| --- |
| license: apache-2.0 |
| task_categories: |
| - video-text-to-text |
| - visual-question-answering |
| - image-text-to-text |
| language: |
| - en |
| tags: |
| - llava |
| - multimodal |
| - video |
| - spatial-reasoning |
| size_categories: |
| - 10M<n<100M |
| configs: |
| - config_name: viewer_caption_30s |
| data_files: |
| - split: preview |
| path: viewer/caption_30s.parquet |
| - config_name: viewer_caption_60s |
| data_files: |
| - split: preview |
| path: viewer/caption_60s.parquet |
| - config_name: viewer_spatial |
| data_files: |
| - split: preview |
| path: viewer/spatial.parquet |
| --- |
| |
| # LLaVA-OneVision-2-Data |
|
|
| Training data for the LLaVA-OneVision-2 multimodal model family, covering large-scale video and spatial reasoning corpora used in mid-training. |
|
|
| ## Dataset Composition |
|
|
| | Subset | Format | Description | |
| |---|---|---| |
| | `mid_training_video/60s_rest/` | WebDataset (`.tar`) | 10,809 shards of ~60s video clips | |
| | `mid_training_video/caption_v0/split_30s.jsonl` | JSONL | Captions for 30-second video clips | |
| | `mid_training_video/caption_v0/split_60s.jsonl` | JSONL | Captions for 60-second video clips | |
| | `spatial/` | WebDataset (`.tar`) | 84 shards of spatial reasoning data (refcoco, visual genome, pointing, 3D, etc.) | |
|
|
| ## Preview Configs |
|
|
| The three `viewer_*` configs above expose small Parquet samples so the Hugging Face Dataset Viewer can render the data directly in the browser: |
|
|
| - **`viewer_caption_30s`** — 5 caption samples from 30-second clips |
| - **`viewer_caption_60s`** — 5 caption samples from 60-second clips |
| - **`viewer_spatial`** — 10 spatial-reasoning samples with embedded thumbnail images, mixed across tasks (refcoco, visual genome, pointing, ca1m, osd, crosspoint, erqa, roborefer) |
| |
| These previews are intended for **schema inspection only**. For training, use the full `mid_training_video/` and `spatial/` shards. |
| |
| ## Loading Examples |
| |
| ### Stream the full spatial WebDataset |
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset( |
| "mvp-lab/LLaVA-OneVision-2-Data", |
| data_files="spatial/train_*.tar", |
| split="train", |
| streaming=True, |
| ) |
| for sample in ds: |
| print(sample) |
| break |
| ``` |
| |
| ### Load a viewer preview |
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("mvp-lab/LLaVA-OneVision-2-Data", "viewer_spatial", split="preview") |
| print(ds[0]) |
| ``` |
| |
| ## Schema |
| |
| ### Caption (`viewer_caption_30s`, `viewer_caption_60s`) |
| - `images_source: List[str]` — relative paths to source video files |
| - `messages: List[{role, content}]` — chat-format caption prompt and assistant response |
| - `preview: str` — flattened text preview |
| |
| ### Spatial (`viewer_spatial`) |
| - `id: str` — sample id |
| - `task: str` — source task name (e.g. `refcoco`, `visual_genome`, `pointing`) |
| - `image: Image` — first referenced image, embedded as JPEG bytes (downscaled to max edge 1024) |
| - `image_paths: List[str]` — original relative image paths in the full dataset |
| - `messages: List[{role, content}]` — chat-format Q/A |
| - `preview: str` — flattened text preview |
| |
| ## License |
| |
| Apache 2.0 |
| |
