Question

我正在为我的网络使用3D卷积。在我的网络节点中，我需要将我的图像从[5,50,50,10,256]调整为[5,100,100,10,256]。我只想调整图像的轴1和轴2的大小。

我尝试使用tf.image.resize_images，但它似乎只适用于3D或4G张量。

任何建议我该怎么办？

Answer 1

没问题，我们仍然可以使用tf.image.resize_images。我们需要做的是将数据以所需的形状发送到 tf.image.resize_images ，这是一个张量（4D）。

# First reorder your dimensions to place them where tf.image.resize_images needs them
transposed = tf.transpose( yourData, [0,3,1,2,4] )

# it is now [5,10,50,50,256]
# but we need it to be 4 dimensions, not 5
reshaped = tf.reshape( transposed, [5*10,50,50,256] )

# and finally we use tf.image.resize_images
new_size = tf.constant( [ 100 , 100 ] )
resized = tf.image.resize_images( reshaped , new_size )

# your data is now [5*10,100,100,256]
undo_reshape = tf.reshape( resized, [5,10,100,100,256] )

# it is now [5,10,100,100,256] so lastly we need to reorder it
undo_transpose = tf.transpose( undo_reshape, [0,2,3,1,4] )

# your output is now [5,100,100,10,256]

使用张量流中的5D张量调整3D图像的大小

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