "1"
else:
_cv_numpy_typestr_map["Vec3f"] = _cv_numpy_endianess +"f" + str(_cv_numpy_sizeof_Vec3f.value)
class _Mat__Vec3f(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec3f_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec3f_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec3f_row(self, y)
def col(self, x):
return _AHT._Mat__Vec3f_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec3f_diag(self, d)
def clone(self):
return _AHT._Mat__Vec3f_clone(self)
def elemSize(self):
return _AHT._Mat__Vec3f_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec3f_elemSize1(self)
def type(self):
return _AHT._Mat__Vec3f_type(self)
def depth(self):
return _AHT._Mat__Vec3f_depth(self)
def channels(self):
return _AHT._Mat__Vec3f_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec3f_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec3f_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec3f_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec3f___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec3f_swiginit(self, _AHT.new__Mat__Vec3f(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec3f___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec3f
# Register _Mat__Vec3f in _AHT:
_AHT._Mat__Vec3f_swigregister(_Mat__Vec3f)
Mat3f = _Mat__Vec3f
class _cv_numpy_sizeof_Vec4f(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec4f_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec4f_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec4f())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec4f
# Register _cv_numpy_sizeof_Vec4f in _AHT:
_AHT._cv_numpy_sizeof_Vec4f_swigregister(_cv_numpy_sizeof_Vec4f)
if _cv_numpy_sizeof_Vec4f.value == 1:
_cv_numpy_typestr_map["Vec4f"] = "|" +"f" + "1"
else:
_cv_numpy_typestr_map["Vec4f"] = _cv_numpy_endianess +"f" + str(_cv_numpy_sizeof_Vec4f.value)
class _Mat__Vec4f(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec4f_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec4f_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec4f_row(self, y)
def col(self, x):
return _AHT._Mat__Vec4f_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec4f_diag(self, d)
def clone(self):
return _AHT._Mat__Vec4f_clone(self)
def elemSize(self):
return _AHT._Mat__Vec4f_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec4f_elemSize1(self)
def type(self):
return _AHT._Mat__Vec4f_type(self)
def depth(self):
return _AHT._Mat__Vec4f_depth(self)
def channels(self):
return _AHT._Mat__Vec4f_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec4f_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec4f_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec4f_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec4f___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec4f_swiginit(self, _AHT.new__Mat__Vec4f(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec4f___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec4f
# Register _Mat__Vec4f in _AHT:
_AHT._Mat__Vec4f_swigregister(_Mat__Vec4f)
Mat4f = _Mat__Vec4f
class _Mat__double(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__double_create(self, *args)
def cross(self, m):
return _AHT._Mat__double_cross(self, m)
def row(self, y):
return _AHT._Mat__double_row(self, y)
def col(self, x):
return _AHT._Mat__double_col(self, x)
def diag(self, d=0):
return _AHT._Mat__double_diag(self, d)
def clone(self):
return _AHT._Mat__double_clone(self)
def elemSize(self):
return _AHT._Mat__double_elemSize(self)
def elemSize1(self):
return _AHT._Mat__double_elemSize1(self)
def type(self):
return _AHT._Mat__double_type(self)
def depth(self):
return _AHT._Mat__double_depth(self)
def channels(self):
return _AHT._Mat__double_channels(self)
def step1(self, i=0):
return _AHT._Mat__double_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__double_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__double_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__double___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__double_swiginit(self, _AHT.new__Mat__double(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__double___str__(self)
__swig_destroy__ = _AHT.delete__Mat__double
# Register _Mat__double in _AHT:
_AHT._Mat__double_swigregister(_Mat__double)
Mat1d = _Mat__double
class _cv_numpy_sizeof_Vec2d(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec2d_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec2d_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec2d())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec2d
# Register _cv_numpy_sizeof_Vec2d in _AHT:
_AHT._cv_numpy_sizeof_Vec2d_swigregister(_cv_numpy_sizeof_Vec2d)
if _cv_numpy_sizeof_Vec2d.value == 1:
_cv_numpy_typestr_map["Vec2d"] = "|" +"f" + "1"
else:
_cv_numpy_typestr_map["Vec2d"] = _cv_numpy_endianess +"f" + str(_cv_numpy_sizeof_Vec2d.value)
class _Mat__Vec2d(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec2d_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec2d_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec2d_row(self, y)
def col(self, x):
return _AHT._Mat__Vec2d_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec2d_diag(self, d)
def clone(self):
return _AHT._Mat__Vec2d_clone(self)
def elemSize(self):
return _AHT._Mat__Vec2d_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec2d_elemSize1(self)
def type(self):
return _AHT._Mat__Vec2d_type(self)
def depth(self):
return _AHT._Mat__Vec2d_depth(self)
def channels(self):
return _AHT._Mat__Vec2d_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec2d_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec2d_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec2d_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec2d___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec2d_swiginit(self, _AHT.new__Mat__Vec2d(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec2d___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec2d
# Register _Mat__Vec2d in _AHT:
_AHT._Mat__Vec2d_swigregister(_Mat__Vec2d)
Mat2d = _Mat__Vec2d
class _cv_numpy_sizeof_Vec3d(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec3d_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec3d_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec3d())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec3d
# Register _cv_numpy_sizeof_Vec3d in _AHT:
_AHT._cv_numpy_sizeof_Vec3d_swigregister(_cv_numpy_sizeof_Vec3d)
if _cv_numpy_sizeof_Vec3d.value == 1:
_cv_numpy_typestr_map["Vec3d"] = "|" +"f" + "1"
else:
_cv_numpy_typestr_map["Vec3d"] = _cv_numpy_endianess +"f" + str(_cv_numpy_sizeof_Vec3d.value)
class _Mat__Vec3d(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec3d_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec3d_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec3d_row(self, y)
def col(self, x):
return _AHT._Mat__Vec3d_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec3d_diag(self, d)
def clone(self):
return _AHT._Mat__Vec3d_clone(self)
def elemSize(self):
return _AHT._Mat__Vec3d_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec3d_elemSize1(self)
def type(self):
return _AHT._Mat__Vec3d_type(self)
def depth(self):
return _AHT._Mat__Vec3d_depth(self)
def channels(self):
return _AHT._Mat__Vec3d_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec3d_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec3d_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec3d_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec3d___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec3d_swiginit(self, _AHT.new__Mat__Vec3d(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec3d___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec3d
# Register _Mat__Vec3d in _AHT:
_AHT._Mat__Vec3d_swigregister(_Mat__Vec3d)
Mat3d = _Mat__Vec3d
class _cv_numpy_sizeof_Vec4d(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
