GiusTex-ComfyUI-DiffusersImageOutpaint/README.md at 9801c8c5d72b941c33b276ff1f3080c42e2f2428

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2024-11-17 12:01:43 +01:00

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

22/10/2024:
- Unet and Controlnet Models Loader using ComfYUI nodes canceled, since I can't find a way to load them properly; more info at the end.
- Guide to change model used.
20/10/2024: No more need to download tokenizers nor text encoders! Now comfyui clip loader works, and you can use your clip models. You can also use the Checkpoint Loader Simple node, to skip the clip selection part.
10/2024: You don't need any more the diffusers vae, and can use the extension in low vram mode using sequential_cpu_offload (also thanks to zmwv823) that pushes the vram usage from 8,3 gb down to 6 gb.

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/diffusion_models:
- model_name:
  - unet:
    - diffusion_pytorch_model.fp16.safetensors (example)
    - config.json (example)
  - scheduler:
    - scheduler_config.json (example)
  - model_index.json (example)
- controlnet_name:
  - config_promax.json (example), diffusion_pytorch_model_promax.safetensors (example)
(Dual) Clip Loader node: if you use the Clip Loader instead of Checkpoint Loader Simple, and want to use RealVisXL_V5.0_Lightning, it works with clip_I and model.fp16 (from sdxl-base), and sdxl type; you can use this workflow.

Minimum VRAM: 6 gb with 1280x720 image, rtx 3060, RealVisXL_V5.0_Lightning, sdxl-vae-fp16-fix, controlnet-union-sdxl-promax using sequential_cpu_offload, otherwise 8,3 gb;
As seen in this issue, images with square corners are required.

The extension gives 4 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;
Encode Diffusers Outpaint Prompt: self explanatory. Works as clip text encode (prompt), and specifies what to add to the image;
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. You can specify the amount of steps to generate 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.

Main model: On huggingface, choose a model from text2image models, then create a new folder named after it in comfyui/models/diffusion_models, then download in it the subfolders unet (if not available use transformer) and scheduler.
- Hint: sometimes in the unet or transformer folder there are more model files and not all are required. If you have model.fp16 and model, I suggest you to use the fp16 variant; if you have model-001-of-002, model-002-of-002, model, choose model (instead of the fragmented version).
Controlnet model: download config.json and the safetensors model.

I can load them but then they don't work in the inference code, since comfyui load diffusers models in a different format (reddit post).

diffusers-image-outpaint by fffiloni