ComfyUI Extension: ComfyUI jank HiDiffusion

ComfyUI jank HiDiffusion Introduction

Welcome to comfyui_jankhidiffusion, an experimental extension for ComfyUI that integrates the innovative techniques of HiDiffusion. This extension aims to enhance the resolution and quality of images generated by diffusion models, particularly Stable Diffusion 1.5 (SD 1.5). By leveraging advanced downscaling and attention mechanisms, comfyui_jankhidiffusion helps artists create more detailed and higher-quality images without extensive technical adjustments.

How ComfyUI jank HiDiffusion Works

At its core, comfyui_jankhidiffusion employs two main techniques: RAU-Net and MSW-MSA attention.

1. RAU-Net (Recurrent Attention U-Net): This technique scales down the image at the beginning of the generation process. Think of it as sketching the broad strokes of a painting before filling in the finer details. By starting with a smaller image, the model can focus on getting the major elements right (like the number of legs on a character). As the process continues, the image is scaled back up, allowing the model to refine and add intricate details. This method uses convolution with stride/dilation and pool averaging for downscaling, which is different from the traditional bicubic downscaling.
2. MSW-MSA (Multi-Scale Windowed Multi-Head Self-Attention): This attention mechanism enhances the performance and quality of high-resolution image generation. It divides the image into smaller windows and applies self-attention within these windows, which helps in managing the computational load and improving the overall quality of the generated images.

ComfyUI jank HiDiffusion Features

RAU-Net

• Downscaling and Upscaling: RAU-Net scales down the image initially and then scales it back up, allowing the model to focus on major details first and refine them later.
• Customizable Parameters: You can adjust the start and end times for the scaling effect, as well as the specific blocks to which the effect is applied.
• Compatibility: Works best with SD 1.5 models. Limited support for SDXL and other models.

MSW-MSA Attention

• Performance Boost: Enhances the performance of SD 1.5 models, especially at high resolutions.
• Quality Improvement: Reduces artifacts and improves the overall quality of the generated images.
• Customizable Blocks: You can specify which blocks to apply the attention mechanism to, allowing for fine-tuning based on your needs.

ComfyUI jank HiDiffusion Models

comfyui_jankhidiffusion primarily supports SD 1.5 models. While it can be used with SDXL and other models, the results may vary, and some features might not work as effectively.

Recommended Settings for SD 1.5

• RAU-Net: Input block 3, output block 8, CA input block 4, CA output block 8, start time 0.0, end time 0.45. - MSW-MSA Attention: Input blocks 1, 2; output blocks 9, 10, 11.

Recommended Settings for SDXL

• RAU-Net: Input block 3, output block 5, disable CA or set CA input block 2, CA output block 7. - MSW-MSA Attention: Input blocks 4, 5; output blocks 4, 5.

Troubleshooting ComfyUI jank HiDiffusion

Common Issues and Solutions

1. Aspect Ratio Problems: Not all aspect ratios work with the MSW-MSA attention node. Use resolutions that are multiples of 64 or 128.
2. ControlNet Compatibility: RAU-Net may not work properly with ControlNet while the scaling effect is active. Adjust the RAU-Net parameters to minimize conflicts.
3. Performance with SDXL: MSW-MSA attention does not significantly improve performance with SDXL models. Adjust the start time for extreme resolutions.

Frequently Asked Questions

• Why is my image not generating correctly? Ensure that you are using the recommended settings for your model. Check if the aspect ratio is a multiple of 64 or 128.

• How do I disable RAU-Net? Execute the workflow once with the RAU-Net node toggled to disabled to ensure the changes are applied.

• Can I use other custom nodes with comfyui_jankhidiffusion? Some custom nodes may conflict with comfyui_jankhidiffusion. Notably, FreeU Advanced may cause issues. Use the provided workarounds or avoid using conflicting nodes.

Learn More about ComfyUI jank HiDiffusion

For more detailed information and advanced usage, refer to the HiDiffusion GitHub repository. You can also explore the ComfyUI documentation for additional insights and community support.

By understanding and utilizing the features of comfyui_jankhidiffusion, you can significantly enhance the quality and resolution of your AI-generated images, making your creative process more efficient and effective.