Key control points
Ensuring that AI-generated images truly reflect the characteristics of the goods requires a systematic quality control scheme:
- Reference image selection criteria::
- Use professionally photographed prints (not modeling prints)
- Maintain a resolution of 2000px or more
- Uses a solid color background
- Includes product standard color cards
- Cue word engineering::
- Add a description of the material (e.g. "100% Cotton T-shirt").
- Specify exact color number (Pantone or RGB values)
- Include size proportions (e.g. "70% of screen height")
- Post-calibration mechanism:: It is recommended that CLIP scores be evaluated after generation (a built-in function of UNO), and parameters should be adjusted to regenerate when the similarity is below 0.7
Advanced Tip: For high-value items, fine-tune the model with 5-10 multi-angle images (using UNO's TRAIN mode) before generating the official matching image.
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 improve the consistency of the generated image with the physical item?
