Google Photos' new AI feature turns your clothes into digital closet

Google Photos is about to make your morning outfit decision a lot less painful. The app announced a new AI-powered feature that scans your existing photo library, identifies the clothes you own, and builds a fully browsable digital wardrobe no separate app required.

The tool analyses existing photographs which you have stored in your Google Photos account to extract distinct clothing pieces from those images. Users will be able to browse their wardrobe by category including tops, bottoms, accessories, jewellery and mix-and-match pieces to create new outfits.

Users can store their outfit combinations in a digital mood board which they can organise according to different occasions including travel, work, date night, events and more.

Google has not disclosed its AI system features yet; the system operates to identify clothing and accessory items through its analysis of existing photo content. The company suggests that well-lit full-body photographs will produce optimal results because they deliver the most accurate extraction results.

Google used the virtual wardrobe from the 1995 movie Clueless as its inspiration for product development which marks its first time doing so. For more than 30 years fashion startups have pursued that idea which Google developed. Google needs to achieve massive user adoption because its outfit photos from Google Photos existing bank will provide immediate access to users who already possess this content.

Users can use a separate virtual try-on function to see how different outfit combinations will look on them. The product now competes directly with specialised styling applications which include Acloset Combyne Pureple Whering and Alta because it has evolved from its previous role as a catalogue application.

The feature has not yet been activated. The first launch of the Google product will take place on Android devices this summer and the company will release an iOS version later. The Google Photos application on both platforms will display the feature in the Collections tab.