Code release for "Cut and Learn for Unsupervised Object Detection and Instance Segmentation" and "VideoCutLER: Surprisingly Simple Unsupervised Video Instance Segmentation"
Thanks for sharing your model.
I'm going to train my custom dataset, and make psuedo-masks with MaskCut.
Could I know the meaning of each argument that goes into 'maskcut.py'?
Thanks for sharing your model. I'm going to train my custom dataset, and make psuedo-masks with MaskCut. Could I know the meaning of each argument that goes into 'maskcut.py'?
01. what is '--vit-arch' ? Are there any options other than 'base'?
02. Is '--patch-size' the correct number of segments for the input-image?
03. what is '--tau' ?
04. what is '--fixed_size' ?
05. '--N' is the number of objects that must be masked in that image, right? Is it a Maximum number??
06. Is 'num-folder-per-job' the number of folders that make up the input-data?
07. what is '--job-index' ?
If you could answer this questions, it would be really helpful to use the CutLer :)