value = _AHT._cv_numpy_sizeof_Vec4d_value
def __init__(self):
_AHT._cv_numpy_sizeof_Vec4d_swiginit(self, _AHT.new__cv_numpy_sizeof_Vec4d())
__swig_destroy__ = _AHT.delete__cv_numpy_sizeof_Vec4d
# Register _cv_numpy_sizeof_Vec4d in _AHT:
_AHT._cv_numpy_sizeof_Vec4d_swigregister(_cv_numpy_sizeof_Vec4d)
if _cv_numpy_sizeof_Vec4d.value == 1:
_cv_numpy_typestr_map["Vec4d"] = "|" +"f" + "1"
else:
_cv_numpy_typestr_map["Vec4d"] = _cv_numpy_endianess +"f" + str(_cv_numpy_sizeof_Vec4d.value)
class _Mat__Vec4d(Mat):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def create(self, *args):
return _AHT._Mat__Vec4d_create(self, *args)
def cross(self, m):
return _AHT._Mat__Vec4d_cross(self, m)
def row(self, y):
return _AHT._Mat__Vec4d_row(self, y)
def col(self, x):
return _AHT._Mat__Vec4d_col(self, x)
def diag(self, d=0):
return _AHT._Mat__Vec4d_diag(self, d)
def clone(self):
return _AHT._Mat__Vec4d_clone(self)
def elemSize(self):
return _AHT._Mat__Vec4d_elemSize(self)
def elemSize1(self):
return _AHT._Mat__Vec4d_elemSize1(self)
def type(self):
return _AHT._Mat__Vec4d_type(self)
def depth(self):
return _AHT._Mat__Vec4d_depth(self)
def channels(self):
return _AHT._Mat__Vec4d_channels(self)
def step1(self, i=0):
return _AHT._Mat__Vec4d_step1(self, i)
def stepT(self, i=0):
return _AHT._Mat__Vec4d_stepT(self, i)
def adjustROI(self, dtop, dbottom, dleft, dright):
return _AHT._Mat__Vec4d_adjustROI(self, dtop, dbottom, dleft, dright)
def __call__(self, *args):
return _AHT._Mat__Vec4d___call__(self, *args)
def __init__(self, *args):
_AHT._Mat__Vec4d_swiginit(self, _AHT.new__Mat__Vec4d(*args))
@classmethod
def __check_channels_compatibility(cls, array):
obj = cls()
n_channel = obj.channels()
if n_channel == 1:
if len(array.shape) != 2:
raise ValueError("{} expects a 2-dimensional numpy ndarray.".format(cls))
else:
if len(array.shape) != 3:
raise ValueError("{} expects a 3-dimensional numpy ndarray.".format(cls))
elif array.shape[2] != n_channel:
raise ValueError("{} expects the last ndarray dimension to have a size of {}".format(cls, n_channel))
@classmethod
def from_array(cls, array):
import numpy as np
array = np.asarray(array)
if cls()._typestr() != array.__array_interface__['typestr']:
raise ValueError("{} expects a {} datatype.".format(cls, cls()._typestr()))
cls.__check_channels_compatibility(array)
new_mat = cls(_mat__np_array_constructor(),
array.shape[0],
array.shape[1],
array.__array_interface__['data'][0])
# Holds an internal reference to keep the image buffer alive
new_mat._array = array
return new_mat
def __str__(self):
return _AHT._Mat__Vec4d___str__(self)
__swig_destroy__ = _AHT.delete__Mat__Vec4d
# Register _Mat__Vec4d in _AHT:
_AHT._Mat__Vec4d_swigregister(_Mat__Vec4d)
Mat4d = _Mat__Vec4d
class _Matx_float_1_2(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_float_1_2_rows
cols = _AHT._Matx_float_1_2_cols
channels = _AHT._Matx_float_1_2_channels
shortdim = _AHT._Matx_float_1_2_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_float_1_2_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_float_1_2_zeros()
@staticmethod
def ones():
return _AHT._Matx_float_1_2_ones()
@staticmethod
def eye():
return _AHT._Matx_float_1_2_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_float_1_2_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_float_1_2_randn(a, b)
def dot(self, v):
return _AHT._Matx_float_1_2_dot(self, v)
def ddot(self, v):
return _AHT._Matx_float_1_2_ddot(self, v)
def t(self):
return _AHT._Matx_float_1_2_t(self)
def mul(self, a):
return _AHT._Matx_float_1_2_mul(self, a)
def div(self, a):
return _AHT._Matx_float_1_2_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_float_1_2___call__(self, i, j)
val = property(_AHT._Matx_float_1_2_val_get, _AHT._Matx_float_1_2_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_float_1_2_swiginit(self, _AHT.new__Matx_float_1_2(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_float_1_2___str__(self)
__swig_destroy__ = _AHT.delete__Matx_float_1_2
# Register _Matx_float_1_2 in _AHT:
_AHT._Matx_float_1_2_swigregister(_Matx_float_1_2)
def _Matx_float_1_2_all(alpha):
return _AHT._Matx_float_1_2_all(alpha)
def _Matx_float_1_2_zeros():
return _AHT._Matx_float_1_2_zeros()
def _Matx_float_1_2_ones():
return _AHT._Matx_float_1_2_ones()
def _Matx_float_1_2_eye():
return _AHT._Matx_float_1_2_eye()
def _Matx_float_1_2_randu(a, b):
return _AHT._Matx_float_1_2_randu(a, b)
def _Matx_float_1_2_randn(a, b):
return _AHT._Matx_float_1_2_randn(a, b)
Matx12f = _Matx_float_1_2
class _Matx_double_1_2(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_double_1_2_rows
cols = _AHT._Matx_double_1_2_cols
channels = _AHT._Matx_double_1_2_channels
shortdim = _AHT._Matx_double_1_2_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_double_1_2_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_double_1_2_zeros()
@staticmethod
def ones():
return _AHT._Matx_double_1_2_ones()
@staticmethod
def eye():
return _AHT._Matx_double_1_2_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_double_1_2_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_double_1_2_randn(a, b)
def dot(self, v):
return _AHT._Matx_double_1_2_dot(self, v)
def ddot(self, v):
return _AHT._Matx_double_1_2_ddot(self, v)
def t(self):
return _AHT._Matx_double_1_2_t(self)
def mul(self, a):
return _AHT._Matx_double_1_2_mul(self, a)
def div(self, a):
return _AHT._Matx_double_1_2_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_double_1_2___call__(self, i, j)
val = property(_AHT._Matx_double_1_2_val_get, _AHT._Matx_double_1_2_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_double_1_2_swiginit(self, _AHT.new__Matx_double_1_2(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_double_1_2___str__(self)
__swig_destroy__ = _AHT.delete__Matx_double_1_2
# Register _Matx_double_1_2 in _AHT:
_AHT._Matx_double_1_2_swigregister(_Matx_double_1_2)
def _Matx_double_1_2_all(alpha):
return _AHT._Matx_double_1_2_all(alpha)
def _Matx_double_1_2_zeros():
return _AHT._Matx_double_1_2_zeros()
def _Matx_double_1_2_ones():
return _AHT._Matx_double_1_2_ones()
def _Matx_double_1_2_eye():
return _AHT._Matx_double_1_2_eye()
def _Matx_double_1_2_randu(a, b):
return _AHT._Matx_double_1_2_randu(a, b)
def _Matx_double_1_2_randn(a, b):
return _AHT._Matx_double_1_2_randn(a, b)
Matx12d = _Matx_double_1_2
class _Matx_float_1_3(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_float_1_3_rows
cols = _AHT._Matx_float_1_3_cols
channels = _AHT._Matx_float_1_3_channels
shortdim = _AHT._Matx_float_1_3_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_float_1_3_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_float_1_3_zeros()
@staticmethod
def ones():
return _AHT._Matx_float_1_3_ones()
@staticmethod
def eye():
return _AHT._Matx_float_1_3_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_float_1_3_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_float_1_3_randn(a, b)
def dot(self, v):
return _AHT._Matx_float_1_3_dot(self, v)
def ddot(self, v):
return _AHT._Matx_float_1_3_ddot(self, v)
def t(self):
return _AHT._Matx_float_1_3_t(self)
def mul(self, a):
return _AHT._Matx_float_1_3_mul(self, a)
def div(self, a):
return _AHT._Matx_float_1_3_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_float_1_3___call__(self, i, j)
val = property(_AHT._Matx_float_1_3_val_get, _AHT._Matx_float_1_3_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_float_1_3_swiginit(self, _AHT.new__Matx_float_1_3(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_float_1_3___str__(self)
__swig_destroy__ = _AHT.delete__Matx_float_1_3
# Register _Matx_float_1_3 in _AHT:
_AHT._Matx_float_1_3_swigregister(_Matx_float_1_3)
def _Matx_float_1_3_all(alpha):
return _AHT._Matx_float_1_3_all(alpha)
def _Matx_float_1_3_zeros():
return _AHT._Matx_float_1_3_zeros()
