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Switch from SMP to TorchSeg #1967
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dependencies
Packaging and dependencies
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I can work on figuring out why dependabot and codecov wasn't working. I'll also try running some tests with different version of timm to see what happens. |
Seems like SMP is now maintained, we just need to start contributing PRs there instead of to TorchSeg. |
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Summary
We should consider switching from SMP to TorchSeg for our segmentation models.
Rationale
SMP is no longer maintained. TorchSeg is a fork providing important features we need:
Implementation
Should be a simple
s/segmentation_models_pytorch/torchseg/g
.However, there are a few more things I would like to see in TorchSeg before committing to the switch:
These are things I can set up myself when I have time (hopefully soon!)
Alternatives
I have not yet found a better alternative to SMP.
If SMP becomes maintained once again, we could contribute back all of the improvements in TorchSeg. But I find this unlikely, and I like the control we have over TorchSeg if we need to quickly add new features.
Additional information
@isaaccorley I'm opening this issue to make sure I don't forget to do this before the 0.6 release sometime in April.
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