调整3D图像与5D张量tensorflow

Question

我使用3D卷积我的网络。在我的网络节点中，我需要将图像从[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。

我试图用tf.image.resize_images，但现在看来，这只是工作的3D or4D张量。

任何建议我可以做什么？

Answer 1

没问题，我们仍然可以使用tf.image.resize_images。我们需要做的是发送数据到tf.image.resize_images它需要的形状是张量（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]