This Neural Network Will Tell You If Your Photo Is Awesome or Not (And Why You Should Give It a Try)

by Sean Setters
 
Are you curious to know how awesome your image is? Would you trust a computer algorithm to judge the merits your photo?
 
The developers at EveryPixel have created a tool to distinguish good stock photos from not-so-good ones.
 
From EveryPixel:
We are building a stock image search engine. And we want it to be the best search tool for stock image users ever. At the moment we can search across hundreds of millions of stock images and unfortunately not all of them are great. Far from it. And this is where our aesthetic detector comes in handy. There are two very important tasks it can accomplish:
 
1. Automatic Image Curation
Neural network would estimate a visual quality of every image and apply aesthetic score to every file. Later on this data would take part in the overall mix of ranking factors and help improve search results by bringing aesthetically better images to the first pages.
 
2. Bad Stock Image Terminator
There are lots and lots of unforgivingly bad stock photos. Neural network would detect photos with the lowest aesthetic score and literally weed them out from the search results.
For fun, I uploaded a few photos from my most recent portrait session. One of the images (seen atop this article) was rated very highly by the tool, while others from the same session were determined to have a much lower probability of awesomeness.
 
EveryPixel Neural Network Awesomeness Image Analyzer 2

EveryPixel Neural Network Awesomeness Image Analyzer 3

While there is certainly some entertainment value in uploading a few images to the tool to see how they score, the real beauty of this neural network analyzer is its ability to fairly accurately generate key words/tags for your images. Using the suggested tags when uploading images to your preferred social media platform may prove extremely beneficial in allowing your work to be found by those who should be most interested in seeing them.
Posted: 4/13/2017 9:08:33 AM CT   Posted By: Sean
Posted to: Canon News, Nikon News, Sony News    
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