A four-step optimization method to improve image quality
The following hands-on program can be adopted to address the problem of blurred PiT output:
- Input Optimization:Part resolution is recommended to be 512px or higher, with transparent or solid color background to avoid JPEG compression artifacts
- Parameter Adjustment:When running the script add the
--steps 50Boost the number of iterations, add--cfg_scale 7.5Enhanced details - Model Enhancement:Replacement of high-res SDXL variants on HuggingFace (e.g. stabilityai/stable-diffusion-xl-base-1.0)
- Post-processing:Super-resolution reconstruction of output using ESRGAN or Real-ESRGAN
Hardware level suggestions: 1) Make sure CUDA version matches torch 2) Add video memory when it's not enough--low_vramParameters 3) Select T4/V100 graphics card when running on cloud platforms such as colab. For specific areas (e.g. jewelry design), exclusive IP-Prior models can be trained to enhance local detail reproduction.
This answer comes from the articlePiT: tool for piecing together complete images from image parts (not open)The
May not be reproduced without permission:AI productivity tools " How to optimize the sharpness of images generated by PiT?
