Datasets:
ArXiv:
| pretty_name: SWAM Pretraining Data | |
| tags: | |
| - robotics | |
| - world-action-models | |
| - video | |
| - egocentric-video | |
| - lerobot | |
| - av1 | |
| # SWAM-Pretrain | |
| [](https://char-lotte-xia.github.io/swam-official/) | |
| <div style="display: flex; justify-content: center; align-items: center; gap: 8px; flex-wrap: wrap; margin: 12px 0 20px;"><a style="display: inline-flex; margin: 0; line-height: 0;" href="https://github.com/shaaaaron/SWAM"><img src="visual-previews/link-github.png" alt="GitHub code" width="124" height="36" style="display: inline-block; margin: 0; vertical-align: middle;"></a><a style="display: inline-flex; margin: 0; line-height: 0;" href="https://char-lotte-xia.github.io/swam-official/"><img src="visual-previews/link-website.png" alt="Project website" width="124" height="36" style="display: inline-block; margin: 0; vertical-align: middle;"></a><a style="display: inline-flex; margin: 0; line-height: 0;" href="https://arxiv.org/abs/2611.12870"><img src="visual-previews/link-arxiv.png" alt="arXiv paper" width="124" height="36" style="display: inline-block; margin: 0; vertical-align: middle;"></a></div> | |
| SWAM pretraining data is organized into **General, Ego, UMI, and Robotics**, covering general videos, egocentric videos, UMI manipulation demonstrations, and robot demonstrations. We standardize the video format, preserve source-specific episode records and annotations, and add detailed annotations for manipulation data. This repository releases the publicly distributable portion in stages. | |
| **Data is being uploaded in batches. See the [repository file list](https://huggingface.co/datasets/FreDERicia/SWAM-Pretrain/tree/main/data) for currently available downloads.** | |
| ## Data scope | |
| | Category | Data sources | Release scope | | |
| | --- | --- | --- | | |
| | General | OpenVid, Panda70M | OpenVid included; Panda70M excluded from this release | | |
| | Ego | EgoVerse, Ego4D, EgoSuite | EgoVerse included; Ego4D and EgoSuite excluded from this release | | |
| | UMI | UMI manipulation demonstrations | Awaiting a future release by Noematrix | | |
| | Robotics | AgiBot World, RoboCoin, RoboMIND, InternData A1, Galaxea, ABC-130K | Released in batches according to the release manifest | | |
| The planned release covers **26 source directories, approximately 2.94 TB** (decimal units). Directory names preserve the original organization; resolution labels describe the source data specifications. | |
| **Why some data is excluded:** Panda70M, Ego4D, and EgoSuite are subject to upstream licensing and redistribution conditions; please obtain them through their official channels. UMI data awaits a **future release by Noematrix**, with release arrangements to be announced through its official channels. | |
| ## Research data statistics | |
| The figures below describe the paper's **full pretraining data pool of approximately 47,000 hours**, including Panda70M, Ego4D, EgoSuite, and UMI, which are excluded from this release. These figures do not represent the amount of data publicly released or uploaded to this repository. | |
|  | |
| *Left: data sources and video hours. Right: shares of total video hours and episodes, and video-duration distributions within each category.* | |
| ## Data format and directory structure | |
| - **Video:** 320 pixels wide by 256 pixels high, AV1 encoded in MP4 containers. Source frame rates and temporal ordering are preserved. | |
| - **Episode records:** Parquet files retain the actions, states, and language annotations provided by each source. Available fields vary across datasets. | |
| - **Metadata:** Source-specific metadata is retained, with video-related dimensions and codec information updated for the processed files. | |
| - **Layout:** LeRobot-style `data/`, `meta/`, and `videos/` directories are packaged as TAR archives. This is an archive distribution, not a single uniform tabular dataset. | |
| Each source directory contains `metadata.tar` and one or more `chunk-*.tar` archives. Extract all archives for a source into the **same source directory**. For example: | |
| ```text | |
| archives/data/galaxea/ | |
| metadata.tar | |
| chunk-000.tar | |
| ... | |
| chunk-020.tar | |
| # After extraction: | |
| data/galaxea/ | |
| meta/ | |
| data/chunk-000/... | |
| videos/chunk-000/... | |
| ... | |
| ``` | |
| ## Download and extract | |
| Install the Hugging Face CLI: | |
| ```bash | |
| pip install -U huggingface_hub | |
| ``` | |
| Download the complete Galaxea subset: | |
| ```bash | |
| hf download FreDERicia/SWAM-Pretrain \ | |
| --repo-type dataset \ | |
| --include "data/galaxea/*.tar" \ | |
| --local-dir ./archives | |
| ``` | |
| Extract it on Linux or macOS: | |
| ```bash | |
| mkdir -p ./data/galaxea | |
| for archive in ./archives/data/galaxea/*.tar; do | |
| tar -xf "$archive" -C ./data/galaxea | |
| done | |
| ``` | |
| For a smaller download, fetch `metadata.tar` and one chunk: | |
| ```bash | |
| hf download FreDERicia/SWAM-Pretrain \ | |
| data/galaxea/metadata.tar data/galaxea/chunk-019.tar \ | |
| --repo-type dataset --local-dir ./sample-archives | |
| ``` | |
| Extract archives from the same source into the same directory. For partial downloads, load only the corresponding episodes. Video readers need **AV1 decoding support**; consult each source's `meta/info.json` for field definitions. | |
| ## Source terms and attribution | |
| This collection includes data from multiple upstream projects. Their respective licenses, attribution requirements, and usage restrictions continue to apply, including non-commercial restrictions where specified. Processing and repackaging do not grant additional rights or place the entire collection under a single permissive license. | |
| ## Code | |
| The accompanying [SWAM code repository](https://github.com/shaaaaron/SWAM) integrates RLinf, DreamZero, DMuon, and RoboTwin, with entry points for training, checkpoint conversion, and RoboTwin evaluation. The code repository is currently private and requires authorized access. | |