At the heart of this repository is the "ClownsharKSampler", which was specifically designed to support both rectified flow and probability flow models. It features 28 different selectible samplers all available in both ODE or SDE modes with 20 noise types, 6 noise scaling modes, and options for implicit Runge-Kutta sampling refinement steps. Several new samplers are implemented, including RES_3S, RES_3M, and RES_2M. Additionally, img2img capabilities include both latent image guidance or unsampling/resampling (via rectified noise inversion, a form of latent image guidance).
A particular emphasis of this project has been to facilitate modulating parameters vs. time, which can facilitate large gains in image quality from the sampling process. To this end, a wide variety of sigma, latent, and noise manipulation nodes are included.
Much of this work remains experimental and is subject to further changes.
TXT2IMG Workflow:
TXT2IMG Workflow (Latent Image Guides):
Input image: https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/txt2img%20guided%20SD35M%20input.png
TXT2IMG Workflow (Dual Guides with Masking):
Input images and mask: https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/txt2img%20dual%20guides%20with%20mask%20SD35M%20input1.png https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/txt2img%20dual%20guides%20with%20mask%20SD35M%20input2.png https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/txt2img%20dual%20guides%20with%20mask%20SD35M%20mask.png
IMG2IMG Workflow (Unsampling):
Input image: https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/img2img%20unsampling%20SD35L%20input.png
IMG2IMG Workflow (Unsampling with SDXL):
Input image: https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/img2img%20unsampling%20SDXL%20input.png
IMG2IMG Workflow (Unsampling with latent image guide):
IMG2IMG Workflow (Unsampling with dual latent image guides and masking):
Input images and mask: https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/img2img%20dual%20guided%20masked%20unsampling%20SD35M%20input1.png https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/img2img%20dual%20guided%20masked%20unsampling%20SD35M%20input2.png https://github.com/ClownsharkBatwing/RES4LYF/blob/main/workflows/img2img%20dual%20guided%20masked%20unsampling%20SD35M%20mask.png
INSTALLATION:
If you are using a venv, you will need to first run from within your ComfyUI folder (that contains your "venv" folder):
Linux:
source venv/bin/activate
Windows:
venv\Scripts\activate
Then, "cd" into your "custom_nodes" folder and run the following commands:
git clone https://github.com/ClownsharkBatwing/RES4LYF/
cd RES4LYF
If you are using a venv, run these commands:
pip install -r requirements.txt
Alternatively, if you are using the portable version of ComfyUI you will need to replace "pip" with the path to your embedded pip executable. For example, on Windows:
X:\path\to\your\comfy_portable_folder\python_embedded\Scripts\pip.exe install -r requirements.txt