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Qwen Image Edit Virtual Try-On New Experimental LoRA Model – Full Setup & Testing
🕑 Added 2025-09-01 13:00:33 +0000 UTC
Video : https://youtu.be/CY9U59mcWqQ
In this video, we dive into the new experimental LoRA model built for virtual try-on using Qwen Image Edit in ComfyUI. Learn how to generate consistent AI characters and easily swap their outfits—perfect for creators, designers, and e-commerce professionals looking to streamline product visualization. We walk through the full setup, test the model with different garments and character types, and explore its real-world applications in fashion, advertising, and AI-generated content. Discover the strengths and current limitations of this lightweight, in-context diffusion model, and see how it compares to older, more complex workflows. Whether you're building AI avatars, creating ad creatives, or experimenting with AI fashion, this tutorial gives you practical insights into the future of virtual try-on technology.
Target Audience:
This content is ideal for AI artists, digital fashion designers, e-commerce marketers, content creators using AI tools, ComfyUI users, and developers interested in generative AI applications for virtual clothing and product placement.
Why It Matters:
Virtual try-on capabilities are in high demand across industries, especially in online retail and digital content creation. This LoRA model offers a simplified, efficient way to change outfits on AI characters without complex masking or multiple models—making it easier to generate high-quality visuals for ads, product showcases, and AI-driven videos.
Resources:
Qwen-Edit Try-On Lora (Alpha version)
https://huggingface.co/FoxBaze/Try_On_Qwen_Edit_Lora_Alpha
Qwen-Edit Try-On Lora (Alpha version)
https://huggingface.co/FoxBaze/Try_On_Qwen_Edit_Lora_Alpha
Model type: LoRA for Qwen Image Edit
Use case: Multi-reference clothing try-on
Input format: One top image (subject) + multiple bottom images (garments). For best results, use garment images that are high quality, and full body-shots for the subject.
Output format: Stylized subject wearing all garments from bottom row
