CV之FR：DIY脚本通过人脸图像得到人脸特征向量并输出多张人脸图片之两两图片之间的距离
输出结果
设计思路
实现代码
from scipy import misc
import tensorflow as tf
import numpy as np
import sys
import os
import argparse
……
计算过程
prewhitened参数是 [[[ 0.12834621 0.69292342 0.78113861]
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[ 0.12834621 0.67528038 0.78113861]
...
[-1.77710188 -1.77710188 -1.61831454]
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[ 0.28713355 0.74585253 0.93992595]
...
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...
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...
[[-0.66559049 -0.41858796 0.07541709]
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...
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[-0.13629936 0.14598925 0.74585253]
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...
[-0.13629936 0.09306013 0.71056646]
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[[-0.96552214 -0.71851961 -0.24215759]
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...
[-0.18922847 0.05777406 0.67528038]
[-0.22451455 0.04013102 0.65763734]
[-0.1539424 0.18127532 0.76349557]]]
prewhitened参数是 [[[-0.41843267 0.01911131 0.37196935]
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...
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[[-0.40431834 0.00499698 0.3437407 ]
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...
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[-0.44666131 -0.00911734 0.28728342]
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[[-0.40431834 0.00499698 0.32962638]
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...
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...
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...
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...
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...
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prewhitened参数是 [[[-0.68576058 -0.65851282 -0.6721367 ]
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...
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...
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...
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...
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...
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...
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...
[ 0.67662762 0.6902515 0.74474703]
[ 0.70387538 0.71749926 0.77199479]
[ 0.73112314 0.74474703 0.79924255]]]
prewhitened参数是 [[[-1.35183598 -1.45036667 -1.43805033]
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[-1.35183598 -1.425734 -1.425734 ]
...
[ 1.43165578 1.41933944 1.46860478]
[ 1.44397211 1.41933944 1.46860478]
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...
[ 1.40702311 1.38239044 1.43165578]
[ 1.41933944 1.39470677 1.44397211]
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...
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...
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...
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...
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...
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images参数 [[[[ 0.12834621 0.69292342 0.78113861]
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[ 0.12834621 0.67528038 0.78113861]
...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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(4, 160, 160, 3)
