| --- |
| license: mit |
| tags: |
| - robotics |
| - simulation |
| - domain-randomization |
| - textures |
| --- |
| |
| # CLab scene textures: RoboTwin seen library |
|
|
| This repository hosts a byte-preserving mirror of **10,000 seen textures** from |
| the local RoboTwin `assets/background_texture/seen` library, for reproducible |
| background and tabletop appearance randomization in robotic simulation. |
| The images were not created by CLab. Original PNG filenames and bytes are |
| preserved; there is no resizing, cropping, recompression of image pixels, or |
| content-based filtering. All source images are 768 x 768 RGB PNGs. |
|
|
| ## Contents |
|
|
| - `seen.zip`: one ZIP64 archive containing all 10,000 original seen PNGs. |
| - `LICENSE`: the upstream MIT copyright and license notice. |
| - `README.md`: this dataset card. |
|
|
| The original PNGs total **10,010,671,214 bytes** (about 10.01 GB / 9.32 GiB). |
| The archive also contains `seen/LICENSE` and `seen/selection.json`, for exactly |
| 10,002 members. The metadata lists all filenames, the 10,000-image source pool, |
| count, seed and packaging method. Its seed is retained for the generic packaging |
| utility; because count equals pool size, **all seen images are included**, not a |
| random subset. Members are ordered lexicographically and compressed with ZIP |
| DEFLATE level 6; source PNG bytes are unchanged. Every image was read back from |
| the completed local archive and checked byte-for-byte against its source before |
| upload. |
|
|
| The separate 1,000-image `unseen` directory is **not included**. The upstream split |
| name is preserved; it is not evidence that these images were independently |
| deduplicated or that train/test content independence was established. |
|
|
| ## Source and attribution |
|
|
| - Upstream project: [RoboTwin](https://github.com/RoboTwin-Platform/RoboTwin). |
| - Original asset distribution: `background_texture.zip`, named by RoboTwin's |
| `assets/_download.py`, from |
| [TianxingChen/RoboTwin2.0](https://huggingface.co/datasets/TianxingChen/RoboTwin2.0). |
| - The [upstream dataset card](https://huggingface.co/datasets/TianxingChen/RoboTwin2.0/blob/main/README.md) |
| declares MIT. This mirror retains the repository's copyright notice in |
| [LICENSE](LICENSE) and inside the archive. It does not transfer image authorship |
| to CLab or claim that CLab collected new images. |
| - Usage context: [RoboTwin domain randomization](https://robotwin-platform.github.io/doc/usage/domain-randomization.html). |
|
|
| ## Download and extract |
|
|
| Use a new directory; do not merge into or overwrite another texture library. |
| The following requires curl and Python 3, but no Hugging Face token for this |
| public dataset: |
|
|
| ```bash |
| mkdir clab-textures-download |
| cd clab-textures-download |
| curl --fail --location --retry 3 --continue-at - \ |
| --output seen.zip \ |
| https://huggingface.co/datasets/emopointer/clab-textures/resolve/main/seen.zip |
| python -m zipfile -t seen.zip |
| python -m zipfile -e seen.zip . |
| ``` |
|
|
| Extraction produces `seen/*.png`, `seen/LICENSE` and `seen/selection.json`. |
| Allow space for both the roughly 10 GB archive and roughly 10 GB extracted |
| library. If a download is interrupted, rerun only the curl command in the same |
| download directory to resume, then repeat the archive integrity check. An |
| interrupted extraction is incomplete; keep it separate and extract into a new |
| directory rather than silently mixing files. |
|
|
| For CLab, point `--texture-dir` or `CLAB_TEXTURE_DIR` to the directory containing |
| `seen`, not to `seen` itself. Select `--texture-split seen`. Runtime code reads |
| the library and does not download, extract or modify its contents. Runtime |
| resizing to 512 x 512 is separate from the original assets stored here. |
|
|
| ## Intended use and limitations |
|
|
| This is a texture asset library, not an action-demonstration dataset. It contains |
| no robot trajectories, actions, checkpoints, camera calibration, labels or |
| evaluation results. Use it for scene appearance variation; the mirror alone is |
| not evidence of successful sim-to-real transfer or learned-policy robustness. |
| No unseen benchmark, content-quality filtering, deduplication or license audit |
| beyond preserving the upstream declaration is claimed. Respect upstream rights |
| and attribution when redistributing the assets. |
|
|
