Technical principles of progressive restoration
The iterative optimization algorithm used by LanPaint simulates the modification process of a professional painter. Each round of iteration only locally optimizes the masked area, and the modification amplitude is controlled by the LanPaint_stepsize parameter, and the system defaults to 5-7 rounds of progressive adjustment. This design avoids the structural distortion caused by one-time full-volume modification, especially when dealing with sensitive areas such as the human face, it can control the expression distortion rate below 3%.
- Comparison advantage: reduces the abruptness of 82% over Stable Diffusion native inpaint
- Parameter logic: stepsize value of 0.3 indicates that each modification of the problem area of 30%
- Hardware adaptation: the iterative process supports CUDA stream parallel computation without significantly increasing the elapsed time
Medical image restoration tests showed that the method retained as much as 97.31 TP3T of detail in radiographs.
This answer comes from the articleLanPaint: A ComfyUI Image Restoration Workflow for Any ModelThe
May not be reproduced without permission:AI productivity tools " Iterative Generation Algorithm Makes LanPaint's Repairs More Natural
