RobustVideoMatting VS caer

Robust Video Matting/Background Remover (Remove Background from images and videos, useful for compositing) https://github.com/PeterL1n/RobustVideoMatting (RVM - Remove backgrounds from videos) https://github.com/nadermx/backgroundremover (BackgroundRemover - works well on single images) -------VOICE GENERATION--------

Looks like runway is packaging a bunch of AI tools like stable diffusion and other opensource tools into a paid package. The matting tools it is using looks like this tool https://github.com/PeterL1n/RobustVideoMatting which can be run off your computer for free if you can figure out the geeky side of installing this stuff. I've tried it out and it sometimes works well but most of the time the results aren't as good as the examples on their github. Still a good tool to have in the toolbox though.

OR this separate application looks promising, if you can work out Google Collab (I couldn't unfortunately): https://github.com/PeterL1n/BackgroundMattingV2 https://github.com/PeterL1n/RobustVideoMatting

I have done a bit of coding and I will use pretrained models only. Looking at things like depth and segmentation. Like this as an example. I am using it on a collab now but its so cumbersome. https://github.com/PeterL1n/RobustVideoMatting

I do not know much about Machine learning, and I am not sure if I can ask question here. But if yes, I need help with either choosing best libraries to do Video Editing like Background Removal and similar. Some of the ones that I found is RVM: https://github.com/PeterL1n/RobustVideoMatting (which currently seems like the best choice)

First of all I would ask if somebody retrained Robust Video Matting model on own data? I am trying to, but with all the models I end up getting bad quality result as the ones attached to the post. So my data is some objects rotating on 360 and with white backgrounds, The task seems to be pretty simple as the model just has to remove white bgr and keep colorized object. I have masks on every 10th frame of my videos. The masks are 0 - bgr, 255 - fgr. I have tried Robust Video Matting model, MODNet, PaddleSeg and several segmentation models and every of them failed to show consistent results on that data. What should I do in the case?

I have found a github with a project like this but it is tedious to use: https://github.com/PeterL1n/RobustVideoMatting

I think it may have. If you look at line 10 of https://github.com/jasmcaus/caer/blob/master/configs.ini, you’ll see that caer has numpy and opencv-contrib-python dependencies that get referenced in its setup.py. If I recall correctly, pip on the nano doesn’t pick up the default numpy and opencv-python system installs, so when you go to install something like caer that has them as dependencies, it will install new copies except the wheel files that it grabs are incompatible. The solution I have found to work is to run something similar to the command above: “pip3 install —no-binary caer —no-binary numpy—no-binary opencv-contrib-python —no-binary typing-extensions —no-binary mypy —force-reinstall caer”. Some of those —no-binary options may not be necessary but they’ll at least ensure pip grabs the source for each of the dependencies and rebuilds it locally rather than using an imcompatible version. This command will take awhile! But you only should have to do it once.