Description
Is your feature request related to a problem? Please describe.
Currently, diffusers library lacks advanced tiled upscaling capabilities that are available in other Stable Diffusion implementations. While the library supports basic img2img and upscaling, there's no built-in solution for handling large images through intelligent tiling and seam fixing. This makes it difficult to process high-resolution images while maintaining quality and managing memory efficiently.
Describe the solution you'd like
Implement Ultimate SD Upscale functionality (similar to Automatic1111's WebUI extension) as a pipeline in diffusers. Key features should include:
- Progressive upscaling with intelligent scale factor determination
- Multiple tiling modes:
- Linear processing
- Chess pattern processing
- Advanced seam fixing options:
- Band pass mode
- Half tile offset
- Half tile with intersections
- Configurable parameters:
- Tile sizes
- Padding
- Mask blur
- Denoise strength for seam fixing
The implementation should integrate smoothly with existing diffusers pipelines and maintain the library's user-friendly API style.
Describe alternatives you've considered
- Using basic tiling without seam fixing (leads to visible artifacts)
- Running multiple separate upscale passes (inefficient and lower quality)
- Implementing as a separate package (loses benefits of diffusers' optimization and integration)
- Using other libraries like PIL or cv2 for tiling (lacks SD-specific optimizations)
Additional context
- Reference implementation: https://github.com/Coyote-A/ultimate-upscale-for-automatic1111
- This feature would be particularly valuable for:
- Professional image upscaling
- Batch processing of large images
- Creating high-resolution outputs while managing VRAM
- Maintaining image quality in tiled processing
- Could potentially be implemented as either a standalone pipeline or an enhancement to existing img2img pipelines
- Would complement existing super-resolution models in the library
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