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https://github.com/wassname/scikit-image.git
synced 2026-07-05 01:25:41 +08:00
Remove deprecated homography function
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@@ -253,98 +253,3 @@ def swirl(image, center=None, strength=1, radius=100, rotation=0,
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return warp(image, _swirl_mapping, map_args=warp_args,
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output_shape=output_shape,
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order=order, mode=mode, cval=cval)
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def homography(image, H, output_shape=None, order=1,
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mode='constant', cval=0.):
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"""
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.. note:: Deprecated in skimage 0.7
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`homography` will be removed in skimage 0.8, it is replaced by
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`warp` because the latter provides the same functionality::
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warp(image, ProjectiveTransform(H))
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Perform a projective transformation (homography) on an image.
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For each pixel, given its homogeneous coordinate :math:`\mathbf{x}
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= [x, y, 1]^T`, its target position is calculated by multiplying
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with the given matrix, :math:`H`, to give :math:`H \mathbf{x}`.
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E.g., to rotate by theta degrees clockwise, the matrix should be
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::
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[[cos(theta) -sin(theta) 0]
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[sin(theta) cos(theta) 0]
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[0 0 1]]
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or, to translate x by 10 and y by 20,
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::
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[[1 0 10]
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[0 1 20]
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[0 0 1 ]].
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Parameters
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----------
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image : 2-D array
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Input image.
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H : array of shape ``(3, 3)``
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Transformation matrix H that defines the homography.
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output_shape : tuple (rows, cols)
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Shape of the output image generated.
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order : int
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Order of splines used in interpolation.
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mode : string
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How to handle values outside the image borders. Passed as-is
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to ndimage.
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cval : string
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Used in conjunction with mode 'constant', the value outside
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the image boundaries.
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Examples
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--------
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>>> # rotate by 90 degrees around origin and shift down by 2
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>>> x = np.arange(9, dtype=np.uint8).reshape((3, 3)) + 1
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>>> x
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array([[1, 2, 3],
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[4, 5, 6],
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[7, 8, 9]], dtype=uint8)
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>>> theta = -np.pi/2
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>>> M = np.array([[np.cos(theta),-np.sin(theta),0],
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... [np.sin(theta), np.cos(theta),2],
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... [0, 0, 1]])
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>>> x90 = homography(x, M, order=1)
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>>> x90
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array([[3, 6, 9],
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[2, 5, 8],
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[1, 4, 7]], dtype=uint8)
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>>> # translate right by 2 and down by 1
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>>> y = np.zeros((5,5), dtype=np.uint8)
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>>> y[1, 1] = 255
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>>> y
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array([[ 0, 0, 0, 0, 0],
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[ 0, 255, 0, 0, 0],
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[ 0, 0, 0, 0, 0],
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[ 0, 0, 0, 0, 0],
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[ 0, 0, 0, 0, 0]], dtype=uint8)
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>>> M = np.array([[ 1., 0., 2.],
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... [ 0., 1., 1.],
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... [ 0., 0., 1.]])
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>>> y21 = homography(y, M, order=1)
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>>> y21
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array([[ 0, 0, 0, 0, 0],
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[ 0, 0, 0, 0, 0],
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[ 0, 0, 0, 255, 0],
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[ 0, 0, 0, 0, 0],
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[ 0, 0, 0, 0, 0]], dtype=uint8)
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"""
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import warnings
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warnings.warn('the homography function is deprecated; '
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'use the `warp` and `ProjectiveTransform` class instead',
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category=DeprecationWarning)
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tform = ProjectiveTransform(H)
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return warp(image, inverse_map=tform.inverse, output_shape=output_shape,
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order=order, mode=mode, cval=cval)
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