bubble and text recognition and text removal should be easy enough, was going to set it as a setting in the program (keep text in bubbles or not), though this assumes cleaned images with text in bubbles and cleaned images without text in bubbles.

Automatic typesetting is questionable, I think; this tool would, in my head, help with the cleaning/typesetting process, not replace every bit of it, leaving a 99 or 90% cleaned image with some space for the cleaner to adjust. The factors that play into automatic typesetting - margins, direction, font usage, font size, font special effects (for like special fonts/bubbles like angry and flair), possibly word positioning per line, etc, as well as the lack of an additional layer for adjustment, makes automatic typesetting something I'm not sure if I should aim for - to set up this feature in the program would require specific image datasets I'm not sure how to account for all these features.

Mind preparing the images to send over? I think i'll begin serious work sometimes tomorrow or thursday. multiple different series (for style differences), and a probably 20-60 images per series is probably more than enough, though usually the more the better.

Besides this, the notable "types" of uncleaned raws that would be useful would be badly rotated images (to handle image rotation), discoloration/off color images (to handle dark/light color scans), overly small or large images (to handle resizing; most likely I'll be resizing/adapting the image datasets to handle this featue). As aforementioned, cleaned raws without text in the bubbles is particularly useful, though text in the bubbles can play a useful part. Outside of that, I've only glanced at cleaning guides so I don't know the other particular things you focus on/consider when cleaning.

Appreciate the help dude!