<p>I guess you work from face images. To perform data augmentation on these images, you can:</p>

<ul>
<li>rotate a little the image, </li>
<li>modify tilt and slant (a little)</li>
<li>crop (a little) </li>
<li>flip left-right</li>
<li>add noise (salt and pepper, Gaussian...)</li>
<li>change luminosity</li>
</ul>

<p>And of course, <strong>mix</strong> two or more of the above processes. See <a href="https://github.com/aleju/imgaug" rel="nofollow noreferrer">imgaug</a> for example.</p>

<p>With more work, you can try style transfer on your images or modify them with GANs. See <a href="https://arxiv.org/abs/1904.11685" rel="nofollow noreferrer">this paper</a></p>
What to do when you have different amount of data in different classes?
<p>I'm working on an age classification problem. When I created classes, based on age group, different age groups have a different number of images. One has only around 1100 pictures and another has around 4500 pictures. I know 1100 pictures are not enough for a class. How do I make more data on the class that has less data? Is there a way to make good data artifacts ?</p>