GiusTex-ComfyUI-DiffusersImageOutpaint/README.md

ComfyUI nodes for outpainting images with diffusers, based on diffusers-image-outpaint by fffiloni.

Installation

• Download this extension or git clone it in comfyui/custom_nodes, then (if comfyui-manager didn't already install the requirements or you have missing modules), from comfyui virtual env write cd your/path/to/this/extension and pip install -r requirements.txt.
• Download models in comfyui/models/unet, vae and controlnet folder, following the grid below (the links are the suggested models, and you can change the model in models/unet, but you need the specified vae and controlnet since the extension is hardcoded to use them. You can always change the code to use different models):

  ComfyUI/models/Unet folder	ComfyUI/models/Vae folder	ComfyUI/models/Controlnet folder
  Diffuser Model folder (you can change this model)	Diffuser Vae folder (you need this model)	Diffuser Controlnet folder (you need this model)
  model_index-json	config.json, sdxl_vae.safetensors	config_promax.json, diffusion_pytorch_model_promax.safetensors
  Unet folder
  config.json, diffusion_pytorch_model.fp16.safetensors
  Scheduler folder
  scheduler_config.json
  Text encoder folder
  config.json, model.fp16.safetensors
  Text encoder 2 folder
  config.json, model.fp16.safetensors
  Tokenizer folder
  merges.txt, special_tokens_map.json, tokenizer_config.json, vocab.json
  Tokenizer 2 folder
  merges.txt, special_tokens_map.json, tokenizer_config.json, vocab.json

Overview

The extension gives 3 nodes:

• Load Diffusion Outpaint Models: a simple node to load diffusion models. You can download them from Huggingface (the extension doesn't download them automatically);

• Paid Image for Diffusers Outpaint: this node creates an empty image of the desired size, fits the original image in the new one based on the chosen alignment, then mask the rest;

• Diffusers Image Outpaint: This is the main node, that outpaints the image. Currently the generation process is based on fffiloni's one, so you can't reproduce a specific a specific outpaint, and the seed option you see is only used to change the UI and generate a new image. Anyway, you can specify the amount of steps to generate the image and the prompt to specify what to add to the image.

• You can also pass image and mask to vae encode (for inpainting) node, then pass the latent to a sampler, but controlnets and ip-adapters are harder to use compared to diffusers outpaint.

Credits

diffusers-image-outpaint by fffiloni