This repository provides a custom node implementation of the TCD Sampler for ComfyUI, enhancing image generation capabilities by leveraging advanced distillation techniques from pre-trained diffusion models. TCD offers improved image quality and detail control compared to traditional methods like LCM, making it a valuable addition for users seeking high-quality outputs with fewer processing steps.
- TCD generates clearer and more detailed images than LCM, even with the same number of denoising steps.
- Users can manipulate the richness of details in generated images through adjustable parameters, allowing for tailored outputs.
- The sampler performs exceptionally well with higher step counts, producing superior results compared to LCM.
Context
The ComfyUI-TCD tool is an extension designed to integrate the TCD Sampler into the ComfyUI framework. Its primary purpose is to enhance image generation quality by utilizing a novel distillation method inspired by Consistency Models, allowing users to create detailed images efficiently.
Key Features & Benefits
The TCD Sampler includes several practical features that significantly enhance image generation. First, it allows for better detail retention during the denoising process compared to LCM, which is crucial for achieving high-quality visuals. Additionally, the ability to adjust parameters like the level of noise adds flexibility, enabling users to create images with varying degrees of detail based on their specific needs.
Advanced Functionalities
TCD introduces advanced functionalities such as the control of stochasticity through the eta parameter, which affects the richness of details in the output. By fine-tuning this parameter, users can switch between deterministic and stochastic sampling, optimizing the image generation process according to the desired level of detail. This capability is particularly useful when working with different LoRAs (Low-Rank Adaptations) for diverse artistic styles.
Practical Benefits
Incorporating the TCD Sampler into ComfyUI enhances workflow efficiency by reducing the number of steps required to achieve high-quality images. Users can expect clearer and more detailed results, improving overall image quality while saving time and computational resources. This tool streamlines the creative process, allowing artists and developers to focus on their work rather than on technical limitations.
Credits/Acknowledgments
This extension is developed by Jett Hu and is based on the original TCD paper and implementations by other contributors. The repository is licensed under open-source terms, encouraging collaboration and further development within the community.