Clean standalone action viewer release

Co-authored-by: Koi <Koi@users.noreply.huggingface.co>

.dockerignore

@@ -0,0 +1,15 @@
+.git
+__pycache__
+*.pyc
+*.pyo
+*.pyd
+.cache
+.venv
+venv
+.env
+.DS_Store
+data
+
+# Exclude vendored LFS pointer assets not needed by the viewer.
+cosmos-framework/inputs/omni/01_hammer_nail.png
+cosmos-framework/assets/cosmos-logo-thumbnail.png

.gitattributes

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+assets/examples/bridge_lerobot_v3/meta/episodes/chunk-000/file-000.parquet filter=lfs diff=lfs merge=lfs -text
+assets/examples/bridge_lerobot_v3/videos/observation.images.image_0/chunk-000/file-000.mp4 filter=lfs diff=lfs merge=lfs -text
+assets/examples/RoboMIND_20251228/benchmark1_0_release/franka_3rgb/241021_close_trash_bin_1/meta/episodes/chunk-000/file-000.parquet filter=lfs diff=lfs merge=lfs -text
+assets/examples/RoboMIND_20251228/benchmark1_1_release/franka_fr3_dual/both_pour_water/data/chunk-000/file-000.parquet filter=lfs diff=lfs merge=lfs -text
+assets/examples/RoboMIND_20251228/benchmark1_1_release/franka_fr3_dual/both_pour_water/meta/episodes/chunk-000/file-000.parquet filter=lfs diff=lfs merge=lfs -text
+assets/examples/RoboMIND_20251228/benchmark1_1_release/franka_fr3_dual/both_pour_water/videos/observation.images.camera_front/chunk-000/file-000.mp4 filter=lfs diff=lfs merge=lfs -text
+assets/examples/RoboMIND_20251228/benchmark1_1_release/franka_fr3_dual/both_pour_water/videos/observation.images.camera_left/chunk-000/file-000.mp4 filter=lfs diff=lfs merge=lfs -text
+assets/examples/RoboMIND_20251228/benchmark1_1_release/franka_fr3_dual/both_pour_water/videos/observation.images.camera_right/chunk-000/file-000.mp4 filter=lfs diff=lfs merge=lfs -text
+assets/examples/droid_plus_lerobot_640x360_20260412/success/data/chunk-000/file-000.parquet filter=lfs diff=lfs merge=lfs -text
+assets/examples/droid_plus_lerobot_640x360_20260412/success/meta/episodes/chunk-000/file-000.parquet filter=lfs diff=lfs merge=lfs -text
+assets/examples/droid_plus_lerobot_640x360_20260412/success/videos/observation.image.exterior_image_1_left/chunk-000/file-000.mp4 filter=lfs diff=lfs merge=lfs -text
+assets/examples/droid_plus_lerobot_640x360_20260412/success/videos/observation.image.exterior_image_2_left/chunk-000/file-000.mp4 filter=lfs diff=lfs merge=lfs -text
+assets/examples/droid_plus_lerobot_640x360_20260412/success/videos/observation.image.wrist_image_left/chunk-000/file-000.mp4 filter=lfs diff=lfs merge=lfs -text
+assets/examples/fractal20220817_data/videos/observation.images.image/chunk-000/file-000.mp4 filter=lfs diff=lfs merge=lfs -text
+assets/examples/av_v2_03292026_wdinfo/data/00000000.tar filter=lfs diff=lfs merge=lfs -text
+assets/examples/fastumi/fastumi_single_arm/pour_coke/videos/observation.image.right_main_camera_rgb/chunk-000/file-000.mp4 filter=lfs diff=lfs merge=lfs -text
+assets/examples/AgiBotWorld-GEAR_20260208/agibot-offshelf/20251016_500h/gripper/task_1018/data/chunk-000/file_000.parquet filter=lfs diff=lfs merge=lfs -text
+assets/examples/AgiBotWorld-GEAR_20260208/agibot-offshelf/20251016_500h/gripper/task_1018/videos/observation.images.hand_left/chunk-000/file-000.mp4 filter=lfs diff=lfs merge=lfs -text
+assets/examples/AgiBotWorld-GEAR_20260208/agibot-offshelf/20251016_500h/gripper/task_1018/videos/observation.images.hand_right/chunk-000/file-000.mp4 filter=lfs diff=lfs merge=lfs -text
+assets/examples/AgiBotWorld-GEAR_20260208/agibot-offshelf/20251016_500h/gripper/task_1018/videos/observation.images.top_head/chunk-000/file-000.mp4 filter=lfs diff=lfs merge=lfs -text

