

Catvton
Overview :
CatVTON is a virtual try-on technology based on a diffusion model, featuring a lightweight network (total of 899.06M parameters), parameter-efficient training (49.57M trainable parameters), and simplified inference (less than 8G VRAM at 1024X768 resolution). By streamlining the network structure and inference process, it achieves quick and effective virtual fitting results, making it particularly suitable for the fashion industry and personalized recommendation scenarios.
Target Users :
CatVTON is primarily designed for fashion designers, clothing retailers, and personalized recommendation platforms. It helps users quickly generate virtual fitting effects, thereby enhancing design efficiency and customer satisfaction.
Use Cases
Fashion designers use CatVTON to quickly generate virtual fitting images, enhancing design efficiency.
Clothing retailers leverage CatVTON to offer personalized fitting experiences to customers, increasing satisfaction.
Personalized recommendation platforms integrate CatVTON to provide users with more accurate clothing recommendations.
Features
Lightweight network design to reduce the model's parameter count.
Parameter-efficient training to decrease the number of parameters needed for training.
Simplified inference process to lower hardware resource requirements.
Support for deployment on ComfyUI, facilitating integration into existing systems.
Provision of a Gradio App deployment option, enabling users to quickly experience the application.
Automatic download of weight files to streamline the user experience.
How to Use
First, install the required environment and dependencies according to the Installation Guide.
Next, follow the Deployment Guide to download and deploy CatVTON to ComfyUI or run it as a Gradio App.
Then, prepare the dataset and preprocess the data according to the Inference Guide.
Finally, execute the inference.py script to initiate the virtual fitting inference process.
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