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# Untitled

a guest Oct 21st, 2019 69 Never
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1. import tensorflow as tf
2. import numpy as np
3.
4.
5. def image_to_patches(image, patch_size, stride):
6.     target_width = ((image.shape[1] - patch_size) // stride + 1) * stride + patch_size + 1
7.     target_height = ((image.shape[0] - patch_size) // stride + 1) * stride + patch_size + 1
8.
9.     image = np.pad(
10.         image,
11.         ((0, target_height - image.shape[0]), (0, target_width - image.shape[1]), (0, 0)),
12.         mode='constant'
13.     )
14.     print(f'Last pixels of the bottom row of the image:\n {image[-1, -5:]}')
15.     # here, the last row of `image` is all zeros
16.     batched_image = np.expand_dims(image, 0)
17.     patches = tf.image.extract_patches(
18.         images=batched_image,
19.         sizes=[1, patch_size, patch_size, 1],
20.         strides=[1, stride, stride, 1],
21.         rates=[1, 1, 1, 1],
23.         name=None
24.     )
25.     patches = np.array(patches)
26.     patches = np.resize(patches, (patches.shape[0] * patches.shape[1] * patches.shape[2], -1))
27.     patches = np.resize(patches, (patches.shape[0], patch_size, patch_size, image.shape[-1]))
28.     print(f'Last pixels of the bottom row of the last patch:\n {patches[-1, -1, -5:]}')
29.     return patches
30.
31.
32. def main():
33.     image = 255 * np.ones((200, 100, 3))
34.     _ = image_to_patches(image, patch_size=60, stride=50)
35.
36.
37. if __name__ == '__main__':
38.     main()
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