Datasets:
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README.md
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@@ -34,7 +34,7 @@ The LADI-v2 dataset is a set of aerial disaster images captured and labeled by t
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The v2 dataset consists of approximately 10k images, split into a train set of 8k images, a validation set of 1k images, and a test test of 1k images. The train and validation sets are drawn from the same distribution (CAP images from federally-declared disasters 2015-2022), whereas the test set is drawn from events in 2023, which has a different distribution of event types and locations. This is done to simulate the distribution shift as new events occur each year.
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### Dataset v2a
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The `v2a` dataset presents the same images with a subset of the labels, where the damage categories for buildings have been compressed into two classes of `buildings_affected_or_greater` and `buildings_minor_or_greater`. We find that this task is easier and of similar practical value for triage purposes.
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- bridges_any
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- buildings_any
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The v2 dataset consists of approximately 10k images, split into a train set of 8k images, a validation set of 1k images, and a test test of 1k images. The train and validation sets are drawn from the same distribution (CAP images from federally-declared disasters 2015-2022), whereas the test set is drawn from events in 2023, which has a different distribution of event types and locations. This is done to simulate the distribution shift as new events occur each year.
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### Dataset v2a
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The `v2a` dataset presents the same images with a subset of the labels, where the damage categories for buildings have been compressed into two classes of `buildings_affected_or_greater` and `buildings_minor_or_greater`. We find that this task is easier and of similar practical value for triage purposes. The `bridges_damage` label has also been removed due to the low number of positive examples in the dataset.
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- bridges_any
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- buildings_any
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