如何将函数应用于numpy数组中的每个第3轴元素? [英] How to apply a function to each 3rd axis element in a numpy array?

问题描述

如果我有一个像这样的numpy数组:

If I have a numpy array like so:

[[[137 153 135]
  [138 154 136]
  [138 153 138]
  ..., 
  [134 159 153]
  [136 159 153]
  [135 158 152]]
  ...,
  [ 57  44  34]
  [ 55  47  37]
  [ 55  47  37]]]

如何对每个[000 000 000]个条目应用一个函数，对其进行修改?

How can I apply a function to each [000 000 000] entry, modifying it?

# a = numpy array
for x in a:
    for y in x:
        y = modify(y)

我想要实现的是修改PIL图像中的每个(r，g，b)像素，这些像素已转换为numpy数组.

What I'd like to achieve is modifying each (r,g,b) pixel in a PIL image that was converted to a numpy array.

推荐答案

一个简单的答案是

for row in a:
    for item in row:
        item[:] = modify(item)

但是，这并不是很有效.一个有效的解决方案应避免Python在所有像素上循环. (这就是NumPy的全部意义-向量化您的代码！)手头案件的向量化版本将是

This won't be very efficient, though. An efficient solution should avoid Python loops over all pixels. (That's somehow what NumPy is all about -- vectorise your code!) A vectorised version for the case at hand would be

r, g, b = a[..., 0], a[..., 1], a[..., 2]
new_a = numpy.empty_like(a)
new_a.fill(255)
new_a[(r != a.max(axis=2)) | (r <= 125) | (g >= 70) | (b >= 110), 1:] = 0

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