Update ego4robo doc

docs/source/references/egocentric_hand_reconstruction.rst

@@ -7,11 +7,26 @@ Egocentric Hand Reconstruction
 Automated pipeline for 4D hand and camera pose reconstruction from egocentric
 videos. Integrates ViPE and Dyn-HaMR in containerized environments.
 
+.. list-table::
+   :widths: 50 50
+
+   * - .. image:: ../_static/egocentric-input.gif
+          :alt: Source egocentric video
+          :width: 100%
+          :class: no-image-zoom
+     - .. image:: ../_static/egocentric-reconstruction.gif
+          :alt: Smooth fit grid reconstruction
+          :width: 100%
+          :class: no-image-zoom
+   * - .. centered:: Source egocentric video
+     - .. centered:: Reconstructed 4D hand and camera poses
+
+
 Video Capture
 ---------------------------
 
 To capture egocentric video with an OAK camera, see the
-:doc:`/device/oak` documentation.
+`OAK camera plugin <https://nvidia.github.io/IsaacTeleop/main/device/oak.html>`_ documentation.
 
 Setup
 -----
@@ -20,9 +35,42 @@ System Requirement
 ^^^^^^^^^^^^^^^^^^
 
 - OS: Ubuntu 24.04
-- GPU: NVIDIA RTX 6000 Ada or L40
-- Memory: 100GB (for a reference 30s video, more for longer)
-- Storage: 100GB
+- GPU: NVIDIA RTX 6000 Ada, L40, H100, GeForce RTX 3090, GeForce RTX 4090
+- System RAM: 100GB (for a reference 30s video, more for longer)
+- System VRAM: 12GB (for a reference 30s video, more for longer)
+- Free Disk: 100GB
+
+Prerequisites
+^^^^^^^^^^^^^
+
+Ensure the following are installed and configured before starting:
+
+**Docker ≥ 20.10** (BuildKit support required):
+
+.. code-block:: bash
+
+   docker --version  # should print 20.10 or newer
+
+**NVIDIA Container Toolkit** — required for GPU access inside containers:
+
+- Install guide: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html
+
+**Python tooling** — required only for downloading videos from S3/Swift URLs:
+
+.. code-block:: bash
+
+   pip install boto3
+
+
+Checkout the code
+^^^^^^^^^^^^^^^^^
+
+.. code-block:: bash
+
+   git clone https://github.com/NVIDIA/IsaacTeleop.git
+   cd IsaacTeleop/src/postprocessing/egocentric_hand_reconstruction
+
+The ``./docker`` and ``./scripts`` directories referenced in this guide are located under this directory.
 
 Prepare data files
 ^^^^^^^^^^^^^^^^^^
@@ -32,19 +80,18 @@ Place required files in the ``outputs/`` directory.
 .. code-block:: text
 
    ...
-   ├── doc/
    ├── docker/
    ├── scripts/
-   ├── ...
+   ├── osmo/
    └── outputs/
        ├── MANO_RIGHT.pkl
        └── BMC/
            └── *.npy
 
 **MANO model** (required):
 
-- Download from: https://mano.is.tue.mpg.de/
-- Place: ``outputs/MANO_RIGHT.pkl``
+- Create an academic account at https://mano.is.tue.mpg.de/ and accept the license.
+- The download is a ZIP archive — extract it and place ``MANO_RIGHT.pkl`` in ``outputs/``.
 
 **BMC data** (required):
 
@@ -106,10 +153,11 @@ Run complete reconstruction (ViPE + Dyn-HaMR) with a single command:
    # Using a remote video file
    ./scripts/run_reconstruction.sh s3://path/to/your_video.mp4
 
-The script accepts either a **local file path** or a ``s3://`` **URL**
-pointing to a video on a S3-compatible cloud storage. When a URL is provided,
-the video is automatically downloaded to the ``outputs/`` directory before
-processing begins.
+The script accepts either a **local file path** or a remote **URL**
+pointing to a video on cloud storage. Both ``s3://`` URLs (S3-compatible
+cloud storage) and ``swift://`` URLs (OpenStack Object Storage) are
+supported. When a URL is provided, the video is automatically downloaded
+to the ``outputs/`` directory before processing begins.
 
