

Ootdiffusion
Overview :
OOTDiffusion is an open-source virtual clothing try-on tool based on a latent diffusion model. It supports both semi-body and full-body models, enabling natural integration of clothing. Users can adjust various parameters to achieve precise control over the try-on effects, meeting diverse needs. This tool is open-source on GitHub and has received over 300 stars of attention.
Target Users :
["To try on clothing effects without purchasing or physically trying them on","To generate photos showcasing different clothing effects","For developing applications or websites with virtual try-on features"]
Use Cases
Virtual try-on on Taobao
Post-processing of model photos
Clothing effect display on e-commerce websites
Features
High-quality image generation based on the latent diffusion model
Supports semi-body and full-body virtual try-on modes
Controllable try-on parameters to meet various demands
Natural clothing integration and realistic try-on effects
Featured AI Tools
Chinese Picks

Capcut Dreamina
CapCut Dreamina is an AIGC tool under Douyin. Users can generate creative images based on text content, supporting image resizing, aspect ratio adjustment, and template type selection. It will be used for content creation in Douyin's text or short videos in the future to enrich Douyin's AI creation content library.
AI image generation
9.0M

Outfit Anyone
Outfit Anyone is an ultra-high quality virtual try-on product that allows users to try different fashion styles without physically trying on clothes. Using a two-stream conditional diffusion model, Outfit Anyone can flexibly handle clothing deformation, generating more realistic results. It boasts extensibility, allowing adjustments for poses and body shapes, making it suitable for images ranging from anime characters to real people. Outfit Anyone's performance across various scenarios highlights its practicality and readiness for real-world applications.
AI image generation
5.3M