这是我用来检查 convolve2d 正确性的代码
import numpy as np
from scipy.signal import convolve2d
X = np.random.randint(5, size=(10,10))
K = np.random.randint(5, size=(3,3))
print "Input's top-left corner:"
print X[:3,:3]
print 'Kernel:'
print K
print 'Hardcording the calculation of a valid convolution (top-left)'
print (X[:3,:3]*K)
print 'Sums to'
print (X[:3,:3]*K).sum()
print 'However the top-left value of the convolve2d result'
Y = convolve2d(X, K, 'valid')
print Y[0,0]
在我的电脑上,结果如下:
Input's top-left (3x3) corner:
[[0 0 0]
[1 1 2]
[1 3 0]]
Kernel:
[[4 1 1]
[0 3 3]
[2 1 2]]
Hardcording the calculation of a valid convolution (top-left)
[[0 0 0]
[0 3 6]
[2 3 0]]
Sums to
14
However the top-left value of the convolve2d result
10
背景故事:我一直在调试一个 convnet 库,不知何故梯度总是错误的。几周后,我得出结论认为一切正常,所以我徒手检查了 convolve2d 函数。
最佳答案
我认为问题在于您没有执行 SciPy 实现的内容。我不会详述细节或基础,只会为您提供解决方案:
反转内核。
>>> import numpy as np
>>> arr = np.array([[0, 0, 0],
[1, 1, 2],
[1, 3, 0]])
>>> kernel = np.array([[4, 1, 1],
[0, 3, 3],
[2, 1, 2]])
>>> from scipy.signal import convolve2d
>>> convolve2d(arr, kernel[::-1, ::-1])
array([[ 0, 0, 0, 0, 0],
[ 2, 3, 7, 4, 4],
[ 5, 13, 14, 12, 0],
[ 4, 14, 16, 6, 8],
[ 1, 4, 7, 12, 0]])
>>> convolve2d(arr, kernel[::-1, ::-1], 'valid')
array([[14]])
关于python - scipy convolve2d 输出错误的值,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/40247760/