Virtual try on AI Virtual Try-On Diffusion with Segmind API This project uses the Segmind API to enable virtual try-on experiences. By utilizing Segmind's API, we leverage advanced machine learning models for clothing fitting and realistic image generation, allowing users to try on clothing items virtually with just a photo. The API uses cutting-edge technology to seamlessly blend clothing items into user images, providing a highly interactive and realistic way to visualize how garments would look when worn.
Project Overview Virtual Try-On Diffusion with Segmind API integrates Segmind's AI models to perform virtual garment fitting using a diffusion-based approach. The user simply uploads a photo, and the system uses the API to generate an image showing them wearing different clothing items from the catalog.
Key Features: Easy Integration with Segmind API: Seamlessly interact with the Segmind API for model inference and image processing. Realistic Try-Ons: The system overlays clothing items in a natural and realistic manner, considering fit and alignment. Fast Image Generation: Thanks to the Segmind API, the try-on process is quick, with high-quality results delivered in seconds. Interactive User Experience: Users can upload their image and instantly see how different clothes look on them. How It Works Image Input: The user uploads their image (portrait or full-body) into the system. Garment Selection: The user selects a clothing item (such as a shirt, jacket, or dress) from a catalog of items. Segmind API Processing: The system sends the image and clothing item to the Segmind API for processing. The API uses AI models to combine the garment with the user's image. Diffusion Model Output: A high-quality image of the user wearing the selected clothing item is generated, thanks to the powerful AI diffusion models from Segmind. Results Display: The final output is displayed to the user.
running command (python scripts/try_on_diffusion.py)
