问题描述
我希望彼此减去2张灰色人脸以查看差异，但是我遇到了一个问题，例如减去[4]-[6]给出的是[254]，而不是[-2](或区别为[2]).
I wish to subtract 2 gray human faces from each other to see the difference, but I encounter a problem that subtracting e.g. [4] - [6] gives [254] instead of [-2] (or difference: [2]).
print(type(face)) #<type 'numpy.ndarray'>
print(face.shape) #(270, 270)
print(type(nface)) #<type 'numpy.ndarray'>
print(nface.shape) #(270, 270)
#This is what I want to do:
sface = face - self.nface #or
sface = np.subtract(face, self.nface)
两者都不给出负数，而是从255中减去0后的其余部分.
Both don't give negative numbers but instead subtract the rest after 0 from 255.
sface的输出示例:
Output example of sface:
[[ 8 255 8 ..., 0 252 3]
[ 24 18 14 ..., 255 254 254]
[ 12 12 12 ..., 0 2 254]
...,
[245 245 251 ..., 160 163 176]
[249 249 252 ..., 157 163 172]
[253 251 247 ..., 155 159 173]]
我的问题:在减去或人脸和nface中每个点的差后，如何使sface成为具有负值的numpy.ndarray(270,270)? (因此不是numpy.setdiff1d，因为它仅返回1个尺寸，而不是270x270)
My question:How do I get sface to be an numpy.ndarray (270,270) with either negative values after subtracting or the difference between each point in face and nface? (So not numpy.setdiff1d, because this returns only 1 dimension instead of 270x270)
从@ajcr的答案中，我做了以下操作(abs()用于显示减去的脸):
From the answer of @ajcr I did the following (abs() for showing subtracted face):
face_16 = face.astype(np.int16)
nface_16 = nface.astype(np.int16)
sface_16 = np.subtract(face_16, nface_16)
sface_16 = abs(sface_16)
sface = sface_16.astype(np.int8)
推荐答案
听起来数组的dtype是uint8.所有数字将被解释为0-255范围内的整数.在这里-2等于256-2，因此相减得出254.
It sounds like the dtype of the array is uint8. All the numbers will be interpreted as integers in the range 0-255. Here, -2 is equal to 256 - 2, hence the subtraction results in 254.
您需要将数组重铸为支持负整数的dtype，例如int16像这样...
You need to recast the arrays to a dtype which supports negative integers, e.g. int16 like this ...
face = face.astype(np.int16)
...然后减去.
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