43 lines
1.4 KiB
Python
43 lines
1.4 KiB
Python
import numpy as np
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from PIL import Image
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from pathlib import Path
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import sys
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cwd = Path.cwd()
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sys.path.append(cwd.as_posix())
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sys.path.append((cwd / 'test').as_posix())
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from extra.datasets import fetch_mnist
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from tqdm import trange
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def augment_img(X, rotate=10, px=3):
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Xaug = np.zeros_like(X)
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for i in trange(len(X)):
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im = Image.fromarray(X[i])
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im = im.rotate(np.random.randint(-rotate,rotate), resample=Image.BICUBIC)
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w, h = X.shape[1:]
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#upper left, lower left, lower right, upper right
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quad = np.random.randint(-px,px,size=(8)) + np.array([0,0,0,h,w,h,w,0])
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im = im.transform((w, h), Image.QUAD, quad, resample=Image.BICUBIC)
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Xaug[i] = im
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return Xaug
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if __name__ == "__main__":
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import matplotlib.pyplot as plt
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X_train, Y_train, X_test, Y_test = fetch_mnist()
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X_train = X_train.reshape(-1, 28, 28).astype(np.uint8)
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X_test = X_test.reshape(-1, 28, 28).astype(np.uint8)
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X = np.vstack([X_train[:1]]*10+[X_train[1:2]]*10)
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fig, a = plt.subplots(2,len(X))
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Xaug = augment_img(X)
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for i in range(len(X)):
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a[0][i].imshow(X[i], cmap='gray')
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a[1][i].imshow(Xaug[i],cmap='gray')
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a[0][i].axis('off')
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a[1][i].axis('off')
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plt.show()
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#create some nice gifs for doc?!
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for i in range(10):
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im = Image.fromarray(X_train[7353+i])
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im_aug = [Image.fromarray(x) for x in augment_img(np.array([X_train[7353+i]]*100))]
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im.save(f"aug{i}.gif", save_all=True, append_images=im_aug, duration=100, loop=0)
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