| --- |
| license: mit |
| task_categories: |
| - video-text-to-text |
| - robotics |
| language: |
| - en |
| tags: |
| - vision-language-navigation |
| - VLN |
| - navigation |
| - embodied-ai |
| - envdrop |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # VLNCE-EnvDrop |
|
|
| Synthetic **Vision-Language Navigation (VLN)** data-augmentation set, derived from the |
| EnvDrop augmentation used in VLN-CE / NaVILA-style training. Each of the **146,304** |
| samples pairs a short first-person navigation video with the natural-language |
| instruction the agent was following and the discrete action sequence it executed. |
|
|
| This dataset provides the visual + motion supervision for training a GRU-augmented |
| Qwen3-VL navigation model: the language conditions the backbone, while the per-step |
| `motion` sequence feeds a GRU whose output is projected into the LLM embedding space. |
|
|
| ## Contents |
|
|
| | File | Size | What it is | |
| |------|------|------------| |
| | `envdrop_videos_00.tar` … `envdrop_videos_14.tar` | ~270 GB | The raw first-person navigation videos, one `<video_id>.mp4` per sample, sharded into 15 tarballs. | |
| | `envdrop_motion.json` | 392 MB | **Primary training annotation.** One record per sample: instruction, decoded frame paths, and the per-step action (`motion`) sequence. | |
| | `annotations.json` | 22.5 MB | Lightweight `video_id → instruction` index (powers the dataset preview). A subset of the info in `envdrop_motion.json`. | |
|
|
| ## Record schema — `envdrop_motion.json` |
| |
| ```json |
| { |
| "video_id": "34300", |
| "q": "Walk forward and stop at the end of the aisle.", |
| "frames": ["34300/frame_0.jpg", "34300/frame_1.jpg", "..."], |
| "motion": [3, 3, 1, 1, 3, 1, 1, 2, 2, 1, "..."] |
| } |
| ``` |
| |
| - **`video_id`** — key into the tarballs (`<video_id>.mp4`). |
| - **`q`** — the natural-language navigation instruction. |
| - **`frames`** — decoded frame paths for the clip (frames are extracted from the |
| corresponding `.mp4` at load time; they are **not** stored separately). |
| - **`motion`** — the discrete action taken at each step (small action vocabulary, |
| e.g. forward / turn-left / turn-right / stop). This is the GRU input. |
| |
| ## Layout |
| |
| ``` |
| VLNCE-EnvDrop/ |
| ├── envdrop_videos_00.tar # <video_id>.mp4 clips |
| │ ... # (15 shards, ~270 GB total) |
| ├── envdrop_videos_14.tar |
| ├── envdrop_motion.json # primary training annotation (146,304 records) |
| └── annotations.json # video_id -> instruction index / preview |
| ``` |
| |
| ## Usage |
| |
| ```python |
| from huggingface_hub import snapshot_download |
|
|
| # annotations only (small) |
| snapshot_download("Rithvik762/VLNCE-EnvDrop", repo_type="dataset", |
| allow_patterns=["*.json"]) |
| |
| # full dataset incl. video tars (~270 GB) |
| snapshot_download("Rithvik762/VLNCE-EnvDrop", repo_type="dataset") |
| ``` |
| |
| After download, extract the shards (e.g. `for f in envdrop_videos_*.tar; do tar xf "$f"; done`). |
| Videos and `envdrop_motion.json` must be kept together — the JSON references |
| `video_id`s that live inside the tarballs. |
| |
| ## License |
| |
| Released under the MIT license. |
| |