def _Matx_float_1_3_ones():
return _AHT._Matx_float_1_3_ones()
def _Matx_float_1_3_eye():
return _AHT._Matx_float_1_3_eye()
def _Matx_float_1_3_randu(a, b):
return _AHT._Matx_float_1_3_randu(a, b)
def _Matx_float_1_3_randn(a, b):
return _AHT._Matx_float_1_3_randn(a, b)
Matx13f = _Matx_float_1_3
class _Matx_double_1_3(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_double_1_3_rows
cols = _AHT._Matx_double_1_3_cols
channels = _AHT._Matx_double_1_3_channels
shortdim = _AHT._Matx_double_1_3_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_double_1_3_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_double_1_3_zeros()
@staticmethod
def ones():
return _AHT._Matx_double_1_3_ones()
@staticmethod
def eye():
return _AHT._Matx_double_1_3_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_double_1_3_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_double_1_3_randn(a, b)
def dot(self, v):
return _AHT._Matx_double_1_3_dot(self, v)
def ddot(self, v):
return _AHT._Matx_double_1_3_ddot(self, v)
def t(self):
return _AHT._Matx_double_1_3_t(self)
def mul(self, a):
return _AHT._Matx_double_1_3_mul(self, a)
def div(self, a):
return _AHT._Matx_double_1_3_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_double_1_3___call__(self, i, j)
val = property(_AHT._Matx_double_1_3_val_get, _AHT._Matx_double_1_3_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_double_1_3_swiginit(self, _AHT.new__Matx_double_1_3(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_double_1_3___str__(self)
__swig_destroy__ = _AHT.delete__Matx_double_1_3
# Register _Matx_double_1_3 in _AHT:
_AHT._Matx_double_1_3_swigregister(_Matx_double_1_3)
def _Matx_double_1_3_all(alpha):
return _AHT._Matx_double_1_3_all(alpha)
def _Matx_double_1_3_zeros():
return _AHT._Matx_double_1_3_zeros()
def _Matx_double_1_3_ones():
return _AHT._Matx_double_1_3_ones()
def _Matx_double_1_3_eye():
return _AHT._Matx_double_1_3_eye()
def _Matx_double_1_3_randu(a, b):
return _AHT._Matx_double_1_3_randu(a, b)
def _Matx_double_1_3_randn(a, b):
return _AHT._Matx_double_1_3_randn(a, b)
Matx13d = _Matx_double_1_3
class _Matx_float_1_4(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_float_1_4_rows
cols = _AHT._Matx_float_1_4_cols
channels = _AHT._Matx_float_1_4_channels
shortdim = _AHT._Matx_float_1_4_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_float_1_4_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_float_1_4_zeros()
@staticmethod
def ones():
return _AHT._Matx_float_1_4_ones()
@staticmethod
def eye():
return _AHT._Matx_float_1_4_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_float_1_4_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_float_1_4_randn(a, b)
def dot(self, v):
return _AHT._Matx_float_1_4_dot(self, v)
def ddot(self, v):
return _AHT._Matx_float_1_4_ddot(self, v)
def t(self):
return _AHT._Matx_float_1_4_t(self)
def mul(self, a):
return _AHT._Matx_float_1_4_mul(self, a)
def div(self, a):
return _AHT._Matx_float_1_4_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_float_1_4___call__(self, i, j)
val = property(_AHT._Matx_float_1_4_val_get, _AHT._Matx_float_1_4_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_float_1_4_swiginit(self, _AHT.new__Matx_float_1_4(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_float_1_4___str__(self)
__swig_destroy__ = _AHT.delete__Matx_float_1_4
# Register _Matx_float_1_4 in _AHT:
_AHT._Matx_float_1_4_swigregister(_Matx_float_1_4)
def _Matx_float_1_4_all(alpha):
return _AHT._Matx_float_1_4_all(alpha)
def _Matx_float_1_4_zeros():
return _AHT._Matx_float_1_4_zeros()
def _Matx_float_1_4_ones():
return _AHT._Matx_float_1_4_ones()
def _Matx_float_1_4_eye():
return _AHT._Matx_float_1_4_eye()
def _Matx_float_1_4_randu(a, b):
return _AHT._Matx_float_1_4_randu(a, b)
def _Matx_float_1_4_randn(a, b):
return _AHT._Matx_float_1_4_randn(a, b)
Matx14f = _Matx_float_1_4
class _Matx_double_1_4(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_double_1_4_rows
cols = _AHT._Matx_double_1_4_cols
channels = _AHT._Matx_double_1_4_channels
shortdim = _AHT._Matx_double_1_4_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_double_1_4_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_double_1_4_zeros()
@staticmethod
def ones():
return _AHT._Matx_double_1_4_ones()
@staticmethod
def eye():
return _AHT._Matx_double_1_4_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_double_1_4_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_double_1_4_randn(a, b)
def dot(self, v):
return _AHT._Matx_double_1_4_dot(self, v)
def ddot(self, v):
return _AHT._Matx_double_1_4_ddot(self, v)
def t(self):
return _AHT._Matx_double_1_4_t(self)
def mul(self, a):
return _AHT._Matx_double_1_4_mul(self, a)
def div(self, a):
return _AHT._Matx_double_1_4_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_double_1_4___call__(self, i, j)
val = property(_AHT._Matx_double_1_4_val_get, _AHT._Matx_double_1_4_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_double_1_4_swiginit(self, _AHT.new__Matx_double_1_4(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_double_1_4___str__(self)
__swig_destroy__ = _AHT.delete__Matx_double_1_4
# Register _Matx_double_1_4 in _AHT:
_AHT._Matx_double_1_4_swigregister(_Matx_double_1_4)
def _Matx_double_1_4_all(alpha):
return _AHT._Matx_double_1_4_all(alpha)
def _Matx_double_1_4_zeros():
return _AHT._Matx_double_1_4_zeros()
def _Matx_double_1_4_ones():
return _AHT._Matx_double_1_4_ones()
def _Matx_double_1_4_eye():
return _AHT._Matx_double_1_4_eye()
def _Matx_double_1_4_randu(a, b):
return _AHT._Matx_double_1_4_randu(a, b)
def _Matx_double_1_4_randn(a, b):
return _AHT._Matx_double_1_4_randn(a, b)
Matx14d = _Matx_double_1_4
class _Matx_float_1_6(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_float_1_6_rows
cols = _AHT._Matx_float_1_6_cols
channels = _AHT._Matx_float_1_6_channels
shortdim = _AHT._Matx_float_1_6_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_float_1_6_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_float_1_6_zeros()
@staticmethod
def ones():
return _AHT._Matx_float_1_6_ones()
@staticmethod
def eye():
return _AHT._Matx_float_1_6_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_float_1_6_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_float_1_6_randn(a, b)
def dot(self, v):
return _AHT._Matx_float_1_6_dot(self, v)
def ddot(self, v):
return _AHT._Matx_float_1_6_ddot(self, v)
def t(self):
return _AHT._Matx_float_1_6_t(self)
def mul(self, a):
return _AHT._Matx_float_1_6_mul(self, a)
def div(self, a):
return _AHT._Matx_float_1_6_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_float_1_6___call__(self, i, j)
val = property(_AHT._Matx_float_1_6_val_get, _AHT._Matx_float_1_6_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_float_1_6_swiginit(self, _AHT.new__Matx_float_1_6(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_float_1_6___str__(self)
__swig_destroy__ = _AHT.delete__Matx_float_1_6
# Register _Matx_float_1_6 in _AHT:
_AHT._Matx_float_1_6_swigregister(_Matx_float_1_6)
def _Matx_float_1_6_all(alpha):
return _AHT._Matx_float_1_6_all(alpha)
def _Matx_float_1_6_zeros():
return _AHT._Matx_float_1_6_zeros()
def _Matx_float_1_6_ones():
return _AHT._Matx_float_1_6_ones()
def _Matx_float_1_6_eye():
return _AHT._Matx_float_1_6_eye()
def _Matx_float_1_6_randu(a, b):
return _AHT._Matx_float_1_6_randu(a, b)
def _Matx_float_1_6_randn(a, b):
return _AHT._Matx_float_1_6_randn(a, b)
Matx16f = _Matx_float_1_6
class _Matx_double_1_6(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_double_1_6_rows
cols = _AHT._Matx_double_1_6_cols
channels = _AHT._Matx_double_1_6_channels
shortdim = _AHT._Matx_double_1_6_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_double_1_6_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_double_1_6_zeros()
@staticmethod
