| --- |
| license: other |
| license_name: mixed-upstream-licenses |
| license_link: https://huggingface.co/datasets/royguw/grounding-data#licensing-and-attribution |
| pretty_name: grounding_data - annotations and images |
| task_categories: |
| - image-segmentation |
| - object-detection |
| - mask-generation |
| - image-to-text |
| tags: |
| - grounding |
| - referring-expression-segmentation |
| - video-object-segmentation |
| - panoptic-segmentation |
| - grounded-captioning |
| size_categories: |
| - 1M<n<10M |
| --- |
| |
| # grounding_data |
| |
| The annotation tree behind a grounding/segmentation training stack, plus the images and |
| video frames that live alongside it. Unlike the companion |
| [`royguw/mm-olmo-images`](https://huggingface.co/datasets/royguw/mm-olmo-images) — which is |
| pixels only — **this repo carries the annotations**: the parquet caches, JSON label files |
| and vocabularies under each dataset's `cache/` directory, which is where masks, boxes, |
| referring expressions, captions and category vocabularies actually live. |
| |
| 9,331,994 files / 1.20 TiB, packed as 255 tar shards across 34 groups. |
| |
| ## Layout |
| |
| ``` |
| shards/<group>/<group>-00000.tar # ~5 GiB each; members are paths relative to the grounding_data root |
| index/<group>.parquet # path -> shard, size (for fetching selectively) |
| ``` |
| |
| Tar shards rather than loose files because the Hub caps entries at 10k per folder and asks |
| for under 100k files per repo; 9.3M loose files breaks both by two orders of magnitude. |
| The payload is a file tree, not tabular rows, so the dataset viewer does not apply. |
| |
| ## Groups |
| |
| Video groups are named `video_data__<dataset>`, matching `video_data/<dataset>/` in the tree. |
| |
| | Group | Shards | Size | What | |
| |---|---|---|---| |
| | `video_data__ViCaS` | 78 | 388.2 GiB | ViCaS grounded video captions + frames | |
| | `video_data__SA-FARI` | 37 | 242.2 GiB | SA-FARI wildlife video, frames + masklets | |
| | `Adobe_EntitySeg` | 38 | 193.9 GiB | EntitySeg images + annotations | |
| | `coco` | 25 | 143.2 GiB | COCO 2014/2017 images, annotations, caches | |
| | `video_data__BOSTVG` | 11 | 55.0 GiB | BOSTVG / OmniSTVG + SAM3 masks | |
| | `GoldG` | 12 | 53.0 GiB | GoldG (Flickr30k entities + GQA) | |
| | `rf100` | 9 | 43.4 GiB | RF100-VL | |
| | `coconut` | 10 | 41.7 GiB | COCONut panoptic PNGs + caches | |
| | `video_data__VIPOSeg` | 4 | 17.7 GiB | VIPOSeg frames + panomasks | |
| | `SA-1B` | 4 | 17.1 GiB | SA-1B annotation caches (not the images) | |
| | `pixno_points` | 3 | 9.9 GiB | PixMo pointing caches | |
| | `refclef` | 2 | 5.6 GiB | RefCLEF / saiapr_tc-12 | |
| | 22 more | 1 each | ~14 GiB | reasonseg, lvis, manual_annotation, refcoco/+/g, grefcoco, panoptic-narrative-grounding, PhraseCutDataset, pixmo, VidSTG, and the small video caches | |
| |
| ## Reconstructing the tree |
| |
| ```bash |
| hf download royguw/grounding-data --repo-type dataset --local-dir ./dl |
| GD=/your/path/to/grounding_data |
| for t in ./dl/shards/*/*.tar; do tar -xf "$t" -C "$GD"; done |
| ``` |
| |
| To pull one dataset only, read its index and fetch just the shards it names: |
| |
| ```python |
| import pyarrow.parquet as pq |
| from huggingface_hub import hf_hub_download |
|
|
| idx = pq.read_table(hf_hub_download("royguw/grounding-data", "index/coco.parquet", |
| repo_type="dataset")).to_pydict() |
| for shard in dict.fromkeys(idx["shard"]): |
| hf_hub_download("royguw/grounding-data", shard, repo_type="dataset") |
| ``` |
| |
| The index is also how you find a single file without downloading everything: look up its |
| path, and it tells you the one shard to fetch. |
| |
| ### A note on paths |
| |
| The annotation parquets store **absolute** source paths in columns such as `image_path`, |
| `png_path` and `frames_dir`. After extracting you must rewrite those prefixes to wherever |
| you put the data. Two prefixes appear: |
| |
| - paths under the grounding_data root -> `$GD` |
| - paths under `mm-olmo/` -> wherever you extracted |
| [`royguw/mm-olmo-images`](https://huggingface.co/datasets/royguw/mm-olmo-images) |
| |
| Video frame lists are stored as extension-less stems in `frame_basenames_json`, resolved |
| against the directory listing; where that column is absent, frames are `f"{i:05d}"` for |
| `i in range(num_frames)`. |
| |
| ## Licensing and attribution |
| |
| This is a **redistribution mirror of third-party datasets** assembled for reproducibility. |
| It is not a new dataset, and no new license is claimed over the underlying images, video |
| frames or upstream annotations. |
| |
| The groups carry different upstream licenses — several are research or non-commercial only |
| (EntitySeg, for one, is Adobe non-commercial), and some require accepting upstream terms |
| before use. **Check the license of any group you intend to use and comply with it.** If you |
| are an author or rights-holder of an upstream dataset here and want a subset removed, open |
| a discussion on this repo and it will be taken down. |
| |
