Google Photos' AI-powered virtual closet is now available to all users in the United States, Brazil, and India on both iOS and Android. The feature, which turns photos of a user's outfits into a digital wardrobe, was announced earlier this year with plans for a summer rollout. Android users were the first to receive access, beginning in June, and the tool has now expanded to iOS.
The feature draws its inspiration from the virtual wardrobe app used by the character Cher in the movie Clueless. In the film, that digital closet was a sign of her privileged Beverly Hills lifestyle, since she owned so many outfits that she needed a system to organize them and decide what to wear. Google's version aims to bring similar organizational technology to a broader audience.
The company uses AI to build a copy of a user's wardrobe based on the items they wore in their photos. Within the app, users can sort items by category, including tops, bottoms, and jewelry, and then combine them to assemble different outfits. Google says the feature is intended to help the user choose what to wear.
Google also says it does not share data about how a user dresses or what they wear with third parties, such as retailers. The virtual closet's wider release accompanies several other updates to Google Photos. One is a way to select, brighten, and share photos using a single prompt in Gemini Spark, which requires a Google AI Pro or Ultra subscription in the United States.
An upgraded Markup tool is part of the same batch of changes. It adds a redacting pen that can blur sensitive information such as license plates, precise thickness sliders for custom sketches, and a choice of fonts when adding text to photos. There are also more Remix templates that use AI to transform photos.
Android users are receiving new photo filters as well. The filters, called Moods, give images different looks, including 35mm film and 2000s digicam. The virtual closet and the accompanying updates together represent Google's latest push to fold AI tools into its Photos app across supported markets.
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