def ones():
return _AHT._Matx_double_1_6_ones()
@staticmethod
def eye():
return _AHT._Matx_double_1_6_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_double_1_6_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_double_1_6_randn(a, b)
def dot(self, v):
return _AHT._Matx_double_1_6_dot(self, v)
def ddot(self, v):
return _AHT._Matx_double_1_6_ddot(self, v)
def t(self):
return _AHT._Matx_double_1_6_t(self)
def mul(self, a):
return _AHT._Matx_double_1_6_mul(self, a)
def div(self, a):
return _AHT._Matx_double_1_6_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_double_1_6___call__(self, i, j)
val = property(_AHT._Matx_double_1_6_val_get, _AHT._Matx_double_1_6_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_double_1_6_swiginit(self, _AHT.new__Matx_double_1_6(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_double_1_6___str__(self)
__swig_destroy__ = _AHT.delete__Matx_double_1_6
# Register _Matx_double_1_6 in _AHT:
_AHT._Matx_double_1_6_swigregister(_Matx_double_1_6)
def _Matx_double_1_6_all(alpha):
return _AHT._Matx_double_1_6_all(alpha)
def _Matx_double_1_6_zeros():
return _AHT._Matx_double_1_6_zeros()
def _Matx_double_1_6_ones():
return _AHT._Matx_double_1_6_ones()
def _Matx_double_1_6_eye():
return _AHT._Matx_double_1_6_eye()
def _Matx_double_1_6_randu(a, b):
return _AHT._Matx_double_1_6_randu(a, b)
def _Matx_double_1_6_randn(a, b):
return _AHT._Matx_double_1_6_randn(a, b)
Matx16d = _Matx_double_1_6
class _Matx_float_2_2(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_float_2_2_rows
cols = _AHT._Matx_float_2_2_cols
channels = _AHT._Matx_float_2_2_channels
shortdim = _AHT._Matx_float_2_2_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_float_2_2_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_float_2_2_zeros()
@staticmethod
def ones():
return _AHT._Matx_float_2_2_ones()
@staticmethod
def eye():
return _AHT._Matx_float_2_2_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_float_2_2_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_float_2_2_randn(a, b)
def dot(self, v):
return _AHT._Matx_float_2_2_dot(self, v)
def ddot(self, v):
return _AHT._Matx_float_2_2_ddot(self, v)
def t(self):
return _AHT._Matx_float_2_2_t(self)
def mul(self, a):
return _AHT._Matx_float_2_2_mul(self, a)
def div(self, a):
return _AHT._Matx_float_2_2_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_float_2_2___call__(self, i, j)
val = property(_AHT._Matx_float_2_2_val_get, _AHT._Matx_float_2_2_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_float_2_2_swiginit(self, _AHT.new__Matx_float_2_2(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_float_2_2___str__(self)
__swig_destroy__ = _AHT.delete__Matx_float_2_2
# Register _Matx_float_2_2 in _AHT:
_AHT._Matx_float_2_2_swigregister(_Matx_float_2_2)
def _Matx_float_2_2_all(alpha):
return _AHT._Matx_float_2_2_all(alpha)
def _Matx_float_2_2_zeros():
return _AHT._Matx_float_2_2_zeros()
def _Matx_float_2_2_ones():
return _AHT._Matx_float_2_2_ones()
def _Matx_float_2_2_eye():
return _AHT._Matx_float_2_2_eye()
def _Matx_float_2_2_randu(a, b):
return _AHT._Matx_float_2_2_randu(a, b)
def _Matx_float_2_2_randn(a, b):
return _AHT._Matx_float_2_2_randn(a, b)
Matx22f = _Matx_float_2_2
class _Matx_double_2_2(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_double_2_2_rows
cols = _AHT._Matx_double_2_2_cols
channels = _AHT._Matx_double_2_2_channels
shortdim = _AHT._Matx_double_2_2_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_double_2_2_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_double_2_2_zeros()
@staticmethod
def ones():
return _AHT._Matx_double_2_2_ones()
@staticmethod
def eye():
return _AHT._Matx_double_2_2_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_double_2_2_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_double_2_2_randn(a, b)
def dot(self, v):
return _AHT._Matx_double_2_2_dot(self, v)
def ddot(self, v):
return _AHT._Matx_double_2_2_ddot(self, v)
def t(self):
return _AHT._Matx_double_2_2_t(self)
def mul(self, a):
return _AHT._Matx_double_2_2_mul(self, a)
def div(self, a):
return _AHT._Matx_double_2_2_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_double_2_2___call__(self, i, j)
val = property(_AHT._Matx_double_2_2_val_get, _AHT._Matx_double_2_2_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_double_2_2_swiginit(self, _AHT.new__Matx_double_2_2(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_double_2_2___str__(self)
__swig_destroy__ = _AHT.delete__Matx_double_2_2
# Register _Matx_double_2_2 in _AHT:
_AHT._Matx_double_2_2_swigregister(_Matx_double_2_2)
def _Matx_double_2_2_all(alpha):
return _AHT._Matx_double_2_2_all(alpha)
def _Matx_double_2_2_zeros():
return _AHT._Matx_double_2_2_zeros()
def _Matx_double_2_2_ones():
return _AHT._Matx_double_2_2_ones()
def _Matx_double_2_2_eye():
return _AHT._Matx_double_2_2_eye()
def _Matx_double_2_2_randu(a, b):
return _AHT._Matx_double_2_2_randu(a, b)
def _Matx_double_2_2_randn(a, b):
return _AHT._Matx_double_2_2_randn(a, b)
Matx22d = _Matx_double_2_2
class _Matx_float_2_3(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_float_2_3_rows
cols = _AHT._Matx_float_2_3_cols
channels = _AHT._Matx_float_2_3_channels
shortdim = _AHT._Matx_float_2_3_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_float_2_3_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_float_2_3_zeros()
@staticmethod
def ones():
return _AHT._Matx_float_2_3_ones()
@staticmethod
def eye():
return _AHT._Matx_float_2_3_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_float_2_3_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_float_2_3_randn(a, b)
def dot(self, v):
return _AHT._Matx_float_2_3_dot(self, v)
def ddot(self, v):
return _AHT._Matx_float_2_3_ddot(self, v)
def t(self):
return _AHT._Matx_float_2_3_t(self)
def mul(self, a):
return _AHT._Matx_float_2_3_mul(self, a)
def div(self, a):
return _AHT._Matx_float_2_3_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_float_2_3___call__(self, i, j)
val = property(_AHT._Matx_float_2_3_val_get, _AHT._Matx_float_2_3_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_float_2_3_swiginit(self, _AHT.new__Matx_float_2_3(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_float_2_3___str__(self)
__swig_destroy__ = _AHT.delete__Matx_float_2_3
# Register _Matx_float_2_3 in _AHT:
_AHT._Matx_float_2_3_swigregister(_Matx_float_2_3)
def _Matx_float_2_3_all(alpha):
return _AHT._Matx_float_2_3_all(alpha)
def _Matx_float_2_3_zeros():
return _AHT._Matx_float_2_3_zeros()
def _Matx_float_2_3_ones():
return _AHT._Matx_float_2_3_ones()
def _Matx_float_2_3_eye():
return _AHT._Matx_float_2_3_eye()
def _Matx_float_2_3_randu(a, b):
return _AHT._Matx_float_2_3_randu(a, b)
def _Matx_float_2_3_randn(a, b):
return _AHT._Matx_float_2_3_randn(a, b)
Matx23f = _Matx_float_2_3
class _Matx_double_2_3(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_double_2_3_rows
cols = _AHT._Matx_double_2_3_cols
channels = _AHT._Matx_double_2_3_channels
shortdim = _AHT._Matx_double_2_3_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_double_2_3_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_double_2_3_zeros()
@staticmethod
def ones():
return _AHT._Matx_double_2_3_ones()
@staticmethod
def eye():
return _AHT._Matx_double_2_3_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_double_2_3_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_double_2_3_randn(a, b)
def dot(self, v):
return _AHT._Matx_double_2_3_dot(self, v)
def ddot(self, v):
return _AHT._Matx_double_2_3_ddot(self, v)
def t(self):
return _AHT._Matx_double_2_3_t(self)
def mul(self, a):
return _AHT._Matx_double_2_3_mul(self, a)
def div(self, a):
return _AHT._Matx_double_2_3_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_double_2_3___call__(self, i, j)
