| 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): |
| |
| 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 |
|
|
