从（图像）数组中提取多个窗口/补丁，如另一个数组中所定义

Question

I have an image im which is an array as given by imread . Say eg

im = np.array([[1,2,3,4],
               [2,3,4,5],
               [3,4,5,6],
               [4,5,6,7]]

I have another (n,4) array of windows where each row defines a patch of the image as (x, y, w, h) . Eg

windows = np.array([[0,0,2,2],
                    [1,1,2,2]]

I'd like to extract all of these patches from im as sub-arrays without looping through. My current looping solution is something like:

for x, y, w, h in windows:
    patch = im[y:(y+h),x:(x+w)]

But I'd like a nice array-based operation to get all of them, if possible.

Thanks.

Answer 1

For same window sizes, we could get views with help from scikit-image's view_as_windows , like so -

from skimage.util.shape import view_as_windows

im4D = view_as_windows(im, (windows[0,2],windows[0,3]))
out = im4D[windows[:,0], windows[:,1]]

Sample run -

In [191]: im4D = view_as_windows(im, (windows[0,2],windows[0,3]))

In [192]: im4D[windows[:,0], windows[:,1]]
Out[192]: 
array([[[1, 2],
        [2, 3]],

       [[3, 4],
        [4, 5]]])

Answer 2

If scikit is not available we can homebrew @Divakar's solution with numpy.lib.stride_tricks . The same constraint (all windows must have same shape) applies:

import numpy as np
from numpy.lib.stride_tricks import as_strided

im = np.array([[1,2,3,4],
               [2,3,4,5],
               [3,4,5,6],
               [4,5,6,7]])

windows = np.array([[0,0,2,2],
                    [1,1,2,2]])

Y, X = im.shape
y, x = windows[0, 2:]
cutmeup = as_strided(im, shape=(Y-y+1, X-x+1, y, x), strides=2*im.strides)
print(cutmeup[windows[:, 0], windows[:, 1]])

Output:

[[[1 2]
  [2 3]]

 [[3 4]
  [4 5]]]