val = property(_AHT._Matx_double_2_3_val_get, _AHT._Matx_double_2_3_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_double_2_3_swiginit(self, _AHT.new__Matx_double_2_3(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_double_2_3___str__(self)
__swig_destroy__ = _AHT.delete__Matx_double_2_3
# Register _Matx_double_2_3 in _AHT:
_AHT._Matx_double_2_3_swigregister(_Matx_double_2_3)
def _Matx_double_2_3_all(alpha):
return _AHT._Matx_double_2_3_all(alpha)
def _Matx_double_2_3_zeros():
return _AHT._Matx_double_2_3_zeros()
def _Matx_double_2_3_ones():
return _AHT._Matx_double_2_3_ones()
def _Matx_double_2_3_eye():
return _AHT._Matx_double_2_3_eye()
def _Matx_double_2_3_randu(a, b):
return _AHT._Matx_double_2_3_randu(a, b)
def _Matx_double_2_3_randn(a, b):
return _AHT._Matx_double_2_3_randn(a, b)
Matx23d = _Matx_double_2_3
class _Matx_float_3_2(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_float_3_2_rows
cols = _AHT._Matx_float_3_2_cols
channels = _AHT._Matx_float_3_2_channels
shortdim = _AHT._Matx_float_3_2_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_float_3_2_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_float_3_2_zeros()
@staticmethod
def ones():
return _AHT._Matx_float_3_2_ones()
@staticmethod
def eye():
return _AHT._Matx_float_3_2_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_float_3_2_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_float_3_2_randn(a, b)
def dot(self, v):
return _AHT._Matx_float_3_2_dot(self, v)
def ddot(self, v):
return _AHT._Matx_float_3_2_ddot(self, v)
def t(self):
return _AHT._Matx_float_3_2_t(self)
def mul(self, a):
return _AHT._Matx_float_3_2_mul(self, a)
def div(self, a):
return _AHT._Matx_float_3_2_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_float_3_2___call__(self, i, j)
val = property(_AHT._Matx_float_3_2_val_get, _AHT._Matx_float_3_2_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_float_3_2_swiginit(self, _AHT.new__Matx_float_3_2(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_float_3_2___str__(self)
__swig_destroy__ = _AHT.delete__Matx_float_3_2
# Register _Matx_float_3_2 in _AHT:
_AHT._Matx_float_3_2_swigregister(_Matx_float_3_2)
def _Matx_float_3_2_all(alpha):
return _AHT._Matx_float_3_2_all(alpha)
def _Matx_float_3_2_zeros():
return _AHT._Matx_float_3_2_zeros()
def _Matx_float_3_2_ones():
return _AHT._Matx_float_3_2_ones()
def _Matx_float_3_2_eye():
return _AHT._Matx_float_3_2_eye()
def _Matx_float_3_2_randu(a, b):
return _AHT._Matx_float_3_2_randu(a, b)
def _Matx_float_3_2_randn(a, b):
return _AHT._Matx_float_3_2_randn(a, b)
Matx32f = _Matx_float_3_2
class _Matx_double_3_2(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_double_3_2_rows
cols = _AHT._Matx_double_3_2_cols
channels = _AHT._Matx_double_3_2_channels
shortdim = _AHT._Matx_double_3_2_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_double_3_2_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_double_3_2_zeros()
@staticmethod
def ones():
return _AHT._Matx_double_3_2_ones()
@staticmethod
def eye():
return _AHT._Matx_double_3_2_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_double_3_2_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_double_3_2_randn(a, b)
def dot(self, v):
return _AHT._Matx_double_3_2_dot(self, v)
def ddot(self, v):
return _AHT._Matx_double_3_2_ddot(self, v)
def t(self):
return _AHT._Matx_double_3_2_t(self)
def mul(self, a):
return _AHT._Matx_double_3_2_mul(self, a)
def div(self, a):
return _AHT._Matx_double_3_2_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_double_3_2___call__(self, i, j)
val = property(_AHT._Matx_double_3_2_val_get, _AHT._Matx_double_3_2_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_double_3_2_swiginit(self, _AHT.new__Matx_double_3_2(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_double_3_2___str__(self)
__swig_destroy__ = _AHT.delete__Matx_double_3_2
# Register _Matx_double_3_2 in _AHT:
_AHT._Matx_double_3_2_swigregister(_Matx_double_3_2)
def _Matx_double_3_2_all(alpha):
return _AHT._Matx_double_3_2_all(alpha)
def _Matx_double_3_2_zeros():
return _AHT._Matx_double_3_2_zeros()
def _Matx_double_3_2_ones():
return _AHT._Matx_double_3_2_ones()
def _Matx_double_3_2_eye():
return _AHT._Matx_double_3_2_eye()
def _Matx_double_3_2_randu(a, b):
return _AHT._Matx_double_3_2_randu(a, b)
def _Matx_double_3_2_randn(a, b):
return _AHT._Matx_double_3_2_randn(a, b)
Matx32d = _Matx_double_3_2
class _Matx_float_3_3(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_float_3_3_rows
cols = _AHT._Matx_float_3_3_cols
channels = _AHT._Matx_float_3_3_channels
shortdim = _AHT._Matx_float_3_3_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_float_3_3_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_float_3_3_zeros()
@staticmethod
def ones():
return _AHT._Matx_float_3_3_ones()
@staticmethod
def eye():
return _AHT._Matx_float_3_3_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_float_3_3_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_float_3_3_randn(a, b)
def dot(self, v):
return _AHT._Matx_float_3_3_dot(self, v)
def ddot(self, v):
return _AHT._Matx_float_3_3_ddot(self, v)
def t(self):
return _AHT._Matx_float_3_3_t(self)
def mul(self, a):
return _AHT._Matx_float_3_3_mul(self, a)
def div(self, a):
return _AHT._Matx_float_3_3_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_float_3_3___call__(self, i, j)
val = property(_AHT._Matx_float_3_3_val_get, _AHT._Matx_float_3_3_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_float_3_3_swiginit(self, _AHT.new__Matx_float_3_3(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_float_3_3___str__(self)
__swig_destroy__ = _AHT.delete__Matx_float_3_3
# Register _Matx_float_3_3 in _AHT:
_AHT._Matx_float_3_3_swigregister(_Matx_float_3_3)
def _Matx_float_3_3_all(alpha):
return _AHT._Matx_float_3_3_all(alpha)
def _Matx_float_3_3_zeros():
return _AHT._Matx_float_3_3_zeros()
def _Matx_float_3_3_ones():
return _AHT._Matx_float_3_3_ones()
def _Matx_float_3_3_eye():
return _AHT._Matx_float_3_3_eye()
def _Matx_float_3_3_randu(a, b):
return _AHT._Matx_float_3_3_randu(a, b)
def _Matx_float_3_3_randn(a, b):
return _AHT._Matx_float_3_3_randn(a, b)
Matx33f = _Matx_float_3_3
class _Matx_double_3_3(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_double_3_3_rows
cols = _AHT._Matx_double_3_3_cols
channels = _AHT._Matx_double_3_3_channels
shortdim = _AHT._Matx_double_3_3_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_double_3_3_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_double_3_3_zeros()
@staticmethod
def ones():
return _AHT._Matx_double_3_3_ones()
@staticmethod
def eye():
return _AHT._Matx_double_3_3_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_double_3_3_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_double_3_3_randn(a, b)
def dot(self, v):
return _AHT._Matx_double_3_3_dot(self, v)
def ddot(self, v):
return _AHT._Matx_double_3_3_ddot(self, v)
def t(self):
return _AHT._Matx_double_3_3_t(self)
def mul(self, a):
return _AHT._Matx_double_3_3_mul(self, a)
def div(self, a):
return _AHT._Matx_double_3_3_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_double_3_3___call__(self, i, j)
val = property(_AHT._Matx_double_3_3_val_get, _AHT._Matx_double_3_3_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_double_3_3_swiginit(self, _AHT.new__Matx_double_3_3(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_double_3_3___str__(self)
__swig_destroy__ = _AHT.delete__Matx_double_3_3
# Register _Matx_double_3_3 in _AHT:
_AHT._Matx_double_3_3_swigregister(_Matx_double_3_3)
def _Matx_double_3_3_all(alpha):
return _AHT._Matx_double_3_3_all(alpha)
def _Matx_double_3_3_zeros():
return _AHT._Matx_double_3_3_zeros()
def _Matx_double_3_3_ones():
return _AHT._Matx_double_3_3_ones()
def _Matx_double_3_3_eye():
return _AHT._Matx_double_3_3_eye()
def _Matx_double_3_3_randu(a, b):
