python - 如何扩展/扩张一个numpy数组？

Question

我正在执行图像分析并以 bool 值的形式生成种子 array :

import numpy as np

# Example output array
a = np.array([[False, False, False], [False, True, False], [False, False, False]])

>>> a
array([[False, False, False],
       [False,  True, False],
       [False, False, False]])

由于我想对 True周围的区域做后续分析。值，我想扩展它(按一定数量，比如像素)。这将导致以下结果:

>>> a
array([[False, True, False],
       [True, True, True],
       [False, True, False]])

有没有 function或解决我的“径向膨胀”问题的简单方法？

提前致谢，
烧烤架

Answer 1

解决方案 scipy.signal.convolve2d :

import numpy as np
from scipy.signal import convolve2d


# Example input
# [[False False False False False]
#  [False False  True  True False]
#  [False False False False False]
#  [False False False False False]
#  [False False False False  True]]
in_array = np.zeros((5, 5), dtype=bool)
in_array[1,2] = True
in_array[1,3] = True
in_array[4,4] = True

# Kernel: here you should define how much the True "dilates"

kernel = np.asarray([[False, True, False],
                     [True, True, True],
                     [False, True, False]])

# Convolution happens here
# Convolution is not possible for bool values though, so we convert to int and
# back. That works because bool(N) == True if N != 0.
result = convolve2d(in_array.astype(int), kernel.astype(int), mode='same').astype(bool)
print(result)

# Result:
# [[False False  True  True False]
#  [False  True  True  True  True]
#  [False False  True  True False]
#  [False False False False  True]
#  [False False False  True  True]]