LaMa and MAT's result is different with original repo

[jarheadjoe]

For example, I want to remove something from original image: Original LaMa output: Your node output: The painted area is blurry and border is clear. The same with MAT.

[Acly]

What original repo are you referring to?

The reason it's blury is that it runs at low resolution (256 for LaMA, 512 for MAT). You can technically run it at higher resolution, but it results in those grainy patterns, I don't find it very useful.

To inpaint this image I'd downscale it, use Lama/MAT inpaint at low resolution, do a 1st diffusion pass, upscale and crop, then run a 2nd diffusion pass at original resolution but only the inpaint area. So Lama/MAT is meant as a first step in a pipeline, not a final solution.

[jarheadjoe]

original lama repo: https://github.com/advimman/lama.Use big-lama ckpt. Original LaMa works good some way. For example, as depth controlnet's input. The LaMa results in your repo are bad and almost like blurring to a certain extent. And for inpaint models, the mask area is not visible. So Lama feels unnecessary as a first step https://github.com/comfyanonymous/ComfyUI/blob/14764aa2e2e2b282c4a4dffbfab4c01d3e46e8a7/nodes.py#L346

[Acly]

I don't use VAEEncodeForInpaint and I downscale/crop images which makes the low resolution less of an issue. Lama still helps at 1.0 denoise as a base for conservative inpainting (remove objects and such).

For a stand-alone solution that you can slap on an image like in your example, the node would have to be more complex. I'm not particularly motivated to go for that because I don't think results are good enough in general.