Triple guarantee mechanism for precise regional protection
To ensure the integrity of non-targeted areas, the following protective measures may be used:
- directive qualification method::
- Use of spatial locators: "Modify only the trees on the left side of the screen"
- Add protection statement: "Keep the character's face exactly the same"
- Color Lock: "Don't affect the background of the same shade when you change the color of your skirt" - Technical protective layer::
1. Pre-processing phase:
- Generating a protective area mask using the SAM model
- Pass the protected_areas parameter through the API
2. Reasoning phase:
- Set attention_mask_scale=0.3
- Enable the content_preserve plugin - Post-calibration program::
- Compare before and after images with PSDChecker tool
- Critical Area Setting 5% Tolerance Thresholds
- Building automated regression test sets
The combined use of the above methods can increase the success rate of non-targeted area protection to more than 95%
This answer comes from the articleQwen-Image-Edit: an AI model for editing images based on textual commandsThe
May not be reproduced without permission:AI productivity tools " How to avoid accidental modification of non-target areas during image editing?
