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a guest Feb 23rd, 2019 60 Never
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  1. import os
  2. import numpy as np
  3. from PIL import Image
  4.  
  5. def unpickle(file):
  6.     import pickle
  7.     with open(file, 'rb') as fo:
  8.         dict = pickle.load(fo, encoding='bytes')
  9.     return dict
  10.    
  11. def rowToFile(row, label, filename):
  12.     label = str(label)
  13.     if not os.path.exists(label):
  14.         os.mkdir(label)
  15.     dim = 32
  16.     wholeImg = list()
  17.     for i in range(dim):
  18.         oneRow = list()
  19.         for j in range(dim):
  20.             oneRGB = list()
  21.             for k in range(3): # RGB
  22.                 pix = row[1024*k + 32*i + j]
  23.                 oneRGB.append(pix)
  24.             oneRow.append(oneRGB)
  25.         wholeImg.append(oneRow)
  26.     wholeImg = np.array(wholeImg)
  27.     img = Image.fromarray(wholeImg)
  28.     img.save(os.path.join(label, filename.decode('ascii')))
  29.     img.close()
  30.  
  31. trainFiles = ['data_batch_1', 'data_batch_2', 'data_batch_3', 'data_batch_4', 'data_batch_5']
  32. testFiles = ['test_batch']
  33.  
  34. files = testFiles
  35.  
  36. for oneFile in files:
  37.     oneBatch = unpickle(oneFile)
  38.     labels = oneBatch[b'labels']
  39.     data = oneBatch[b'data']
  40.     filenames = oneBatch[b'filenames']
  41.     for i in range(len(labels)):
  42.         rowToFile(data[i], labels[i], filenames[i])
  43.     print(oneFile + " is finished")
  44.  
  45. print("Everything is finished")
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