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April 6, 2022 09:20
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import os | |
import cv2 | |
import numpy as np | |
train_image = 'train-images-idx3-ubyte' | |
train_label = 'train-labels-idx1-ubyte' | |
test_image = 't10k-images-idx3-ubyte' | |
test_label = 't10k-labels-idx1-ubyte' | |
for f in [train_image, train_label, test_image, test_label]: | |
os.system('wget --no-check-certificate http://yann.lecun.com/exdb/mnist/%s.gz' % (f,)) | |
for f in [train_image, train_label, test_image, test_label]: | |
os.system('gunzip %s.gz' % (f,)) | |
for image_f, label_f in [(train_image, train_label), (test_image, test_label)]: | |
with open(image_f, 'rb') as f: | |
images = f.read() | |
with open(label_f, 'rb') as f: | |
labels = f.read() | |
images = [ord(d) for d in images[16:]] | |
images = np.array(images, dtype=np.uint8) | |
images = images.reshape((-1,28,28)) | |
outdir = image_f + "_folder" | |
if not os.path.exists(outdir): | |
os.mkdir(outdir) | |
for k,image in enumerate(images): | |
cv2.imwrite(os.path.join(outdir, '%05d.png' % (k,)), image) | |
labels = [outdir + '/%05d.png %d' % (k, ord(l)) for k,l in enumerate(labels[8:])] | |
with open('%s.txt' % label_f, 'w') as f: | |
f.write(os.linesep.join(labels)) |
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