Dockerfile

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+FROM python:3.11-slim
+
+ENV PYTHONUNBUFFERED=1 \
+    PORT=7860 \
+    PIP_NO_CACHE_DIR=1 \
+    HF_HUB_DISABLE_XET=1
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    git curl ca-certificates ffmpeg build-essential linux-libc-dev \
+    libgl1 libglib2.0-0 libegl1 libosmesa6 libgomp1
+
+WORKDIR /app
+
+COPY cosmos-framework /app/cosmos-framework
+COPY assets /app/assets
+COPY start.sh /app/start.sh
+
+RUN python -m pip install --upgrade pip uv \
+ && uv pip install --system torch==2.6.0 torchvision==0.21.0 --index-url https://download.pytorch.org/whl/cpu \
+ && uv pip install --system -e /app/cosmos-framework --no-deps \
+ && uv pip install --system \
+    accelerate av cattrs diffusers einops hydra-core imageio imageio-ffmpeg loguru msgpack \
+    obstore omegaconf pydantic requests scipy termcolor 'transformers>=4.57.1,<5.0.0' tyro websockets \
+    boto3 pyyaml lerobot==0.4.4 pandas pyarrow 'datasets>=2.19.0' \
+    viser mujoco pin trimesh opencv-python-headless huggingface_hub hf_transfer iopath \
+ && uv pip install --system torchcodec==0.2.* --index-url https://download.pytorch.org/whl/cpu
+
+CMD ["bash", "/app/start.sh"]

README.md

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+---
+title: Cosmos3 Action Viewer
+emoji: 🤖
+colorFrom: blue
+colorTo: green
+sdk: docker
+app_port: 7860
+pinned: false
+license: other
+---
+
+# Cosmos3 Action Viewer
+
+Minimal Docker Space for a standalone Cosmos3 action data viewer.
+
+Packaged local demo data under `assets/examples/`:
+
+- Bridge: 2 local episodes
+- Fractal: 1 local episode
+- DROID: 1 local success episode
+- RoboMIND Franka: 1 local episode
+- RoboMIND Franka dual: 1 local episode
+- AV: 1 local wdinfo/tar shard with 10 samples
+- UMI/FastUMI: 1 local episode
+
+Runtime behavior: no HF dataset download or video streaming by default. The app runs the existing `viser` URDF/action viewer on the Hugging Face Spaces port.
+
+Environment overrides are still supported for larger mounted datasets:
+
+- `BRIDGE_LEROBOT_ROOT`
+- `FRACTAL_ROOT`
+- `DROID_ROOT`
+- `ROBOMIND_FRANKA_ROOT`
+- `ROBOMIND_FRANKA_DUAL_ROOT`
+- `AV_ROOT`
+- `UMI_ROOT`

assets/examples/RoboMIND_20251228/benchmark1_0_release/franka_3rgb/241021_close_trash_bin_1/manifest.json

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+{
+  "source_root": "/lustre/fsw/portfolios/cosmos/projects/cosmos_base_training/cosmos3_action_datasets/RoboMIND_20251228/benchmark1_0_release/franka_3rgb/241021_close_trash_bin_1",
+  "source_episode": 0,
+  "local_episode": 0,
+  "source_index_range": [
+    0,
+    120
+  ],
+  "frames": 120,
+  "source_task_indices": [
+    0
+  ],
+  "tasks": [
+    "Close the trash can by pressing down from the back."
+  ],
+  "videos": [
+    "videos/observation.images.camera_top/chunk-000/file-000.mp4",
+    "videos/observation.images.camera_left/chunk-000/file-000.mp4",
+    "videos/observation.images.camera_right/chunk-000/file-000.mp4"
+  ]
+}

assets/examples/RoboMIND_20251228/benchmark1_0_release/franka_3rgb/241021_close_trash_bin_1/meta/episodes/chunk-000/file-000.parquet

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+oid sha256:fdbf9cef8d1a5d04e90459c24f3b2092c598ebf3459fc90740357b340bb08faf
+size 123148

assets/examples/RoboMIND_20251228/benchmark1_0_release/franka_3rgb/241021_close_trash_bin_1/meta/info.json

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+{
+  "codebase_version": "v3.0",
+  "robot_type": "franka_3rgb",
+  "total_episodes": 1,
+  "total_frames": 120,
+  "total_tasks": 1,
+  "chunks_size": 1000,
+  "data_files_size_in_mb": 100,
+  "video_files_size_in_mb": 200,
+  "fps": 30,
+  "splits": {
+    "train": "0:1"
+  },
+  "data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
+  "video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4",
+  "features": {
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+      "dtype": "video",
+      "shape": [
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+        1280,
+        3
+      ],
+      "names": [
+        "height",
+        "width",
+        "rgb"
+      ],
+      "info": {
+        "video.height": 720,
+        "video.width": 1280,
+        "video.codec": "av1",
+        "video.pix_fmt": "yuv420p",
+        "video.is_depth_map": false,
+        "video.fps": 30,
+        "video.channels": 3,
+        "has_audio": false
+      }
+    },
+    "observation.images.camera_left": {
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+          "gripper"
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+  }
+}

