This week, I unexpectedly found myself trying on Kate Hudson’s iconic yellow dress from “How to Lose a Guy in 10 Days,” thanks to Google’s new AI fashion experiment, Doppl. This innovative app allows users to virtually try on outfits by simply taking a full-body photo and uploading an image of the desired clothing item. Within a minute, an AI-generated digital version of yourself dons the chosen outfit, reminiscent of Alicia Silverstone’s digital closet in “Clueless.” Eager to test the app’s capabilities, I was both curious and slightly apprehensive about how accurately my digital twin would reflect my style and proportions.
Doppl, which made its debut as part of Google Labs, serves as a blend of a fashion tool and a tech experiment. Users can upload photos of any outfit they fancy, whether from online stores or thrift shops. Moreover, if users prefer not to upload their own images, they can select from a variety of preset AI models representing different body types, ages, and races. This broad inclusivity aligns with current trends towards diversity in fashion, making it accessible for a larger audience. However, Google cautions that the tool may not be perfect, acknowledging the limitations in its current capabilities, mainly focusing on tops, bottoms, and dresses, while excluding essential accessories like shoes and bags.
I was excited to try out different looks, especially from my Pinterest board titled “The Life of a Shopping Addict.” One particular outfit I aimed to replicate—a black tank top paired with a flowy skirt—left me underwhelmed when the generated image appeared instead as a short black mini dress with boots that didn’t even remotely resemble my desired look. Other tests yielded better results; for instance, when I uploaded a pair of jeans from Zara, the app surprisingly included a belt in the rendering, even though accessories are officially unsupported. This nuanced detail indicated that Doppl’s recognition capabilities might occasionally surpass expectations, even if inconsistently.
While I found that the app performs best with straightforward outfits, it struggles with more complex styles, often producing glitchy results or entirely unintended clothing configurations. When the AI succeeds, it can be convincing enough to persuade you to make a purchase, as it did with me—I ended up buying the Zara jeans. Such outcomes highlight the potential utility of the app, even if it doesn’t revolutionize the fashion industry or guarantee a doubling of sales for retailers.
Despite its intriguing technology, Doppl is not without flaws. The absence of personalized metrics, such as height or specific body measurements, prevents users from receiving fully tailored try-on experiences, which is crucial for anyone looking for accurate fittings. Additionally, the app has age and account restrictions, confining its use to individuals over 18 with a Google account residing in the U.S. These limitations may hinder broader accessibility and usability for prospective users who would benefit from the app’s features.
In conclusion, while Doppl may not yet be capable of replacing traditional dressing rooms, its free, user-friendly design approaches the experience effectively. Whether it can ultimately instigate a trend in virtual styling or influence shopping habits remains to be seen, but it certainly provides an engaging experience that could encourage users to buy what they were already considering, reminding us that technology continues to integrate itself into our daily lives in imaginative ways.