return _AHT._Matx_double_3_3_randu(a, b)
def _Matx_double_3_3_randn(a, b):
return _AHT._Matx_double_3_3_randn(a, b)
Matx33d = _Matx_double_3_3
class _Matx_float_3_4(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_float_3_4_rows
cols = _AHT._Matx_float_3_4_cols
channels = _AHT._Matx_float_3_4_channels
shortdim = _AHT._Matx_float_3_4_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_float_3_4_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_float_3_4_zeros()
@staticmethod
def ones():
return _AHT._Matx_float_3_4_ones()
@staticmethod
def eye():
return _AHT._Matx_float_3_4_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_float_3_4_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_float_3_4_randn(a, b)
def dot(self, v):
return _AHT._Matx_float_3_4_dot(self, v)
def ddot(self, v):
return _AHT._Matx_float_3_4_ddot(self, v)
def t(self):
return _AHT._Matx_float_3_4_t(self)
def mul(self, a):
return _AHT._Matx_float_3_4_mul(self, a)
def div(self, a):
return _AHT._Matx_float_3_4_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_float_3_4___call__(self, i, j)
val = property(_AHT._Matx_float_3_4_val_get, _AHT._Matx_float_3_4_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_float_3_4_swiginit(self, _AHT.new__Matx_float_3_4(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_float_3_4___str__(self)
__swig_destroy__ = _AHT.delete__Matx_float_3_4
# Register _Matx_float_3_4 in _AHT:
_AHT._Matx_float_3_4_swigregister(_Matx_float_3_4)
def _Matx_float_3_4_all(alpha):
return _AHT._Matx_float_3_4_all(alpha)
def _Matx_float_3_4_zeros():
return _AHT._Matx_float_3_4_zeros()
def _Matx_float_3_4_ones():
return _AHT._Matx_float_3_4_ones()
def _Matx_float_3_4_eye():
return _AHT._Matx_float_3_4_eye()
def _Matx_float_3_4_randu(a, b):
return _AHT._Matx_float_3_4_randu(a, b)
def _Matx_float_3_4_randn(a, b):
return _AHT._Matx_float_3_4_randn(a, b)
Matx34f = _Matx_float_3_4
class _Matx_double_3_4(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_double_3_4_rows
cols = _AHT._Matx_double_3_4_cols
channels = _AHT._Matx_double_3_4_channels
shortdim = _AHT._Matx_double_3_4_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_double_3_4_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_double_3_4_zeros()
@staticmethod
def ones():
return _AHT._Matx_double_3_4_ones()
@staticmethod
def eye():
return _AHT._Matx_double_3_4_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_double_3_4_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_double_3_4_randn(a, b)
def dot(self, v):
return _AHT._Matx_double_3_4_dot(self, v)
def ddot(self, v):
return _AHT._Matx_double_3_4_ddot(self, v)
def t(self):
return _AHT._Matx_double_3_4_t(self)
def mul(self, a):
return _AHT._Matx_double_3_4_mul(self, a)
def div(self, a):
return _AHT._Matx_double_3_4_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_double_3_4___call__(self, i, j)
val = property(_AHT._Matx_double_3_4_val_get, _AHT._Matx_double_3_4_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_double_3_4_swiginit(self, _AHT.new__Matx_double_3_4(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_double_3_4___str__(self)
__swig_destroy__ = _AHT.delete__Matx_double_3_4
# Register _Matx_double_3_4 in _AHT:
_AHT._Matx_double_3_4_swigregister(_Matx_double_3_4)
def _Matx_double_3_4_all(alpha):
return _AHT._Matx_double_3_4_all(alpha)
def _Matx_double_3_4_zeros():
return _AHT._Matx_double_3_4_zeros()
def _Matx_double_3_4_ones():
return _AHT._Matx_double_3_4_ones()
def _Matx_double_3_4_eye():
return _AHT._Matx_double_3_4_eye()
def _Matx_double_3_4_randu(a, b):
return _AHT._Matx_double_3_4_randu(a, b)
def _Matx_double_3_4_randn(a, b):
return _AHT._Matx_double_3_4_randn(a, b)
Matx34d = _Matx_double_3_4
class _Matx_float_4_3(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_float_4_3_rows
cols = _AHT._Matx_float_4_3_cols
channels = _AHT._Matx_float_4_3_channels
shortdim = _AHT._Matx_float_4_3_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_float_4_3_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_float_4_3_zeros()
@staticmethod
def ones():
return _AHT._Matx_float_4_3_ones()
@staticmethod
def eye():
return _AHT._Matx_float_4_3_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_float_4_3_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_float_4_3_randn(a, b)
def dot(self, v):
return _AHT._Matx_float_4_3_dot(self, v)
def ddot(self, v):
return _AHT._Matx_float_4_3_ddot(self, v)
def t(self):
return _AHT._Matx_float_4_3_t(self)
def mul(self, a):
return _AHT._Matx_float_4_3_mul(self, a)
def div(self, a):
return _AHT._Matx_float_4_3_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_float_4_3___call__(self, i, j)
val = property(_AHT._Matx_float_4_3_val_get, _AHT._Matx_float_4_3_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_float_4_3_swiginit(self, _AHT.new__Matx_float_4_3(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_float_4_3___str__(self)
__swig_destroy__ = _AHT.delete__Matx_float_4_3
# Register _Matx_float_4_3 in _AHT:
_AHT._Matx_float_4_3_swigregister(_Matx_float_4_3)
def _Matx_float_4_3_all(alpha):
return _AHT._Matx_float_4_3_all(alpha)
def _Matx_float_4_3_zeros():
return _AHT._Matx_float_4_3_zeros()
def _Matx_float_4_3_ones():
return _AHT._Matx_float_4_3_ones()
def _Matx_float_4_3_eye():
return _AHT._Matx_float_4_3_eye()
def _Matx_float_4_3_randu(a, b):
return _AHT._Matx_float_4_3_randu(a, b)
def _Matx_float_4_3_randn(a, b):
return _AHT._Matx_float_4_3_randn(a, b)
Matx43f = _Matx_float_4_3
class _Matx_double_4_3(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_double_4_3_rows
cols = _AHT._Matx_double_4_3_cols
channels = _AHT._Matx_double_4_3_channels
shortdim = _AHT._Matx_double_4_3_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_double_4_3_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_double_4_3_zeros()
@staticmethod
def ones():
return _AHT._Matx_double_4_3_ones()
@staticmethod
def eye():
return _AHT._Matx_double_4_3_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_double_4_3_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_double_4_3_randn(a, b)
def dot(self, v):
return _AHT._Matx_double_4_3_dot(self, v)
def ddot(self, v):
return _AHT._Matx_double_4_3_ddot(self, v)
def t(self):
return _AHT._Matx_double_4_3_t(self)
def mul(self, a):
return _AHT._Matx_double_4_3_mul(self, a)
def div(self, a):
return _AHT._Matx_double_4_3_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_double_4_3___call__(self, i, j)
val = property(_AHT._Matx_double_4_3_val_get, _AHT._Matx_double_4_3_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_double_4_3_swiginit(self, _AHT.new__Matx_double_4_3(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_double_4_3___str__(self)
__swig_destroy__ = _AHT.delete__Matx_double_4_3
# Register _Matx_double_4_3 in _AHT:
_AHT._Matx_double_4_3_swigregister(_Matx_double_4_3)
def _Matx_double_4_3_all(alpha):
return _AHT._Matx_double_4_3_all(alpha)
def _Matx_double_4_3_zeros():
return _AHT._Matx_double_4_3_zeros()
def _Matx_double_4_3_ones():
return _AHT._Matx_double_4_3_ones()
def _Matx_double_4_3_eye():
return _AHT._Matx_double_4_3_eye()
def _Matx_double_4_3_randu(a, b):
return _AHT._Matx_double_4_3_randu(a, b)
def _Matx_double_4_3_randn(a, b):
return _AHT._Matx_double_4_3_randn(a, b)
Matx43d = _Matx_double_4_3
class _Matx_float_4_4(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_float_4_4_rows
cols = _AHT._Matx_float_4_4_cols
channels = _AHT._Matx_float_4_4_channels
shortdim = _AHT._Matx_float_4_4_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_float_4_4_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_float_4_4_zeros()
@staticmethod
def ones():
return _AHT._Matx_float_4_4_ones()
@staticmethod
def eye():
return _AHT._Matx_float_4_4_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_float_4_4_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_float_4_4_randn(a, b)
