-
Notifications
You must be signed in to change notification settings - Fork 1
/
preprocessing_CIFAR10.py
31 lines (27 loc) · 965 Bytes
/
preprocessing_CIFAR10.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
import glob
import numpy as np
import matplotlib.pyplot as plt
from skimage.io import imread, imshow
from skimage.color import rgb2gray
def unpickle(file):
import pickle
with open(file, 'rb') as fo:
dict = pickle.load(fo, encoding='bytes')
return dict
result_data = np.zeros(1024)
result_labels = []
for file in glob.glob('/media/talesmarra/9C8E-AD88/cifar-10-python/*'):
dictionary = unpickle(file)
data = dictionary[b'data']
R = data[:,0:1024]
G = data[:,1024:2048]
B = data[:,2048:3072]
rgb = np.dstack((R,G,B))
R = data[:,0:1024]*0.2125
G = data[:,1024:2048]*0.7154
B = data[:,2048:3072]*0.0721
gray = R+G+B
result_data = np.vstack((result_data,gray))
result_labels += dictionary[b'labels']
np.savetxt('/home/talesmarra/Desktop/Courses/Recent Advances ML/CIFAR10_data.dlm',result_data[1:])
np.savetxt('/home/talesmarra/Desktop/Courses/Recent Advances ML/CIFAR10_labels.dlm',result_labels)