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author | nunzip <np.scarh@gmail.com> | 2018-10-23 16:51:08 +0100 |
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committer | Vasil Zlatanov <v@skozl.com> | 2018-10-29 15:34:12 +0000 |
commit | 1b1d22a025c23703b05b08204276a4066ebbe9bc (patch) | |
tree | ba93b0a42a44f720c54a7c49e562230ea349ca04 | |
parent | 5b3291144270dc4736ce0c1fd5dda52ba6808d22 (diff) | |
download | vz215_np1915-1b1d22a025c23703b05b08204276a4066ebbe9bc.tar.gz vz215_np1915-1b1d22a025c23703b05b08204276a4066ebbe9bc.tar.bz2 vz215_np1915-1b1d22a025c23703b05b08204276a4066ebbe9bc.zip |
Rotate faces
-rwxr-xr-x | train.py | 4 |
1 files changed, 2 insertions, 2 deletions
@@ -6,7 +6,7 @@ import matplotlib.pyplot as plt import sys import random - +from numpy import linalg as LA from random import randint from sklearn.neighbors import KNeighborsClassifier @@ -105,7 +105,7 @@ if args.faces: sys.exit("Can not plot eigenfaces when using LDA") for i in range(args.faces): ax = plt.subplot(2, args.faces/2, i + 1) - ax.imshow(pca.components_[i].reshape([46, 56])) + ax.imshow(pca.components_[i].reshape([46, 56]).T) plt.show() if args.principal: |