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Add BigEarthNetv2 dataset #2371
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from torchgeo.datasets.geo import NonGeoDataset | ||
from torchgeo.datasets.utils import download_url, extract_archive, sort_sentinel2_bands | ||
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class BigEarthNetv2(NonGeoDataset): |
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I think between the existing BigEarthNet
version and version 2, there is a lot of shared code. The __init__
signature is the same as well, so I would think it's beneficial to inherit from BigEarthNet
instead of NonGeoDataset
so that a lot of the code does not have to be written twice, and instead only overwrite the relevant parts.
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Can someone point me to a summary of the changes between v1 and v2? Basically I'm curious if this is just a newer version of the same dataset (slightly more images or better labels) or a completely new iteration. We could either do:
BigEarthNet(version=1)
BigEarthNet(version=2)
in the case of the former or:
BigEarthNet()
BigEarthNetv2()
in the case of the latter.
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Yes you're right, I've basically used v1 as the template to write v2.
v2 is the same dataset with the following changes:
- Better labels
- Better spatial splits
- Fewer images - problematic images removed
- pixel-levels labels additionally available ('maps') along with multi-class image-level labels
The reBEN paper details these differences
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Gotcha. In that case I'm kind of leaning towards adding a version
parameter to the existing dataset. We could default to 2. This would require the fewest code modifications.
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dir_s2 = self.metadata_locs["s2"]["directory"] | ||
dir_maps = self.metadata_locs["maps"]["directory"] | ||
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self.metadata = pd.read_parquet(os.path.join(self.root, filename)) |
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Just noticed, that this is missing a filter based on the split for the appropriate set.
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Args: | ||
root: root directory where dataset can be found | ||
split: train/val/test split to load |
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And in v2, the val split is called "validation"
Basic BENv2 dataset added.
_verify(..)
and checksums missing