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MSE Between Two Images

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Computer Vision

Difficulty: 2 | Problem written by mesakarghm
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MSE (mean squared error) is one way to compute image similarity. The MSE between two images is the sum of squared differences between every pixel values of the given two images of same dimension. 

Write a function  mse(imageA, imageB) which calculates and returns the MSE between given two images (2D NumPy arrays). 

 

Sample Input:
<class 'list'>
imageA: [[1, 2, 3], [4, 5, 6]]
<class 'list'>
imageB: [[1, 2, 3], [4, 5, 6]]

Expected Output:
<class 'float'>
0.0

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numpy has been already imported as np (import numpy as np)