forked from 170010011/fr
61 lines
2.0 KiB
Python
61 lines
2.0 KiB
Python
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import numpy as np
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from ..util import img_as_float
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from itertools import product
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def compare_images(image1, image2, method='diff', *, n_tiles=(8, 8)):
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"""
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Return an image showing the differences between two images.
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.. versionadded:: 0.16
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Parameters
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----------
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image1, image2 : 2-D array
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Images to process, must be of the same shape.
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method : string, optional
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Method used for the comparison.
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Valid values are {'diff', 'blend', 'checkerboard'}.
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Details are provided in the note section.
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n_tiles : tuple, optional
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Used only for the `checkerboard` method. Specifies the number
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of tiles (row, column) to divide the image.
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Returns
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-------
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comparison : 2-D array
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Image showing the differences.
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Notes
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-----
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``'diff'`` computes the absolute difference between the two images.
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``'blend'`` computes the mean value.
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``'checkerboard'`` makes tiles of dimension `n_tiles` that display
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alternatively the first and the second image.
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"""
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if image1.shape != image2.shape:
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raise ValueError('Images must have the same shape.')
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img1 = img_as_float(image1)
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img2 = img_as_float(image2)
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if method == 'diff':
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comparison = np.abs(img2 - img1)
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elif method == 'blend':
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comparison = 0.5 * (img2 + img1)
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elif method == 'checkerboard':
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shapex, shapey = img1.shape
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mask = np.full((shapex, shapey), False)
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stepx = int(shapex / n_tiles[0])
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stepy = int(shapey / n_tiles[1])
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for i, j in product(range(n_tiles[0]), range(n_tiles[1])):
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if (i + j) % 2 == 0:
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mask[i * stepx:(i + 1)*stepx, j * stepy:(j + 1) * stepy] = True
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comparison = np.zeros_like(img1)
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comparison[mask] = img1[mask]
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comparison[~mask] = img2[~mask]
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else:
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raise ValueError('Wrong value for `method`. '
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'Must be either "diff", "blend" or "checkerboard".')
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return comparison
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