prescription
To address the feature confusion problem that is likely to occur when multiple products are displayed in the same frame in e-commerce scenarios, UNO realizes precise control through the following methods:
- UnoPE Technology Applications: Utilizing a generalized rotational position embedding technique to assign an independent coding space to the subjects in each reference image, the system automatically learns the feature boundaries of different subjects
- Resolution Optimization Settings: Set the reference image resolution to 320×320 (via the -width and -height parameters), a size that balances detail retention with feature differentiation in multi-subject scenes
- Reference image specification: Each product image uploaded should maintain
- The main body accounts for more than 60% screen
- Background as pure as possible
- Use separate image uploads for different products
Practical case: suppose we need to generate the "sneakers and backpack in outdoor scene" picture, we should shoot separate close-ups of shoes and backpack to avoid the same frame in the initial material, and then upload them through UNO's image_ref1/image_ref2 respectively.
This answer comes from the articleUNO: Support for single-subject and multi-subject customized image generation tools (suitable for e-commerce graphics)The
Related files download url
You need to log in to download this resource. Go to log in
© Download resources copyright belongs to the author; all resources on this site are from the network, for learning purposes only, please support the original version!
May not be reproduced without permission:AI productivity tools " How to solve the problem of confusing the characteristics of multi-subject goods in e-commerce matching pictures?
English 
简体中文 
日本語 
Deutsch 
Português do Brasil