title: Can't reshape the numpy array containing PNG images
body: <p>I've trained a Handwritten image classifier using Keras library in Python. Initially I've used standard MNIST dataset for training and testing purpose. But now I want to use my own data set for testing, in which all the images are size <code>900*1200*3</code> instead of <code>28*28*1</code> </p>
  
  <p>So I need to reshape all the images before testing. I'm using following code to reshape but it give errors. </p>
  
  <p><strong>Code:</strong></p>
  
  <pre><code>bb =  lol.reshape(lol.shape[0], 28, 28, 1).astype('float32')
  </code></pre>
  
  <p>where <code>lol</code> is my numpy array containing 55 images of shape <code>(900,1200,3)</code></p>
  
  <p>and the Error log is as following:</p>
  
  <pre><code>ValueError                                Traceback (most recent call last)
  &lt;ipython-input-46-87da95da73e9&gt; in &lt;module&gt;()
       24 #     # you can show every image
       25 #     img.show()
  ---&gt; 26 bb =  lol.reshape(lol.shape[0], 28, 28, 1).astype('float32')
       27 # model = loaded_model
       28 # classes = model.predict(bb)
  
  ValueError: cannot reshape array of size 178200000 into shape (55,28,28,1)
  </code></pre>
  
  <p>So what am I doing wrong? Can I get accurate predictions even after resizing the large images to very small images of 28*28?  Thanks for help. </p>