title: How to use view as blocks in Scikit-Image?
body: <p>I have a numpy array of shape <code>(12,224,224)</code>. This is 12 images of size <code>(244, 244)</code>. When I had a single image, this was simple. The image was of size <code>(x,y)</code>. For example, <code>x</code> is an image of size <code>(400,400)</code>, for which I could use <code>view_as_blocks</code> like this:</p>
  
  <pre><code>from skimage.util import view_as_blocks as vablks
  xx = vablks(x, block_shape=(8,8))
  </code></pre>
  
  <p>This would result in a block of shape <code>(50,50,8,8)</code>.
  Now I would like to know how to apply this when I have a list of images. Either I lose shape, that is my 12 images are combined into one (224,224) block broken down into <code>(28,28,8,8)</code>, or I run into a ValueError. Here is the code I tried to use for iterating over the 12 images and viewing the <code>(224,224)</code> shaped images</p>
  
  <pre><code>xx = []
  for item_ in x:
      xx.append(blockSplitter(item_))
  </code></pre>
  
  <p>where x is a list of images.</p>
  
  <p>Here is the error:</p>
  
  <pre><code>ValueError: 'block_shape' is not compatible with 'arr_in'
  </code></pre>
  
  <p>Overall, I would like to know how to view the images as blocks of 8x8 without losing the images.
  Help, Please and Thank You.</p>