ComfyUI Extension: TBG’s ComfyUI Development Takeaways
A curated collection of reusable ComfyUI nodes developed by TGB. These sidecodes encapsulate key breakthroughs in model sampling, noise scheduling, and image refinement for enhanced stable diffusion workflows.
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README
ComfyUI-TBG-Takeaways
TGB’s ComfyUI Development Takeaways
A curated collection of reusable ComfyUI nodes developed by TGB. These sidecodes encapsulate key breakthroughs in model sampling, noise scheduling, and image refinement for enhanced stable diffusion workflows.
Table of Contents
Included Nodes
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TBG_FluxKontextStabilizer (New!)
Developed specifically for the TBG ETUR (Enhanced Tiled Upscaler and Refiner), this node maintains exact positioning of reference images in final outputs. It stabilizes spatial context during tiled upscaling and refinement to ensure high-fidelity alignment and image coherence. Stay with euler beta and between 16 and 30 steps. Add to Promt: Repair and enhance this this this photo. -
ModelSamplingFluxGradual
Implements gradual flux-based sampling control for smoother transitions during model sampling - ModelSamplingFluxGradual interpolates between ModelSamplingFlux and ModelSamplingFlux Normalized. This allows for the best of both approaches. Detailed Inforamtion here: https://www.patreon.com/posts/125571636/edit -
PolyExponentialSigmaAdder Highres Fix Flux
The PolyExponential Sigma Adder node adds the ability to manipulate curve parameters, such as adjusting the curve’s rigidity, and allows for the application of a negative poly-exponential curve to the Sigmas. The PolyExponential Sigma Adder introduces a resolution-independent curve, ensuring a consistent adjustment to img2img processing across different resolutions. Sustitución for resolutions depending ModelSamplingFlux -
BasicSchedulerNormalized
A scheduler node with built-in denoise normalization to ensure stable consistent sampling results across schedulers. -
LogSigmaSamplerNode & LogSigmaStepSamplerNode These nodes offer direct access to the internal model noise curve—the curve the model expects from sigma values during diffusion. LogSigmaSamplerNode enables manipulation of this curve directly, allowing users to enhance fine details, introduce natural imperfections, or soften the final image by shifting how the model interprets noise over time. This approach gives precise control over the model's behavior—similar in effect to techniques used by Detail Deamon or Lying Sigmas. These nodes are ideal for users looking to experiment with or customize the core diffusion response for artistic or technical purposes.
Detailed Inforamtion on my Patreon:
Overview
TGB’s sidecodes provide practical solutions distilled from complex development work into simple, easy-to-integrate nodes. These tools offer enhanced control over sampling dynamics, noise management, and image refinement, making them valuable assets for artists, developers, and researchers using ComfyUI and stable diffusion workflows.
Explore this repository to discover how these nodes can streamline your image generation pipeline and help push the boundaries of creative and technical possibilities.
License
Copyright (C) 2025 Tobias Laarmann This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License.
This program comes with ABSOLUTELY NO WARRANTY;
This is free software, and you are welcome to redistribute it
under certain conditions;
Support
For updates and detailed development insights, visit TGB’s Patreon page).
Tags
ComfyUI
Stable Diffusion
AI Art
Model Sampling
Noise Scheduling
Image Refinement
Upscaling
Tiled Upscaler
Patreon
Open Source
AI Nodes
Flux Control
Happy creating!