lvis

LVIS: Kumpulan data untuk segmentasi instance kosakata besar.

Membelah Contoh
'minival' 4.809
'test' 19.822
'train' 100.170
'validation' 19.809
  • Struktur fitur :
FeaturesDict({
    'image': Image(shape=(None, None, 3), dtype=uint8),
    'image/id': int64,
    'neg_category_ids': Sequence(ClassLabel(shape=(), dtype=int64, num_classes=1203)),
    'not_exhaustive_category_ids': Sequence(ClassLabel(shape=(), dtype=int64, num_classes=1203)),
    'objects': Sequence({
        'area': int64,
        'bbox': BBoxFeature(shape=(4,), dtype=float32),
        'id': int64,
        'label': ClassLabel(shape=(), dtype=int64, num_classes=1203),
        'segmentation': Image(shape=(None, None, 1), dtype=uint8),
    }),
})
  • Dokumentasi fitur :
Fitur Kelas Membentuk Dtype Keterangan
fiturDict
gambar Gambar (Tidak ada, Tidak ada, 3) uint8
gambar/id Tensor int64
neg_category_ids Urutan(Label Kelas) (Tidak ada,) int64
not_exhaustive_category_ids Urutan(Label Kelas) (Tidak ada,) int64
objek Urutan
benda/daerah Tensor int64
benda/bbox Fitur BBox (4,) float32
benda/id Tensor int64
benda/label LabelKelas int64
objek/segmentasi Gambar (Tidak ada, Tidak ada, 1) uint8

Visualisasi

@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}
}