Tile-based control over SDXL enables refined manipulation of image details within upscaled blocks, offering a robust alternative to standard controlnets in complex creative workflows. This article compiles and reorganizes the provided material to present a comprehensive overview of Tile SDXL ControlNet, its workflow, strengths, limitations, and practical tips for achieving high-detail results without altering the base model’s intrinsic style.
Overview and scope
It is a SDXL based controlnet Tile model, trained with huggingface diffusers sets, fit for Stable diffusion SDXL controlnet. It is originally trained for my own realistic model used for Ultimate upscale process to boost the picture details, and control mode is My prompt is more important: type in the prompts in positive and negative text box, gen the image as you wish. If you want to change the cloth, type like a woman dressed in yellow T-shirt, and change the background like in a shopping mall. Hires fix is supported. You will get the result as below: Part2 for ultimate sd upscale application.
Key characteristics
- Tile model is designed to enhance or change the detail of the original size image, not to upscale by itself. It will not significantly change the base model style.
- Tile upscale workflow can be integrated with WebUI as a tile model using tile_resample for the Ultimate Upscale script, or via ComfortUI by loading the controlnet model and applying to the control net condition.
- Preprocessing quality affects edge handling: edge halos can appear if the output is too sharp; blur the input before controlnet when necessary. If the output is too blurry, excessive preprocessing blur or too-small source images may be the cause.
- Control strength is robust enough to substitute canny+openpose under certain conditions, expanding practical flexibility in various edge scenarios.
- IPA (Identity-Preserving Augmentation) and early stop on controlnet can improve human image fixes for high-detail outputs.
Workflow and practical steps
The Tile model is not an upscale model by itself. It adds features to the upscaled pixel blocks and should be used with proper preprocessing and workflow to achieve high-detail results.
- Prepare the input image with appropriate denoise and resolution. For ultimate upscale, a typical workflow uses image-to-image with a denoise rate around 0.1 for low-quality images (e.g., 600x400 to 1200x800) before feeding into the upscale process.
- Adjust preprocessing to avoid edge halos: ensure that the preprocessing provides the controlnet image with sufficient blurring if halos appear; if the output is too sharp, apply moderate blur before sending to ControlNet.
- Set denoise in tile-based upscale to around 0.3-0.4 for good results, and set control strength to about 0.9 for improved control over details.
- For human image fixes, use IPA and early stop on ControlNet to achieve better results while preserving realism.
- Choose a suitable base model that is realistic and aligned with your target style, recognizing that the tile model adds detail without drastically altering the base style.
In WebUI, select the tile model and apply tile_resample for the Ultimate Upscale script; in ComfyUI, load the controlnet model and apply it to the control net condition. If you attempt to use Tile in text-to-image (t2i) mode, ensure proper prompt setup to avoid unintended color modifications of the original image.
Variants and versions
There are references to multiple versions and trade-offs: V2, V1, and rank256. The trade-offs note that saving VRAM may reduce quality, and users should refer to the accompanying illustration to choose between versions. The ranking is described as Farai logo, with V2 > V1 > rank256, and material examples include carbon fiber textures used in some presets.
Image quality, edge handling, and color considerations
Edge halos are a known issue when dealing with t2i or i2i workflows. If the output exhibits a halo, increasing blur in preprocessing before ControlNet helps. If the image is overly blurred post-processing, it can be due to excessive pre-blur or the source image being too small. Conversely, excessive sharpness or color shifts can occur if the prompt configuration in t2i is not properly balanced.
To maintain color fidelity, especially when using tile models in t2i mode, a careful prompt setup is essential. Users report that improper prompt configurations can significantly modify the original image color, reinforcing the need for careful prompt engineering and controlled preprocessing.
Training data and capabilities
The Tile model is trained on a realistic dataset, emphasizing natural textures, fabrics, and environmental details. It is not intended for comic or animation applications. It is designed to enhance realistic features and textures in upscaled blocks, rather than transforming the base style entirely.
Important notes
- Tile model is not a dedicated upscaler; it augments detail within the original content size. Upscaling quality improvements come from the integrated upscale workflow rather than from the tile model alone.
- The model is best used with realistic base models and appropriate denoise and control strength settings for high-detail, faithful results.
- There is no commercial use clause specified in the provided notes; users should verify licensing terms in their deployment environment.
Potential visuals to accompany the article
Infographics or diagrams could illustrate the relationship between tile blocks, control strength, and final detail enhancements, as well as a workflow chart for ultimate upscale integration. Additionally, a schematic showing how blur levels before ControlNet influence edge halos would be informative.
Implementation tips and tips for practitioners
- When using WebUI, choose the tile model and apply tile_resample for the Ultimate Upscale script; ensure the denoise and control strength are tuned for your image.
- In ComfyUI, load the controlnet tile model and attach to the appropriate control net condition to leverage tile-based details.
- If color shifts occur in t2i mode, adjust prompts to avoid unintended color dominance and consider applying a subtle color correction node in your pipeline.
- For edge handling, maintain a balance between blur in preprocessing and sharpness in the final output to minimize halos while preserving detail.
- Choosing a good, realistic base model is important for achieving natural-looking results with tile-based enhancement.
The model supports hires fix, and it offers practical workflows for ultimate upscale applications. It also provides guidance on prompt composition, with a focus on positive and negative prompts to drive the output toward desired details while maintaining realism.
Limitations and disclaimers
- Tile model is not an upscale model and should be used in conjunction with an upscale process to achieve high-resolution outputs.
- There may be color modifications in certain setups, particularly in t2i workflows; prompt and preprocessing adjustments are necessary to mitigate such effects.
- No commercial use statement is provided; verify licensing for personal or commercial deployments.
tags: #controlnet #tile #sdxl