Google Photos announced an upcoming AI-powered feature that will convert images of clothing into a digital wardrobe, allowing users to create outfits and preview them through virtual try-on tools.
AI Builds Digital Wardrobe From Photo Library
The feature uses artificial intelligence to scan a user’s photo library and identify clothing items and accessories. It then creates a digital version of the wardrobe inside the app. Users can organize items by categories such as tops, bottoms, and jewelry, making it possible to combine pieces into different outfit options directly within the interface.
Outfit Creation And Sharing Tools Integrated
Once outfits are created, users can save them to a digital moodboard or share them with others. The moodboard supports organizing looks for specific contexts, including travel, events, work, or social occasions, allowing users to plan outfits in advance.
Virtual Try-On Expands Feature Set
The update also includes a virtual try-on function that enables users to preview how selected combinations will look. This adds a visual layer to outfit planning beyond static image matching.
Feature Draws Inspiration From Popular Culture
The concept reflects the virtual wardrobe system featured in the film Clueless, where the main character used a digital interface to browse outfit combinations. The new feature adapts that idea using AI to automate clothing recognition and organization.
Rollout Timeline And Platform Availability
Google said the feature is not yet live. It is scheduled to roll out on Android later this summer, followed by iOS. Within the app, it will appear under the “Collections” section.
Competitive Landscape Includes Existing Fashion Apps
The feature will compete with existing wardrobe and styling applications such as Acloset, Combyne, Pureple, Whering, and Alta.
AI Recognition Relies On Image Quality
Google did not provide technical details about how the AI system operates but said it identifies clothing items from images stored in the user’s library to create digital representations. The effectiveness of the feature may depend on image quality, as clearer and more complete photos of clothing could improve recognition accuracy.
Featured image credits: Smith Collection/Gado via Laptop Mag
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