Practical solutions to style inconsistencies
When using PiT for image stitching, you may encounter the problem of inconsistent part styles resulting in an uncoordinated generation effect. The following are specific solutions:
- Pre-treatment of parts:Make sure all parts are from a similar style library before importing, PS/GIMP is recommended for uniform brightness, color temperature and line thickness.
- Enable IP-LoRA:Add style parameters at runtime, e.g.
--prompt "赛博朋克风格"Forced overall stylization - Model Selection:Replaced with IP-Prior models for specialized domains (e.g., anime-specific models), the GitHub repository's mod directory usually offers alternative downloads
- Layered input:Submit the parts that determine the style (e.g. head outline) first, then add the detail parts (the five senses)
The advanced solution can be done by fine-tuning the IP-Adapter model by 1) preparing 30-50 samples of the same style 2) modifying the style weight parameter in training_script.py 3) executing the fine-tune process (requires GPU support). If still unsatisfactory, it is recommended to add ControlNet for post-processing in the SDXL rendering stage.
This answer comes from the articlePiT: tool for piecing together complete images from image parts (not open)The
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