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  • Post by: Super User

fashion designer working on a new collection has an idea, but wonders if it’s been done before. Another is looking for historical inspiration—1950s-style wasp waists or 80s-era padded shoulders.

Soon, they might turn to Cognitive Prints for help. The suite of AI tools IBM is developing for the fashion industry can take a photo of a dress or a shirt and search for similar garments. It can search for images with specific elements—Mandarin collars, for example, or gladiator laces, or fleur-de-lis prints. It can also design patterns itself, based on any image data set a user inputs—architectural images, amoebas, sunsets.

“Fashion designers arduously put in efforts and time in coming up with new designs which could potentially be trend-setters,” says Priyanka Agrawal, a research scientist at IBM Research India, who has worked on Cognitive Prints. “Additionally, they have inspirations like architecture or technology, which they aspire to translate into their work. However, it becomes difficult to do something novel and interesting every single time. We wanted to make it easier for them by augmenting the design lifecycle.”

The AI image search engine, a collaboration between IBM and the Fashion Institute of Technology (FIT), was trained using 100,000 print swatches from 10 years of winning Fashion Week entries. Users can filter results by year, designer or inspiration (say, “Japanese street wear”). Designers can get inspired, or can make sure their inspiration is really their own and not inadvertent plagiarism (Gucci was recently accused of ripping off designs from legendary Harlem tailor Dapper Dan; they’ve since launched a collaboration).

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