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assets/examples/bridge_lerobot_v3/README.md

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+---
+pretty_name: Bridge LeRobot v3
+library_name: lerobot
+tags:
+- robotics
+- robot-learning
+- vision-language-action
+- bridgedata
+- bridge
+- lerobot
+- LeRobotDataset-v3
+license: openmdw-1.0
+---
+
+# Bridge LeRobot v3
+
+## Dataset Summary
+
+`nvidia/bridge_lerobot_v3` is a LeRobotDataset v3.0 conversion of the BridgeDataset / BridgeData V2 robot manipulation dataset. BridgeData V2 is a large-scale real-world robotics dataset collected to support scalable robot learning, including imitation learning, offline reinforcement learning, and open-vocabulary multi-task policies conditioned on goal images or natural-language instructions.
+
+This repository packages Bridge trajectories in the LeRobot v3 layout with Parquet state/action data, MP4 video observations, and structured LeRobot metadata. The converted repository's `meta/info.json` reports 50,415 episodes, 1,801,090 frames, 22,199 task IDs, and a 5 Hz sampling rate.
+
+## Dataset Details
+
+### Dataset Description
+
+BridgeData V2 contains robot manipulation behaviors collected across varied tabletop and toy-kitchen environments. The upstream dataset was designed to study generalization across tasks, objects, environments, institutions, and conditioning modes such as language instructions and goal images.
+
+This LeRobot v3 conversion preserves the dataset for workflows that use the LeRobot data loader and Hugging Face Hub-native robotics dataset conventions. The conversion changes the storage layout: frame-level tabular data is stored in Apache Parquet shards, visual observations are stored as MP4 videos, and metadata records the schema, feature statistics, task IDs, episode boundaries, and path templates.
+
+### Dataset Sources
+
+- Repository: https://huggingface.co/datasets/nvidia/bridge_lerobot_v3
+- BridgeData V2 project page: https://rail-berkeley.github.io/bridgedata/
+- BridgeData V2 paper: https://arxiv.org/abs/2308.12952
+- LeRobotDataset v3.0 documentation: https://huggingface.co/docs/lerobot/lerobot-dataset-v3
+
+## Uses
+
+### Direct Use
+
+This dataset is intended for research and development in:
+
+- robot imitation learning
+- offline reinforcement learning
+- vision-language-action model training
+- goal-conditioned and language-conditioned robot policy learning
+- multi-camera visuomotor policy learning
+- evaluation of LeRobot-compatible training, streaming, and data-loading workflows
+
+### Out-of-Scope Use
+
+This dataset is not intended to be used as the sole validation source for safety-critical robot deployment. Policies trained on this data should be evaluated in the target environment, with appropriate robot safety controls, before any physical deployment.
+
+## Dataset Structure
+
+The repository follows the LeRobotDataset v3.0 layout:
+
+```text
+.
++-- data/
+|   `-- chunk-000/
+|       `-- file-*.parquet
++-- meta/
+|   +-- info.json
+|   +-- stats.json
+|   +-- tasks.parquet
+|   `-- episodes/
+|       `-- chunk-000/
+|           `-- file-*.parquet
+`-- videos/
+    `-- observation.images.<camera_key>/
+        `-- chunk-000/
+            `-- file-*.mp4
+```
+
+### Repository Metadata
+
+The following values are taken from the repository's `meta/info.json`.
+
+| Field | Value |
+|---|---:|
+| LeRobot codebase version | `v3.0` |
+| Episodes | 50,415 |
+| Frames | 1,801,090 |
+| Task IDs | 22,199 |
+| Split | `train: 0:50415` |
+| FPS | 5 |
+| Average episode length | 35.7 frames, about 7.1 seconds |
+| Robot type in metadata | `null` |
+
+The upstream BridgeData V2 project describes the source data as collected on a WidowX 250 6DOF robot arm at 5 Hz. The converted repository does not populate `robot_type` in `meta/info.json`.
+
+### Features
+
+The following feature schema is declared in `meta/info.json`.
+
+| Feature | Type | Shape / Details |
+|---|---|---|
+| `observation.images.image_0` | video | RGB, 480 x 640, AV1 MP4, 5 FPS, no audio |
+| `observation.images.image_1` | video | RGB, 480 x 640, AV1 MP4, 5 FPS, no audio |
+| `observation.images.image_2` | video | RGB, 480 x 640, AV1 MP4, 5 FPS, no audio |
+| `observation.images.image_3` | video | RGB, 480 x 640, AV1 MP4, 5 FPS, no audio |
+| `observation.state` | `float32` | 7-dimensional robot state |
+| `action` | `float32` | 7-dimensional robot action |
