File size: 3,119 Bytes
712b117 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 | import functools
from itertools import product
import numpy as np
from .dtype import img_as_float
def _rename_image_params(func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
# Turn all args into kwargs
for i, (value, param) in enumerate(
zip(args, ["image0", "image1", "method", "n_tiles"])
):
if param in kwargs:
raise ValueError(
f"{param} passed both as positional and keyword argument."
)
else:
kwargs[param] = value
args = tuple()
return func(*args, **kwargs)
return wrapper
@_rename_image_params
def compare_images(image0, image1, *, method='diff', n_tiles=(8, 8)):
"""
Return an image showing the differences between two images.
.. versionadded:: 0.16
Parameters
----------
image0, image1 : ndarray, shape (M, N)
Images to process, must be of the same shape.
.. versionchanged:: 0.24
`image1` and `image2` were renamed into `image0` and `image1`
respectively.
method : {'diff', 'blend', 'checkerboard'}, optional
Method used for the comparison.
Details are provided in the note section.
.. versionchanged:: 0.24
This parameter and following ones are keyword-only.
n_tiles : tuple, optional
Used only for the `checkerboard` method. Specifies the number
of tiles (row, column) to divide the image.
Returns
-------
comparison : ndarray, shape (M, N)
Image showing the differences.
Notes
-----
``'diff'`` computes the absolute difference between the two images.
``'blend'`` computes the mean value.
``'checkerboard'`` makes tiles of dimension `n_tiles` that display
alternatively the first and the second image. Note that images must be
2-dimensional to be compared with the checkerboard method.
"""
if image1.shape != image0.shape:
raise ValueError('Images must have the same shape.')
img1 = img_as_float(image0)
img2 = img_as_float(image1)
if method == 'diff':
comparison = np.abs(img2 - img1)
elif method == 'blend':
comparison = 0.5 * (img2 + img1)
elif method == 'checkerboard':
if img1.ndim != 2:
raise ValueError(
'Images must be 2-dimensional to be compared with the '
'checkerboard method.'
)
shapex, shapey = img1.shape
mask = np.full((shapex, shapey), False)
stepx = int(shapex / n_tiles[0])
stepy = int(shapey / n_tiles[1])
for i, j in product(range(n_tiles[0]), range(n_tiles[1])):
if (i + j) % 2 == 0:
mask[i * stepx : (i + 1) * stepx, j * stepy : (j + 1) * stepy] = True
comparison = np.zeros_like(img1)
comparison[mask] = img1[mask]
comparison[~mask] = img2[~mask]
else:
raise ValueError(
'Wrong value for `method`. '
'Must be either "diff", "blend" or "checkerboard".'
)
return comparison
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