About the problem of training with heterogeneous data.
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Hello, author. First of all, thank you very much for open-sourcing such excellent code. OneFormer can jointly train multiple segmentation tasks, but the dataset source is the same. I think it is difficult for any data to have panoramic, instance, and semantic segmentation annotations at the same time. Is it possible to extend it to data from multiple sources, but each source only includes annotations for specific tasks? I don't know if you have considered or tried this aspect.
Hi @hhaAndroid, thanks for your interest in our work. You can also train OneFormer on single-task annotation by writing your custom dataset mappers. We also provide some sample custom dataset mappers for users' convenience.
https://github.com/SHI-Labs/OneFormer/tree/main/datasets/custom_datasets
I am closing this issue due to inactivity. Feel free to re-open.