+| `timestamp` | `float32` | Frame timestamp |
+| `frame_index` | `int64` | Frame index within episode |
+| `episode_index` | `int64` | Episode index |
+| `task_index` | `int64` | Task ID |
+| `index` | `int64` | Global frame index |
+
+### File Format
+
+- Frame-level state/action data: Apache Parquet under `data/`.
+- Episode metadata: chunked Parquet under `meta/episodes/`.
+- Task metadata: `meta/tasks.parquet`.
+- Dataset schema and statistics: `meta/info.json` and `meta/stats.json`.
+- Video observations: AV1-encoded MP4 files under `videos/`.
+
+## Loading
+
+Authenticate with Hugging Face if required, then download or stream the dataset using LeRobot-compatible tooling.
+
+```python
+from huggingface_hub import snapshot_download
+
+repo_dir = snapshot_download(
+    repo_id="nvidia/bridge_lerobot_v3",
+    repo_type="dataset",
+    token=True,
+)
+
+print(repo_dir)
+```
+
+Example LeRobot usage:
+
+```python
+from lerobot.datasets.lerobot_dataset import LeRobotDataset
+
+dataset = LeRobotDataset("nvidia/bridge_lerobot_v3")
+print(dataset.num_episodes)
+print(dataset.meta.info["features"].keys())
+```
+
+## Dataset Creation
+
+### Source Data
+
+The source dataset is BridgeData V2, a real-world robot manipulation dataset with diverse tasks, objects, camera poses, and environments. The BridgeData V2 project page reports 60,096 trajectories across 24 environments and 13 skills, including teleoperated demonstrations and scripted pick-and-place rollouts.
+
+This converted repository reports 50,415 episodes in `meta/info.json`; users should treat the repository metadata as authoritative for this LeRobot package and consult upstream BridgeData V2 documentation for the full source dataset description.
+
+### Conversion
+
+This repository converts Bridge data into LeRobotDataset v3.0. In v3, multiple episodes can be concatenated into larger Parquet and MP4 shard files, while metadata is used to recover per-episode boundaries and feature statistics. This layout reduces file-system pressure and supports Hub-native loading and streaming workflows.
+
+## Bias, Risks, and Limitations
+
+- The dataset reflects the embodiment, control frequency, camera setup, task distribution, and environments of the source BridgeData V2 collection.
+- The upstream data is concentrated around tabletop and toy-kitchen manipulation tasks; policies trained only on this dataset may not generalize to other robots, objects, lighting, homes, labs, or industrial settings.
+- Natural-language task annotations are inherited from the source/conversion pipeline and should be inspected before task-specific filtering or evaluation.
+- The repository metadata reports a converted package with fewer episodes than the full upstream BridgeData V2 trajectory count.
+- This dataset should not be used as the sole basis for validating safe real-world robot behavior.
+
+## Personal and Sensitive Information
+
+BridgeData V2 is robot manipulation data collected in controlled robotics environments. It is not intended to contain personal or sensitive information. Because the source uses real camera imagery, users should still inspect samples for their own release, redistribution, or downstream demo requirements.
+
+## Citation
+
+If you use this dataset, please cite the original BridgeData V2 paper:
+
+```bibtex
+@inproceedings{walke2023bridgedata,
+    title={BridgeData V2: A Dataset for Robot Learning at Scale},
+    author={Walke, Homer and Black, Kevin and Lee, Abraham and Kim, Moo Jin and Du, Max and Zheng, Chongyi and Zhao, Tony and Hansen-Estruch, Philippe and Vuong, Quan and He, Andre and Myers, Vivek and Fang, Kuan and Finn, Chelsea and Levine, Sergey},
+    booktitle={Conference on Robot Learning (CoRL)},
+    year={2023}
+}
+```
+
+Please also cite or reference LeRobot if you use LeRobot tooling, dataset loaders, or streaming interfaces.
+
+## References
+
+- BridgeData V2 project page: https://rail-berkeley.github.io/bridgedata/
+- BridgeData V2 arXiv paper: https://arxiv.org/abs/2308.12952
+- BridgeData V2 Hugging Face paper page: https://huggingface.co/papers/2308.12952
+- LeRobotDataset v3.0 blog: https://huggingface.co/blog/lerobot-datasets-v3
+- LeRobotDataset v3.0 documentation: https://huggingface.co/docs/lerobot/lerobot-dataset-v3

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assets/examples/fastumi/fastumi_single_arm/pour_coke/meta/tasks.jsonl

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