def dot(self, v):
return _AHT._Matx_float_4_4_dot(self, v)
def ddot(self, v):
return _AHT._Matx_float_4_4_ddot(self, v)
def t(self):
return _AHT._Matx_float_4_4_t(self)
def mul(self, a):
return _AHT._Matx_float_4_4_mul(self, a)
def div(self, a):
return _AHT._Matx_float_4_4_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_float_4_4___call__(self, i, j)
val = property(_AHT._Matx_float_4_4_val_get, _AHT._Matx_float_4_4_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_float_4_4_swiginit(self, _AHT.new__Matx_float_4_4(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_float_4_4___str__(self)
__swig_destroy__ = _AHT.delete__Matx_float_4_4
# Register _Matx_float_4_4 in _AHT:
_AHT._Matx_float_4_4_swigregister(_Matx_float_4_4)
def _Matx_float_4_4_all(alpha):
return _AHT._Matx_float_4_4_all(alpha)
def _Matx_float_4_4_zeros():
return _AHT._Matx_float_4_4_zeros()
def _Matx_float_4_4_ones():
return _AHT._Matx_float_4_4_ones()
def _Matx_float_4_4_eye():
return _AHT._Matx_float_4_4_eye()
def _Matx_float_4_4_randu(a, b):
return _AHT._Matx_float_4_4_randu(a, b)
def _Matx_float_4_4_randn(a, b):
return _AHT._Matx_float_4_4_randn(a, b)
Matx44f = _Matx_float_4_4
class _Matx_double_4_4(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_double_4_4_rows
cols = _AHT._Matx_double_4_4_cols
channels = _AHT._Matx_double_4_4_channels
shortdim = _AHT._Matx_double_4_4_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_double_4_4_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_double_4_4_zeros()
@staticmethod
def ones():
return _AHT._Matx_double_4_4_ones()
@staticmethod
def eye():
return _AHT._Matx_double_4_4_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_double_4_4_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_double_4_4_randn(a, b)
def dot(self, v):
return _AHT._Matx_double_4_4_dot(self, v)
def ddot(self, v):
return _AHT._Matx_double_4_4_ddot(self, v)
def t(self):
return _AHT._Matx_double_4_4_t(self)
def mul(self, a):
return _AHT._Matx_double_4_4_mul(self, a)
def div(self, a):
return _AHT._Matx_double_4_4_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_double_4_4___call__(self, i, j)
val = property(_AHT._Matx_double_4_4_val_get, _AHT._Matx_double_4_4_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_double_4_4_swiginit(self, _AHT.new__Matx_double_4_4(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_double_4_4___str__(self)
__swig_destroy__ = _AHT.delete__Matx_double_4_4
# Register _Matx_double_4_4 in _AHT:
_AHT._Matx_double_4_4_swigregister(_Matx_double_4_4)
def _Matx_double_4_4_all(alpha):
return _AHT._Matx_double_4_4_all(alpha)
def _Matx_double_4_4_zeros():
return _AHT._Matx_double_4_4_zeros()
def _Matx_double_4_4_ones():
return _AHT._Matx_double_4_4_ones()
def _Matx_double_4_4_eye():
return _AHT._Matx_double_4_4_eye()
def _Matx_double_4_4_randu(a, b):
return _AHT._Matx_double_4_4_randu(a, b)
def _Matx_double_4_4_randn(a, b):
return _AHT._Matx_double_4_4_randn(a, b)
Matx44d = _Matx_double_4_4
class _Matx_float_6_6(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_float_6_6_rows
cols = _AHT._Matx_float_6_6_cols
channels = _AHT._Matx_float_6_6_channels
shortdim = _AHT._Matx_float_6_6_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_float_6_6_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_float_6_6_zeros()
@staticmethod
def ones():
return _AHT._Matx_float_6_6_ones()
@staticmethod
def eye():
return _AHT._Matx_float_6_6_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_float_6_6_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_float_6_6_randn(a, b)
def dot(self, v):
return _AHT._Matx_float_6_6_dot(self, v)
def ddot(self, v):
return _AHT._Matx_float_6_6_ddot(self, v)
def t(self):
return _AHT._Matx_float_6_6_t(self)
def mul(self, a):
return _AHT._Matx_float_6_6_mul(self, a)
def div(self, a):
return _AHT._Matx_float_6_6_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_float_6_6___call__(self, i, j)
val = property(_AHT._Matx_float_6_6_val_get, _AHT._Matx_float_6_6_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_float_6_6_swiginit(self, _AHT.new__Matx_float_6_6(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_float_6_6___str__(self)
__swig_destroy__ = _AHT.delete__Matx_float_6_6
# Register _Matx_float_6_6 in _AHT:
_AHT._Matx_float_6_6_swigregister(_Matx_float_6_6)
def _Matx_float_6_6_all(alpha):
return _AHT._Matx_float_6_6_all(alpha)
def _Matx_float_6_6_zeros():
return _AHT._Matx_float_6_6_zeros()
def _Matx_float_6_6_ones():
return _AHT._Matx_float_6_6_ones()
def _Matx_float_6_6_eye():
return _AHT._Matx_float_6_6_eye()
def _Matx_float_6_6_randu(a, b):
return _AHT._Matx_float_6_6_randu(a, b)
def _Matx_float_6_6_randn(a, b):
return _AHT._Matx_float_6_6_randn(a, b)
Matx66f = _Matx_float_6_6
class _Matx_double_6_6(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
rows = _AHT._Matx_double_6_6_rows
cols = _AHT._Matx_double_6_6_cols
channels = _AHT._Matx_double_6_6_channels
shortdim = _AHT._Matx_double_6_6_shortdim
@staticmethod
def all(alpha):
return _AHT._Matx_double_6_6_all(alpha)
@staticmethod
def zeros():
return _AHT._Matx_double_6_6_zeros()
@staticmethod
def ones():
return _AHT._Matx_double_6_6_ones()
@staticmethod
def eye():
return _AHT._Matx_double_6_6_eye()
@staticmethod
def randu(a, b):
return _AHT._Matx_double_6_6_randu(a, b)
@staticmethod
def randn(a, b):
return _AHT._Matx_double_6_6_randn(a, b)
def dot(self, v):
return _AHT._Matx_double_6_6_dot(self, v)
def ddot(self, v):
return _AHT._Matx_double_6_6_ddot(self, v)
def t(self):
return _AHT._Matx_double_6_6_t(self)
def mul(self, a):
return _AHT._Matx_double_6_6_mul(self, a)
def div(self, a):
return _AHT._Matx_double_6_6_div(self, a)
def __call__(self, i, j):
return _AHT._Matx_double_6_6___call__(self, i, j)
val = property(_AHT._Matx_double_6_6_val_get, _AHT._Matx_double_6_6_val_set)
import re
_re_pattern = re.compile("^_Matx_(?P<value_type>[a-zA-Z_][a-zA-Z0-9_]*)_(?P<rows>[0-9]+)_(?P<cols>[0-9]+)$")
def __init__(self, *args):
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
array = _array_map[value_type](rows*cols)
for i in range(len(args)):
array[i] = args[i]
args = [array]
_AHT._Matx_double_6_6_swiginit(self, _AHT.new__Matx_double_6_6(*args))
def __getattribute__(self, name):
if name == "__array_interface__":
ma = self._re_pattern.match(self.__class__.__name__)
value_type = ma.group("value_type")
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
return {"shape": (rows, cols),
"typestr": _cv_numpy_typestr_map[value_type],
"data": (int(self.val), False)}
else:
return object.__getattribute__(self, name)
def __getitem__(self, key):
ma = self._re_pattern.match(self.__class__.__name__)
rows = int(ma.group("rows"))
cols = int(ma.group("cols"))
if isinstance(key, int):
if rows != 1 and cols != 1:
raise IndexError
i = key
j = 0
elif isinstance(key, tuple) and len(key) == 2:
i = key[0]
j = key[1]
else:
raise TypeError
if i >= rows or j >= cols:
raise IndexError
return self(i, j)
def __str__(self):
return _AHT._Matx_double_6_6___str__(self)
__swig_destroy__ = _AHT.delete__Matx_double_6_6
# Register _Matx_double_6_6 in _AHT:
_AHT._Matx_double_6_6_swigregister(_Matx_double_6_6)
def _Matx_double_6_6_all(alpha):
return _AHT._Matx_double_6_6_all(alpha)
def _Matx_double_6_6_zeros():
return _AHT._Matx_double_6_6_zeros()
def _Matx_double_6_6_ones():
return _AHT._Matx_double_6_6_ones()
def _Matx_double_6_6_eye():
return _AHT._Matx_double_6_6_eye()
def _Matx_double_6_6_randu(a, b):
return _AHT._Matx_double_6_6_randu(a, b)
def _Matx_double_6_6_randn(a, b):
return _AHT._Matx_double_6_6_randn(a, b)
Matx66d = _Matx_double_6_6
class _Point__int(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self, *args):
_AHT._Point__int_swiginit(self, _AHT.new__Point__int(*args))
