lvis

• Visualization: Explore in Know Your Data north_east

• Description:

LVIS: A dataset for large vocabulary instance segmentation.

• Homepage: https://www.lvisdataset.org/

• Source code: tfds.object_detection.lvis.Lvis

• Versions:

  • 1.1.0: Added fields neg_category_ids and not_exhaustive_category_ids.

  • 1.2.0 (default): Added class names.

• Download size: 25.35 GiB

• Dataset size: 22.29 GiB

• Auto-cached (documentation): No

• Splits:

• Features:

FeaturesDict({
    'image': Image(shape=(None, None, 3), dtype=tf.uint8),
    'image/id': tf.int64,
    'neg_category_ids': Sequence(ClassLabel(shape=(), dtype=tf.int64, num_classes=1203)),
    'not_exhaustive_category_ids': Sequence(ClassLabel(shape=(), dtype=tf.int64, num_classes=1203)),
    'objects': Sequence({
        'area': tf.int64,
        'bbox': BBoxFeature(shape=(4,), dtype=tf.float32),
        'id': tf.int64,
        'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=1203),
        'segmentation': Image(shape=(None, None, 1), dtype=tf.uint8),
    }),
})

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

• Citation:

@inproceedings{gupta2019lvis,
  title={ {LVIS}: A Dataset for Large Vocabulary Instance Segmentation},
  author={Gupta, Agrim and Dollar, Piotr and Girshick, Ross},
  booktitle={Proceedings of the {IEEE} Conference on Computer Vision and Pattern Recognition},
  year={2019}
}