Technical solutions for maintaining image detail
The following measures can be taken to address the blurring of details that can occur with Diffusion Transformer:
- Enable VAE Enhancement: Ensure correct loadingvae.safetensorsfile (335MB), this variational self-encoder reconstructs high-frequency details that need to be placed in the
models/step1xcatalogs - Controlling the number of generation steps: in
run_inference.pyScript to add--num_inference_steps 50parameter (default 30 steps), which increases the 20% computation time but significantly improves the details of the hair, texture, etc. - Post-processing program: Use the officially recommendedReal-ESRGANPerforms super-resolution reconstruction, which can be installed with additional commands:
pip install realesrgan
Experimental data show that combining VAE and 50-step inference improves the PSNR metric of 1024×1024 images by 3.2 dB
This answer comes from the articleStep1X-Edit: An Open Source Tool for Editing Images with Natural Language InstructionsThe
May not be reproduced without permission:AI productivity tools " How to avoid loss of detail in Step1X-Edit generated images?
