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

Update:

• 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.
• If your text_encoder and text_encoder_2 names contain .fp16. or other things before safetensors, you need to remove it (see the table below).

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 the comfyui/models/diffusion_models folder, following the grid below (you can use the links to download the suggested models; you can also change the main model, 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): | main model | controlnet model | | :-----: | :-----: | | Diffuser Model folder (you can change this model) | Diffuser Controlnet folder (you need this model) | | model_index-json | 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~ -> model.safetensors | | | Text encoder 2 folder | | | config.json, ~model.fp16.safetensors~ -> model.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

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.

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.

Credits

diffusers-image-outpaint by fffiloni