Hugging Face's logo

Datasets:
facebook
/
SACo-VEval

Modalities:
Text
Formats:
json
Languages:
English
Size:
< 1K
Libraries:
Datasets
pandas
License:
Dataset card Data Studio Files
xet
Community
1

You need to agree to share your contact information to access this dataset

The information you provide will be collected, stored, processed and shared in accordance with the Meta Privacy Policy.

Log in or Sign Up to review the conditions and access this dataset content.

SA-Co/VEval Dataset

License each domain has its own License

  • SA-Co/VEval - SA-V: CC-BY-NC 4.0
  • SA-Co/VEval - YT-Temporal-1B: CC-BY-NC 4.0
  • SA-Co/VEval - SmartGlasses: CC-by-4.0

SA-Co/VEval is an evaluation dataset comprising of 3 domains, each domain has a val and test split.

This Hugging Face dataset repo contains the following contents:

datasets/facebook/SACo-VEval/tree/main/
├── annotation/
│   ├── saco_veval_sav_test.json
│   ├── saco_veval_sav_val.json
│   ├── saco_veval_smartglasses_test.json
│   ├── saco_veval_smartglasses_val.json
│   ├── saco_veval_yt1b_test.json
│   ├── saco_veval_yt1b_val.json
└── media/
    ├── saco_sg.tar.gz
    └── yt1b_start_end_time.json
  • annotation
    • all the GT json files
  • media
    • saco_sg.tar.gz: the preprocessed JPEGImages for SA-Co/VEval - SmartGlasses
    • yt1b_start_end_time.json: the Youtube video ids and the start and end time used in SA-Co/VEval - YT-Temporal-1B

More detail to prepare the complete SA-Co/VEval Dataset can be found in the SAM 3 Github.

Annotation Format

The format is similar to the YTVIS format.

In the annotation json, e.g. saco_veval_sav_test.json there are 5 fields:

  • info:
    • A dict containing the dataset info
    • E.g. {'version': 'v1', 'date': '2025-09-24', 'description': 'SA-Co/VEval SA-V Test'}
  • videos
    • A list of videos that are used in the current annotation json
    • It contains {id, video_name, file_names, height, width, length}
  • annotations
    • A list of positive masklets and their related info
    • It contains {id, segmentations, bboxes, areas, iscrowd, video_id, height, width, category_id, noun_phrase}
      • video_id should match to the videos - id field above
      • category_id should match to the categories - id field below
      • segmentations is a list of RLE
  • categories
    • A globally used noun phrase id map, which is true across all 3 domains.
    • It contains {id, name}
      • name is the noun phrase
  • video_np_pairs
    • A list of video-np pairs, including both positive and negative used in the current annotation json
    • It contains {id, video_id, category_id, noun_phrase, num_masklets}
      • video_id should match the videos - id above
      • category_id should match the categories - id above
      • when num_masklets > 0 it is a positive video-np pair, and the presenting masklets can be found in the annotations field
      • when num_masklets = 0 it is a negative video-np pair, meaning no masklet presenting at all
data {
    "info": info
    "videos": [video]
    "annotations": [annotation]
    "categories": [category]
    "video_np_pairs": [video_np_pair]
}
video {
    "id": int
    "video_name": str  # e.g. sav_000000
    "file_names": List[str]
    "height": int
    "width": width
    "length": length
}
annotation {
    "id": int
    "segmentations": List[RLE]
    "bboxes": List[List[int, int, int, int]]
    "areas": List[int]
    "iscrowd": int
    "video_id": str
    "height": int
    "width": int
    "category_id": int
    "noun_phrase": str
}
category {
    "id": int
    "name": str
}
video_np_pair {
    "id": int
    "video_id": str
    "category_id": int
    "noun_phrase": str
    "num_masklets" int
}

SAM 3 Github sam3/examples/saco_veval_vis_example.ipynb shows some examples of the data format and data visualization.

Downloads last month
77

Collection including facebook/SACo-VEval