[perennate]

Unless you're using unsupervised learning or can find a good dataset, most of the cost will be in labeling the data. I'm not too familiar with background removal, there may be some self-supervised/contrastive learning approaches, but generally they don't work as well as supervised learning. Even for a week of training, the compute cost is only $200.

Edit: maybe you can get some decent results just with COCO segmentation labels: https://towardsdatascience.com/background-removal-with-deep-...

[ghoomketu]

Does it make sense to add random backgrounds to already transparent pngs and then use it to train the models?

P.S. Really useful link btw. Thank you.

P.P.S. One more question if you don't mind. After I've trained the model what kind of hardware does it require to use that model to convert a png image to transparent? I'm guessing that requirements are different when you already have a trained model?

Sorry for all the n00b questions. I'm not trying to create a background removal site btw, just trying to grasp what kind of costs it takes to create and run something like it.