在 scikit-image 中,images are just NumPy arrays 所以你应该为此使用 NumPy 切片:
from skimage import data
import matplotlib.pyplot as plt
image = data.camera()
nrows, ncols = image.shape
rsplit, csplit = nrows // 2, ncols // 2
quadrants = [
image[:rsplit, :csplit],
image[:rsplit, csplit:],
image[rsplit:, :csplit],
image[rsplit:, csplit:],
]
fig, axes = plt.subplots(2, 2)
for quadrant, ax in zip(quadrants, axes.flat):
ax.imshow(quadrant, cmap='gray')
ax.set_axis_off()
当且仅当您确定图像的行数和列数是偶数时,您可以得到带有skimage.util.view_as_blocks 的象限:
from skimage.util import view_as_blocks
quadrants = view_as_blocks(image, (rsplit, csplit)).reshape(
(4, rsplit, csplit)
)