Add WorldCover segmentation task #274
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Farbum
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Feb 9, 2026
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LGTM.
Does it make sense to add a readme.md in the worldcover folder to refer to the tolbi readme.md for data spec and collection information?
| average: "micro" | ||
| other_metrics: | ||
| cacao_precision: | ||
| class_path: rslearn.train.tasks.segmentation.SegmentationMetric |
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Would it make sense to set report_metric_per_class to True in the SegmentationTask init parameters to have metrics reported per class?
Never mind, we just talked. We'll need to add a naming dictionary to the logic.
favyen2
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Feb 9, 2026
| @@ -0,0 +1,214 @@ | |||
| """Create windows for the Tolbi project.""" | |||
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Fix docstring (Tolbi -> WorldCover) and add some information either in docstring or README about where the WorldCover data is, how much data there is, etc.
favyen2
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Feb 10, 2026
| COPY requirements-extra.txt /opt/rslearn_projects/requirements-extra.txt | ||
| # Using cache mount here avoids needing to re-download dependencies for later builds if the version didn't change. | ||
| RUN --mount=type=cache,target=/root/.cache/uv uv pip install --system /opt/rslearn[extra] /opt/olmoearth_pretrain -r /opt/rslearn_projects/requirements.txt -r /opt/rslearn_projects/requirements-extra.txt | ||
| RUN uv pip install --system /opt/rslearn[extra] /opt/olmoearth_pretrain -r /opt/rslearn_projects/requirements.txt -r /opt/rslearn_projects/requirements-extra.txt |
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What is the reason to drop this? I thought it makes the build faster.
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This PR include two tasks: (1) Tolbi cash crop classification - though given the lack of negative samples, the inference result is not good, (2) WorldCover land cover and land use classification - this is using the labels here: https://doi.org/10.5281/zenodo.14871659, and tried different modality combination (i haven't ran inference yet, will do that later).