Photo editing can be a painstaking process that involves hours of tweaking and adjusting a photo to perfect it. Over the years the algorithms that filters and other editing tools use have improved by leaps and bounds, and it should come as no surprise that the next big step forward seems to involve utilizing the machine learning of Artificial Intelligence (AI).
In theory machine learning could be used to improve several areas of photo editing. It could result in more ‘intelligent’ filters that are able to better understand the images and colors of photos and improve them accordingly. At the same time machine learning could also be used to create other types of adaptive tools that make photo editing easier, or automate certain tasks.
While this may sound like future tech, it is actually very much in the present. Machine learning is already being used to improve photo editing at this very moment Click To Tweet in a variety of different ways.
Uses of Machine Learning
One of the most notable uses of machine learning in photo editing is by none other than Google. Over the last few years the researchers on its Machine Perception team have been training AI to identify impressive landscape photos from Google Street View and then edit them. To determine the success of the experiment Google showed the results alongside other landscape photos to professional photographers and had them grade their quality – and over 40% of Google’s submissions were deemed to be ‘semi-professional’ or ‘professional’.
Another interesting project is the Neutral Photo Editor created by a team at the University of Edinburgh. Within this editor is a ‘contextual paintbrush’ that attempts to predict how users intend to edit their photo based on the color they select as well as the context of the image. In other words this single brush could be used for a wide range of different tasks, and will intuitively change itself on a situational basis.
Make no mistake there are many other examples of how machine learning is improving photo editing. In some cases it is used to automatically label layers or identify and straighten horizons. Similarly it could automatically detect common issues with photos such as shadowy images, low-light conditions, or motion blur and compensate for them.
Although machine learning is seeing practical use in photo editing, it is still far from available in the current generation of editors. For now if you would like to be able to more easily and conveniently edit your photos you should try using an intuitively designed editor such as Movavi Photo Editor.
While it may not use machine learning per se, Movavi Photo Editor does automate and simplify a lot of the tasks that photo editing involves. Because of how user-friendly it is there is practically no learning curve involved and you’ll be able to almost immediately apply its features to improve the quality of your photos, remove unwanted objects, add captions, apply filters, touch up portraits, replace the background, and much more.