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| language: |
| - en |
| pretty_name: SA-FARI |
| configs: |
| - config_name: SA-FARI |
| data_files: |
| - split: train |
| path: annotation/sa_fari_train.json |
| - split: test |
| path: annotation/sa_fari_test.json |
| license: other |
| --- |
| # SA-FARI Dataset |
| **License** CC-BY-NC 4.0 |
|
|
| **SA-FARI** is a wildlife camera dataset collected through a collaboration between Meta and [CXL](https://www.conservationxlabs.com/). |
|
|
| All videos and pre-processed JPEGImages can be found in [cxl-public-camera-trap](https://console.cloud.google.com/storage/browser/cxl-public-camera-trap), which contains the following contents: |
| ``` |
| sa_fari/ |
| ├── sa_fari_test_tars/ |
| │ ├── JPEGImages_6fps/ |
| │ ├── videos/ |
| ├── sa_fari_test/ |
| │ ├── JPEGImages_6fps/ |
| │ ├── videos/ |
| ├── sa_fari_train_tars/ |
| │ ├── JPEGImages_6fps/ |
| │ ├── videos/ |
| └── sa_fari_train/ |
| ├── JPEGImages_6fps/ |
| └── videos/ |
| ``` |
| * `videos`: The original full fps videos. |
| * `JPEGImages_6fps`: For annotation, the videos have been downsampled to 6fps. This folder contains the downsampled frames compatible with the annotation json files below. |
|
|
| This Hugging Face dataset repo contains the annotations: |
| ``` |
| datasets/facebook/SA-FARI/tree/main/ |
| └── annotation/ |
| ├── sa_fari_test.json |
| ├── sa_fari_test_ext.json |
| ├── sa_fari_train.json |
| └── sa_fari_train_ext.json |
| ``` |
| * `sa_fari_test.json` and `sa_fari_train.json` |
| * Follow the same format as [SA-Co/VEval](https://huggingface.co/datasets/facebook/SACo-VEval/) |
| * `sa_fari_test_ext.json` and `sa_fari_train_ext.json` |
| * In additional to the [SA-Co/VEval] format, we added additional metadata to the following fields: |
| * `videos`: |
| * `video_num_frames`, `video_fps`, `video_creation_datetime` and `location_id` have been added as additional metadata to the `videos` field. |
| * `categories`: |
| * `Kingdom`, `Phylum`, `Class`, `Order`, `Family`, `Genus` and `Species` have been added when applicable as additional metadata to the `categories` field. |
|
|
| All the SA-FARI annotation files are compatible to use the visualization notebook and offline evaluator developed in [SAM 3 Github](https://github.com/facebookresearch/sam3/tree/main/scripts/eval/veval). |
|
|
| ## Annotation Format |
| A format breakdown for `sa_fari_test.json` and `sa_fari_train.json`. The format is similar to the [YTVIS](https://youtube-vos.org/dataset/vis/) format. |
|
|
| In the annotation json, e.g. `sa_fari_test.json` there are 5 fields: |
| * info: |
| * A dict containing the dataset info |
| * E.g. {'version': 'v1', 'date': '2025-09-24', 'description': 'SA-FARI 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](https://github.com/cocodataset/cocoapi/blob/master/PythonAPI/pycocotools/mask.py) |
| * 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 |
| } |
| ``` |