def dot(self, pt):
return _AHT._Point__int_dot(self, pt)
def ddot(self, pt):
return _AHT._Point__int_ddot(self, pt)
def cross(self, pt):
return _AHT._Point__int_cross(self, pt)
x = property(_AHT._Point__int_x_get, _AHT._Point__int_x_set)
y = property(_AHT._Point__int_y_get, _AHT._Point__int_y_set)
def __iter__(self):
return iter((self.x, self.y))
def __str__(self):
return _AHT._Point__int___str__(self)
__swig_destroy__ = _AHT.delete__Point__int
# Register _Point__int in _AHT:
_AHT._Point__int_swigregister(_Point__int)
Point2i = _Point__int
class _Point__float(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self, *args):
_AHT._Point__float_swiginit(self, _AHT.new__Point__float(*args))
def dot(self, pt):
return _AHT._Point__float_dot(self, pt)
def ddot(self, pt):
return _AHT._Point__float_ddot(self, pt)
def cross(self, pt):
return _AHT._Point__float_cross(self, pt)
x = property(_AHT._Point__float_x_get, _AHT._Point__float_x_set)
y = property(_AHT._Point__float_y_get, _AHT._Point__float_y_set)
def __iter__(self):
return iter((self.x, self.y))
def __str__(self):
return _AHT._Point__float___str__(self)
__swig_destroy__ = _AHT.delete__Point__float
# Register _Point__float in _AHT:
_AHT._Point__float_swigregister(_Point__float)
Point2f = _Point__float
class _Point__double(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self, *args):
_AHT._Point__double_swiginit(self, _AHT.new__Point__double(*args))
def dot(self, pt):
return _AHT._Point__double_dot(self, pt)
def ddot(self, pt):
return _AHT._Point__double_ddot(self, pt)
def cross(self, pt):
return _AHT._Point__double_cross(self, pt)
x = property(_AHT._Point__double_x_get, _AHT._Point__double_x_set)
y = property(_AHT._Point__double_y_get, _AHT._Point__double_y_set)
def __iter__(self):
return iter((self.x, self.y))
def __str__(self):
return _AHT._Point__double___str__(self)
__swig_destroy__ = _AHT.delete__Point__double
# Register _Point__double in _AHT:
_AHT._Point__double_swigregister(_Point__double)
Point2d = _Point__double
Point = Point2i
class _Rect__int(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self, *args):
_AHT._Rect__int_swiginit(self, _AHT.new__Rect__int(*args))
def tl(self):
return _AHT._Rect__int_tl(self)
def br(self):
return _AHT._Rect__int_br(self)
def size(self):
return _AHT._Rect__int_size(self)
def area(self):
return _AHT._Rect__int_area(self)
def contains(self, pt):
return _AHT._Rect__int_contains(self, pt)
x = property(_AHT._Rect__int_x_get, _AHT._Rect__int_x_set)
y = property(_AHT._Rect__int_y_get, _AHT._Rect__int_y_set)
width = property(_AHT._Rect__int_width_get, _AHT._Rect__int_width_set)
height = property(_AHT._Rect__int_height_get, _AHT._Rect__int_height_set)
def __iter__(self):
return iter((self.x, self.y, self.width, self.height))
def __str__(self):
return _AHT._Rect__int___str__(self)
__swig_destroy__ = _AHT.delete__Rect__int
# Register _Rect__int in _AHT:
_AHT._Rect__int_swigregister(_Rect__int)
Rect2i = _Rect__int
class _Rect__float(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self, *args):
_AHT._Rect__float_swiginit(self, _AHT.new__Rect__float(*args))
def tl(self):
return _AHT._Rect__float_tl(self)
def br(self):
return _AHT._Rect__float_br(self)
def size(self):
return _AHT._Rect__float_size(self)
def area(self):
return _AHT._Rect__float_area(self)
def contains(self, pt):
return _AHT._Rect__float_contains(self, pt)
x = property(_AHT._Rect__float_x_get, _AHT._Rect__float_x_set)
y = property(_AHT._Rect__float_y_get, _AHT._Rect__float_y_set)
width = property(_AHT._Rect__float_width_get, _AHT._Rect__float_width_set)
height = property(_AHT._Rect__float_height_get, _AHT._Rect__float_height_set)
def __iter__(self):
return iter((self.x, self.y, self.width, self.height))
def __str__(self):
return _AHT._Rect__float___str__(self)
__swig_destroy__ = _AHT.delete__Rect__float
# Register _Rect__float in _AHT:
_AHT._Rect__float_swigregister(_Rect__float)
Rect2f = _Rect__float
class _Rect__double(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self, *args):
_AHT._Rect__double_swiginit(self, _AHT.new__Rect__double(*args))
def tl(self):
return _AHT._Rect__double_tl(self)
def br(self):
return _AHT._Rect__double_br(self)
def size(self):
return _AHT._Rect__double_size(self)
def area(self):
return _AHT._Rect__double_area(self)
def contains(self, pt):
return _AHT._Rect__double_contains(self, pt)
x = property(_AHT._Rect__double_x_get, _AHT._Rect__double_x_set)
y = property(_AHT._Rect__double_y_get, _AHT._Rect__double_y_set)
width = property(_AHT._Rect__double_width_get, _AHT._Rect__double_width_set)
height = property(_AHT._Rect__double_height_get, _AHT._Rect__double_height_set)
def __iter__(self):
return iter((self.x, self.y, self.width, self.height))
def __str__(self):
return _AHT._Rect__double___str__(self)
__swig_destroy__ = _AHT.delete__Rect__double
# Register _Rect__double in _AHT:
_AHT._Rect__double_swigregister(_Rect__double)
Rect2d = _Rect__double
Rect = Rect2i
class _Scalar__double(_Vec_double_4):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self, *args):
_AHT._Scalar__double_swiginit(self, _AHT.new__Scalar__double(*args))
@staticmethod
def all(v0):
return _AHT._Scalar__double_all(v0)
def mul(self, a, scale=1):
return _AHT._Scalar__double_mul(self, a, scale)
def conj(self):
return _AHT._Scalar__double_conj(self)
def isReal(self):
return _AHT._Scalar__double_isReal(self)
def __iter__(self):
return iter((self(0), self(1), self(2), self(3)))
def __getitem__(self, key):
if not isinstance(key, int):
raise TypeError
if key >= 4:
raise IndexError
return self(key)
def __str__(self):
return _AHT._Scalar__double___str__(self)
__swig_destroy__ = _AHT.delete__Scalar__double
# Register _Scalar__double in _AHT:
_AHT._Scalar__double_swigregister(_Scalar__double)
def _Scalar__double_all(v0):
return _AHT._Scalar__double_all(v0)
Scalar4d = _Scalar__double
Scalar = Scalar4d
class _Size__int(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self, *args):
_AHT._Size__int_swiginit(self, _AHT.new__Size__int(*args))
def area(self):
return _AHT._Size__int_area(self)
width = property(_AHT._Size__int_width_get, _AHT._Size__int_width_set)
height = property(_AHT._Size__int_height_get, _AHT._Size__int_height_set)
def __iter__(self):
return iter((self.width, self.height))
def __str__(self):
return _AHT._Size__int___str__(self)
__swig_destroy__ = _AHT.delete__Size__int
# Register _Size__int in _AHT:
_AHT._Size__int_swigregister(_Size__int)
Size2i = _Size__int
class _Size__float(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self, *args):
_AHT._Size__float_swiginit(self, _AHT.new__Size__float(*args))
def area(self):
return _AHT._Size__float_area(self)
width = property(_AHT._Size__float_width_get, _AHT._Size__float_width_set)
height = property(_AHT._Size__float_height_get, _AHT._Size__float_height_set)
def __iter__(self):
return iter((self.width, self.height))
def __str__(self):
return _AHT._Size__float___str__(self)
__swig_destroy__ = _AHT.delete__Size__float
# Register _Size__float in _AHT:
_AHT._Size__float_swigregister(_Size__float)
Size2f = _Size__float
class _Size__double(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self, *args):
_AHT._Size__double_swiginit(self, _AHT.new__Size__double(*args))
def area(self):
return _AHT._Size__double_area(self)
width = property(_AHT._Size__double_width_get, _AHT._Size__double_width_set)
height = property(_AHT._Size__double_height_get, _AHT._Size__double_height_set)
def __iter__(self):
return iter((self.width, self.height))
def __str__(self):
return _AHT._Size__double___str__(self)
__swig_destroy__ = _AHT.delete__Size__double
# Register _Size__double in _AHT:
_AHT._Size__double_swigregister(_Size__double)
Size2d = _Size__double
Size = Size2i
def AHT(file1, file2, outfile):
return _AHT.LHBA(file1, file2, outfile)