Datasets:
Formats:
parquet
Size:
10K - 100K
ArXiv:
Tags:
personalization
instance_detection
instance_classification
instance_segmentation
instance_retrieval
License:
Update README.md
Browse files
README.md
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@@ -65,7 +65,10 @@ Metadata is stored in two files:
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* `class_to_idx`: Mapping of each class to an integer id
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* `class_to_sc`: Mapping of each class to a broad, single-word semantic category
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* `class_to_split`: Mapping of each class to the `val` or `test` split.
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* `pods_image_annos.json`: Maps every image ID to
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## Using PODS
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* `class_to_idx`: Mapping of each class to an integer id
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* `class_to_sc`: Mapping of each class to a broad, single-word semantic category
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* `class_to_split`: Mapping of each class to the `val` or `test` split.
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* `pods_image_annos.json`: Maps every image ID to a dictionary:
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* `class`: The class name that the image belongs to
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* `split`: One of `[train, test]` indicating if the image is in the train or test set for that class.
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* `test_split`: For images in the `test` split, denotes which distribution-shift test split the image is in: One of `[in_distribution, pose, distractors, pose_and_distractors]`
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## Using PODS
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