Comments (3)
adamjstewart
commented on July 22, 2024
Why not always compute both macro and micro statistics in all trainers? I would welcome a PR that adds this.
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robmarkcole
commented on July 22, 2024
In addition to class wise or instead of? I think that would be nice to have the complete set - with the classwise as optional otherwise the list of metrics can get very long
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adamjstewart
commented on July 22, 2024
Ah sorry, yeah I meant macro + micro + classwise. As long as that doesn't noticeably slow down training time it should be fine.
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Related Issues (20)
- Overrideable resample property for IntersectionDataset
- UnionDataset of two IntersectionDataset fails HOT 2
- RandomBatchGeoSampler produces nan or nodata values HOT 6
- Check if bbox of intersection is valid HOT 4
- Git clone and pip install results in 'Successfully installed UNKNOWN-0.0.0' HOT 10
- class_weights cannot be passed via config file as a tensor is expected HOT 5
- README.md benchmark dataset code HOT 17
- AgriFieldNet missing filename glob HOT 3
- CLI script for test HOT 2
- PatternNet download link is broken HOT 2
- VHR10 plot fails for negative split HOT 1
- VHR10 uses 'masks' as data_key, not 'mask' HOT 1
- Support logging figures to multiple loggers HOT 2
- Figure plotting with Eurosat & classification trainer gives blank images HOT 3
- What values are being "clipped to the interval [0, 98]" HOT 2
- Adding custom dataset for multiclassification HOT 9
- VectorDataset has always the same time range from 0 to sys.maxsize and how to deal with multiple image and mask pairs for training. HOT 5
- BigEarthNet download links are broken HOT 3
- Normalization in Datamodules does not use correct statistics HOT 1
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