[英]Faster way to extract patches from a tensor?
I am trying to extract patches of fixed size centred at some given position (x,y,z). 我试图提取以某个给定位置(x,y,z)为中心的固定大小的补丁。 The code is given below:
代码如下:
x = np.random.randint(0,99,(150, 80, 50, 3))
patch_size = 32
half = int(patch_size//2)
indices = np.array([[40, 20, 30], [60, 30, 27], [20, 18, 21]])
n_patches = indices.shape[0]
patches = np.empty((n_patches, patch_size, patch_size,patch_size, x.shape[-1]))
for ix,_ in enumerate(indices):
patches[ix, ...] = x[indices[ix, 0]-half:indices[ix, 0]+half,
indices[ix, 1]-half:indices[ix, 1]+half,
indices[ix, 2]-half:indices[ix, 2]+half, ...]
Can anyone tell me how to make this work faster? 谁能告诉我如何使这项工作更快? or any other alternatives if you can suggest it would be of great help.
或任何其他替代方法(如果您可以建议这样做的话)会很有帮助。 I've seen a similar problem solved in https://stackoverflow.com/a/37901746/4296850 , but only for 2D images.
我在https://stackoverflow.com/a/37901746/4296850中看到了类似的问题,但仅适用于2D图像。 Could anyone help me to generalize this solution?
谁能帮我概括这个解决方案?
We can leverage np.lib.stride_tricks.as_strided
based scikit-image's view_as_windows
to get sliding windows. 我们可以利用
np.lib.stride_tricks.as_strided
基于scikit-image's view_as_windows
得到滑动窗口。 More info on use of as_strided
based view_as_windows
. 有关使用基于
view_as_windows
的as_strided
的更多信息 。
from skimage.util.shape import view_as_windows
# Get sliding windows
w = view_as_windows(x,(2*half,2*half,2*half,1))[...,0]
# Get starting indices for indexing along the first three three axes
idx = indices-half
# Use advanced-indexing to index into first 3 axes with idx and a
# final permuting of axes to bring the output format as desired
out = np.moveaxis(w[idx[:,0],idx[:,1],idx[:,2]],1,-1)
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