Using an inpainting model for standard generation
I’m interested in “standard” text-conditioned generation and inpainting (and/or outpainting). Is it possible to do standard generation with a model fine-tuned for inpainting? I kind of imagine that it is, since inpainting is still generation, but it does have a bit of contextual “help” in doing its job… so maybe not?If the answer is “no”, would it help to maybe randomize the (boolean)mask_full_imageargument to therandom_mask()function, when fine-tuning withtrain_dreambooth_inpaint.py?Presumably, “inpainting” with the whole image masked would be equivalent to standard generation…
2023-01-19T03:11:31Z
Just to note, I don’t actually have classes for my data, so Dreambooth might not make much sense. Is there much else to inpainting training than integrating the random masks? I mean, could I hack that into the normaltrain_text_to_image.pyscript and have basically the same effect?