问题
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)
Both don't give negative numbers but instead subtract the rest after 0 from 255.
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]]
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)
Working
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)
回答1:
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.
You need to recast the arrays to a dtype which supports negative integers, e.g. int16 like this ...
face = face.astype(np.int16)
...and then subtract.
回答2:
This is a problem with your datatype in the numpy array. You have a uint8 inside it, which seems to wrap around
Have a look at nfac.dtype whichwill show it to you. You have to convert it prior to your calculation operation. Use numpy.ndarray.astype to convert it or have a look at In-place type conversion of a NumPy array
来源：https://stackoverflow.com/questions/26678132/python-numpy-subtraction-no-negative-numbers-4-6-gives-254