title: How to append 2 numpy Image Arrays with different dimensions and shapes using numpy
body: <p>I am making an input dataset which will have couple of thousands of images which all don't have same sizes but have same number of channels. I need to make these different images into one stack.</p>
  <pre><code>orders = (channels, size, size)
  Image sizes = (3,240,270), (3,100,170), etc
  </code></pre>
  <p>I have tried appending it to axis of 0 and one and inserting too.</p>
  <pre><code>Images = append(Images, image, axis = 0)
  </code></pre>
  <pre><code>  File &quot;d:/Python/advanced3DFacePointDetection/train.py&quot;, line 25, in &lt;module&gt;
      Images = np.append(Images, item, axis=0)
    File &quot;C:\Users\NIK\AppData\Roaming\Python\Python37\site-packages\numpy\lib\function_base.py&quot;, line 4694, in append
      return concatenate((arr, values), axis=axis)
  ValueError: all the input array dimensions except for the concatenation axis must match exactly
  </code></pre>
  <p>Ideal output shape is like (number of images, 3) 3 for number of channels and it contains different shapes of images after that.</p>