tf.extract_image_patches的理解记录-20201102

import tensorflow as tf

n = 10
# images is a 1 x 10 x 10 x 1 array that contains the numbers 1 through 100 in order
images = [[[[x * n + y + 1] for y in range(n)] for x in range(n)]]

# We generate four outputs as follows:
# 1. 3x3 patches with stride length 5
# 2. Same as above, but the rate is increased to 2
# 3. 4x4 patches with stride length 7; only one patch should be generated
# 4. Same as above, but with padding set to 'SAME'


import numpy as np
images = np.array(images)
print(images.shape)
print(images[0,:,:,0])

with tf.Session() as sess:
    print(sess.run(tf.extract_image_patches(images=images, ksizes=[1, 3, 3, 1], 
                                            strides=[1, 1, 1, 1], rates=[1, 1, 1, 1], padding='VALID')), '\n\n')
#     print(sess.run(tf.extract_image_patches(images=images, ksizes=[1, 3, 3, 1], 
#                                  strides=[1, 5, 5, 1], rates=[1, 2, 2, 1], padding='VALID')), '\n\n')
#     print(sess.run(tf.extract_image_patches(images=images, ksizes=[1, 4, 4, 1], 
#                                  strides=[1, 7, 7, 1], rates=[1, 1, 1, 1], padding='SAME')), '\n\n')
#     print(sess.run(tf.extract_image_patches(images=images, ksizes=[1, 4, 4, 1], 
#                                  strides=[1, 7, 7, 1], rates=[1, 1, 1, 1], padding='SAME')))

根据提示，是将左上角的*内容展平得到，可以对应上面的代码结果辅助理解

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