Designers and image editors often have to browse through large numbers of low-quality photographs before they find the stock image that is most suitable for their purposes. Now, a new algorithm has been created to filter images based on their aesthetic value and get rid of the junk before it clogs up your search results. 

Everypixel uses neural networks for ranking stock images and for this purpose has trained the algorithms to judge the aesthetic value of a stock image in the same way as a human would do.

Everypixel’s CEO Dmitry Shironosov said: “Designers, editors and experienced stock photographers helped us generate a training dataset with 946,894 positive and negative patterns. We wanted to create a technology that can measure not only aesthetics of stock images, but their commercial potential as well. This is the main difference between our smart filter and other solutions that exist today.”

The neural network is capable of estimating the visual quality of an image and applies a score to every file which, if working properly, could save many man hours of human image curation. The algorithm is currently in beta stage but you can already test it with your own images on Everypixel. We're not so sure about the scoring, but the system already looks pretty good at assigning correct keywords. How did your images do? Let us know in the comments.