Module code >> skvideo.measure.mse
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Source code for skvideo.measure.mse

from ..utils import *
import numpy as np
import scipy.ndimage


[docs]def mse(referenceVideoData, distortedVideoData): """Computes mean-squared error (MSE). Both video inputs are compared frame-by-frame to obtain T MSE measurements. Parameters ---------- referenceVideoData : ndarray Reference video, ndarray of dimension (T, M, N, C), (T, M, N), (M, N, C), or (M, N), where T is the number of frames, M is the height, N is width, and C is number of channels. distortedVideoData : ndarray Distorted video, ndarray of dimension (T, M, N, C), (T, M, N), (M, N, C), or (M, N), where T is the number of frames, M is the height, N is width, and C is number of channels. Returns ------- mse_array : ndarray The mse results, ndarray of dimension (T,), where T is the number of frames """ referenceVideoData = vshape(referenceVideoData) distortedVideoData = vshape(distortedVideoData) assert(referenceVideoData.shape == distortedVideoData.shape) T, M, N, C = referenceVideoData.shape assert C == 1, "mse called with videos containing %d channels. Please supply only the luminance channel" % (C,) scores = np.zeros(T, dtype=np.float32) for t in range(T): referenceFrame = referenceVideoData[t].astype(np.float32) distortedFrame = distortedVideoData[t].astype(np.float32) mse = np.mean((referenceFrame - distortedFrame)**2) scores[t] = mse return scores