ComfyUI Extension: Tiled sampling for ComfyUI

Tiled sampling for ComfyUI Introduction

ComfyUI_TiledKSampler is an extension for ComfyUI that enhances the denoising process for larger images. By breaking down a large image into smaller, manageable tiles, this extension allows for more efficient and seamless denoising. This method helps to minimize visible seams in the final image, ensuring a smoother and more cohesive result. For AI artists, this means you can work with larger images without worrying about the quality degradation that often comes with traditional denoising methods.

panorama of the ocean, sailboats and large moody clouds

How Tiled sampling for ComfyUI Works

The core principle behind ComfyUI_TiledKSampler is tiling. Imagine you have a large painting that you want to clean up. Instead of trying to clean the entire painting at once, you divide it into smaller sections and clean each section individually. This is essentially what ComfyUI_TiledKSampler does with your images.

1. Tiling: The image is divided into smaller tiles based on the specified width and height.
2. Denoising: Each tile is denoised individually. The extension uses a step-by-step approach to gradually denoise all tiles, reducing the risk of visible seams.
3. Reassembly: The denoised tiles are then reassembled to form the final image. By randomizing the tile positions for each step and using different tiling strategies, the extension ensures that the seams between tiles are minimized, resulting in a smoother final image.

Tiled sampling for ComfyUI Features

ComfyUI_TiledKSampler comes with several customizable features that allow you to control the tiling and denoising process:

• tile_width: Sets the width of each tile. Adjusting this can help balance between processing time and the quality of the final image.
• tile_height: Sets the height of each tile. Similar to tile_width, this can be adjusted to optimize performance and quality.
• tiling_strategy: Determines how the image is divided into tiles. Different strategies can be used to achieve different results.

Tiling Strategies

1. Random: This strategy aims to reduce seams by randomizing the tile positions for each step. It alternates between horizontal and vertical brick patterns, which helps in minimizing visible seams. However, it may introduce some overhead per step. gif showing of the random brick tiling

2. Random Strict: Similar to the random strategy but ensures that border tiles are not cropped unfavorably. This is achieved through masking, making it incompatible with some samplers.

3. Padded: This strategy adds padding around each tile, giving it more context from its surroundings. While this can reduce seams, it requires more tiles to be processed, which can increase the overall processing time. gif showing of padded tiling

4. Simple: Divides the image into a static grid of tiles and denoises each one individually. This is the most straightforward approach but may result in more visible seams compared to other strategies.

Troubleshooting Tiled sampling for ComfyUI

Here are some common issues you might encounter while using ComfyUI_TiledKSampler and how to solve them:

1. Visible Seams: If you notice visible seams in your final image, try using the random or random strict tiling strategies. These strategies are designed to minimize seams.
2. Performance Issues: If the extension is running slowly, consider reducing the tile width and height. Smaller tiles require less processing power but may increase the risk of seams.
3. Incompatibility with Samplers: Some tiling strategies, like random strict, may not work well with certain samplers. If you encounter issues, try switching to a different tiling strategy.

Learn More about Tiled sampling for ComfyUI

For more information, tutorials, and community support, you can visit the following resources:

• ComfyUI Examples
• ComfyUI GitHub Repository
• ComfyUI Community Forums These resources provide a wealth of information to help you get the most out of ComfyUI_TiledKSampler and improve your AI art projects.