Room Reinvented

This capability allows users to upload a photo of their room and utilizes a generative adversarial network (GAN) to apply over 30 different interior design styles. The implementation leverages pre-trained models that have been fine-tuned on a diverse dataset of interior images, ensuring high-quality style transfer. The unique aspect of this approach is the ability to maintain the original room layout while seamlessly integrating the new design elements, which is achieved through advanced image segmentation techniques.

This capability provides users with a real-time preview of style transformations as they adjust settings or select different styles. It employs WebSocket technology to maintain a live connection between the client and server, allowing for instant updates without needing to refresh the page. This enhances user experience by providing immediate feedback on changes, making the design process more interactive and engaging.

This capability allows users to compare different design styles side by side by generating multiple versions of the uploaded room image. It uses a grid layout to display the original image alongside transformed versions, enabling users to easily assess differences in aesthetics. The backend processes multiple style transformations concurrently, optimizing for performance and reducing wait times for users.