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__all__ = []
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import numpy as np
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import cv2 as cv
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from typing import TYPE_CHECKING, Any
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# Same as cv2.typing.NumPyArrayNumeric, but avoids circular dependencies
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if TYPE_CHECKING:
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_NumPyArrayNumeric = np.ndarray[Any, np.dtype[np.integer[Any] | np.floating[Any]]]
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else:
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_NumPyArrayNumeric = np.ndarray
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# NumPy documentation: https://numpy.org/doc/stable/user/basics.subclassing.html
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class Mat(_NumPyArrayNumeric):
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'''
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cv.Mat wrapper for numpy array.
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Stores extra metadata information how to interpret and process of numpy array for underlying C++ code.
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'''
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def __new__(cls, arr, **kwargs):
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obj = arr.view(Mat)
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return obj
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def __init__(self, arr, **kwargs):
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self.wrap_channels = kwargs.pop('wrap_channels', getattr(arr, 'wrap_channels', False))
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if len(kwargs) > 0:
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raise TypeError('Unknown parameters: {}'.format(repr(kwargs)))
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def __array_finalize__(self, obj):
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if obj is None:
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return
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self.wrap_channels = getattr(obj, 'wrap_channels', None)
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Mat.__module__ = cv.__name__
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cv.Mat = Mat
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cv._registerMatType(Mat)
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