 To use a remote video, set the following environment variables for
 credentials:
@@ -148,6 +196,53 @@ The pipeline will:
 3. Run Dyn-HaMR for hand reconstruction.
 4. Save all results to ``outputs/logs/``.
 
+Batch Reconstruction with OSMO
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+For large-scale batch processing, the pipeline can be submitted as an
+`OSMO <https://github.com/NVIDIA/OSMO>`_ workflow using ``hand_reconstruction.yaml``.
+This runs ViPE and Dyn-HaMR as two chained tasks on a GPU pool.
+
+**Prerequisites:**
+
+- A working OSMO cluster deployment (see the `OSMO deployment guide <https://nvidia.github.io/OSMO/main/deployment_guide/getting_started/infrastructure_setup.html>`_)
+- OSMO CLI installed and authenticated (``osmo login …``)
+- Bucket and image registry credentials stored in OSMO
+- Container images built and pushed to your registry (see `Build Docker images`_)
+- MANO and BMC assets available at an S3 URL
+
+See ``osmo/README.md`` for full setup details including credential registration and container image push steps.
+
+**Submit a workflow:**
+
+.. code-block:: bash
+
+   osmo workflow submit osmo/hand_reconstruction.yaml \
+       --pool POOL_NAME \
+       --set-string \
+           experiment_id=EXPERIMENT_ID \
+           source_url=s3://INPUT_S3_PATH \
+           dest_url=s3://OUTPUT_S3_PATH \
+           assets_url=s3://ASSETS_S3_PATH \
+           vipe_image=CONTAINER_REGISTRY/ego_vipe:TAG \
+           dynhamr_image=CONTAINER_REGISTRY/ego_dynhamr:TAG
+
+**Monitor progress:**
+
+.. code-block:: bash
+
+   osmo workflow logs WORKFLOW_ID -n 100
+
+Estimated Runtime
+^^^^^^^^^^^^^^^^^
+
+For a reference 30-second video, expect approximately:
+
+- **ViPE**: ~7 minutes
+- **Dyn-HaMR**: ~30 minutes
+
+Actual runtime may vary depending on system hardware and video length.
+
 View results
 ^^^^^^^^^^^^
 
@@ -158,3 +253,8 @@ View results
 
    # View visualization
    vlc outputs/logs/video-custom/<DATE>/<VIDEO_NAME>*/*_grid.mp4
+
+Limitations
+-----------
+
+The quality of the reconstructed result is directly related to the capture quality of the egocentric video.

src/postprocessing/egocentric_hand_reconstruction/osmo/README.md

@@ -23,11 +23,11 @@ The reconstruction pipeline requires two sets of external data files, stored in
 - **MANO_RIGHT.pkl**
 - **BMC/**
 
-See [`doc/quickstart.md`](../doc/quickstart.md) for detailed setup instructions.
+See [`Isaac Teleop Documentation`](https://nvidia.github.io/IsaacTeleop/main/references/egocentric_hand_reconstruction.html) for detailed setup instructions.
 
 ### Container images
 
-The workflow requires two container images (`vipe_image` and `dynhamr_image`). Build them locally following the instructions in [`doc/quickstart.md`](../doc/quickstart.md):
+The workflow requires two container images (`vipe_image` and `dynhamr_image`). Build them locally following the instructions in [`Isaac Teleop Documentation`](https://nvidia.github.io/IsaacTeleop/main/references/egocentric_hand_reconstruction.html):
 
 ```bash
 ./docker/vipe.sh build
@@ -107,7 +107,6 @@ osmo credential set REGISTRY_CREDENTIAL \
 
 See the [OSMO credentials documentation](https://nvidia.github.io/OSMO/main/user_guide/getting_started/credentials.html) for details.
 
-
 ## Template Parameters
 
 The workflow uses `{{placeholder}}` template variables that are filled at submission time via `--set-string`: