Update default pi0 ckpt_path and documentation for the new weights

tools/env_setup/install_isaac.sh

@@ -35,7 +35,7 @@ mkdir -p "$PROJECT_ROOT/third_party"
 # ---- Install IsaacSim ----
 echo "Installing IsaacSim..."
 pip install 'isaacsim[all,extscache]==4.5.0' \
-    git+ssh://[email protected]/isaac-for-healthcare/i4h-asset-catalog.git@main \
+    git+ssh://[email protected]/isaac-for-healthcare/i4h-asset-catalog.git@v0.2.0rc1 \
     --extra-index-url https://pypi.nvidia.com
 
 ISAACLAB_DIR="$PROJECT_ROOT/third_party/IsaacLab"

workflows/robotic_surgery/README.md

@@ -94,7 +94,7 @@ Download the required assets using:
 i4h-asset-retrieve
 ```
 
-This will download assets to `~/.cache/i4h-assets/<sha256>`. For more details, refer to the [Asset Container Helper](https://github.com/isaac-for-healthcare/i4h-asset-catalog/blob/v0.1.0/docs/catalog_helper.md).
+This will download assets to `~/.cache/i4h-assets/<sha256>`. For more details, refer to the [Asset Container Helper](https://github.com/isaac-for-healthcare/i4h-asset-catalog/blob/v0.2.0rc1/docs/catalog_helper.md).
 
 ### Environment Variables
 

workflows/robotic_surgery/docker/Dockerfile

@@ -46,7 +46,7 @@ ENV PYTHONPATH=/workspace/robotic_surgery/scripts
 
 ENV PYTHON_EXECUTABLE=/workspace/isaaclab/_isaac_sim/python.sh
 
-RUN --mount=type=ssh $PYTHON_EXECUTABLE -m pip install --no-deps git+ssh://[email protected]/isaac-for-healthcare/i4h-asset-catalog.git@main
+RUN --mount=type=ssh $PYTHON_EXECUTABLE -m pip install --no-deps git+ssh://[email protected]/isaac-for-healthcare/i4h-asset-catalog.git@v0.2.0rc1
 
 # Install the robotic surgery extensions
 # Extension installation also needs to know which python to use via the PYTHON_EXECUTABLE environment variable

workflows/robotic_ultrasound/README.md

@@ -86,7 +86,7 @@ conda activate robotic_ultrasound
 
 ##### Install Raytracing Ultrasound Simulator
 Choose one of the following options:
-- **(Experimental)** Download the pre-release version from [here](https://github.com/isaac-for-healthcare/i4h-sensor-simulation/releases/tag/v0.1.0) and extract to `workflows/robotic_ultrasound/scripts/raysim`
+- **(Experimental)** Download the pre-release version from [here](https://github.com/isaac-for-healthcare/i4h-sensor-simulation/releases/tag/v0.2.0rc1) and extract to `workflows/robotic_ultrasound/scripts/raysim`
 - **(Recommended)** Install and build following instructions in [Raytracing Ultrasound Simulator](https://github.com/isaac-for-healthcare/i4h-sensor-simulation/tree/main/ultrasound-raytracing#installation)
 
 ##### Install All Dependencies
@@ -129,7 +129,7 @@ Download the required assets using:
 i4h-asset-retrieve
 ```
 
-This will download assets to `~/.cache/i4h-assets/<sha256>`. For more details, refer to the [Asset Container Helper](https://github.com/isaac-for-healthcare/i4h-asset-catalog/blob/v0.1.0/docs/catalog_helper.md).
+This will download assets to `~/.cache/i4h-assets/<sha256>`. For more details, refer to the [Asset Container Helper](https://github.com/isaac-for-healthcare/i4h-asset-catalog/blob/v0.2.0rc1/docs/catalog_helper.md).
 
 **Note**: During asset download, you may see warnings about blocking functions. This is expected behavior and the download will complete successfully despite these warnings.
 

workflows/robotic_ultrasound/docker/Dockerfile

@@ -83,7 +83,7 @@ ENV PYTHON_EXECUTABLE=/workspace/isaaclab/_isaac_sim/python.sh
 # # Set up the Simulation
 RUN --mount=type=ssh \
     $PYTHON_EXECUTABLE -m pip install --no-deps \
-        git+ssh://[email protected]/isaac-for-healthcare/i4h-asset-catalog.git@main && \
+        git+ssh://[email protected]/isaac-for-healthcare/i4h-asset-catalog.git@v0.2.0rc1 && \
     $PYTHON_EXECUTABLE -m pip install \
         rti.connext==7.3.0 \
         pyrealsense2==2.55.1.6486 \

workflows/robotic_ultrasound/scripts/simulation/README.md

@@ -331,7 +331,7 @@ based on 3D meshes. The simulator uses Holoscan framework and DDS communication
 
 #### NVIDIA OptiX Raytracing with Python Bindings
 
-For instructions on preparing and building the Python module, please refer to the [Environment Setup](../../README.md#install-the-raytracing-ultrasound-simulator) instructions and [Ultrasound Raytracing README](https://github.com/isaac-for-healthcare/i4h-sensor-simulation/blob/v0.1.0/ultrasound-raytracing/README.md) to setup the `raysim` module correctly.
+For instructions on preparing and building the Python module, please refer to the [Environment Setup](../../README.md#install-the-raytracing-ultrasound-simulator) instructions and [Ultrasound Raytracing README](https://github.com/isaac-for-healthcare/i4h-sensor-simulation/blob/v0.2.0rc1/ultrasound-raytracing/README.md) to setup the `raysim` module correctly.
 
 
 #### Configuration

workflows/robotic_ultrasound/scripts/simulation/environments/sim_with_dds.py

@@ -316,7 +316,7 @@ def main():
                 robot_obs = []
                 for t in range(max_timesteps):
                     # get and publish the current images and joint positions
-                    rgb_images, depth_images = capture_camera_images(
+                    rgb_images, depth_images, _ = capture_camera_images(
                         env, ["room_camera", "wrist_camera"], device=env.unwrapped.device
                     )
                     pub_data["room_cam"], pub_data["room_cam_depth"] = (
@@ -406,7 +406,7 @@ def main():
                     for _ in range(reset_steps):
                         reset_tensor = get_reset_action(env)
                         obs, rew, terminated, truncated, info_ = env.step(reset_tensor)
-            if episode_idx >= total_episodes - 1 or actions is None:
+            if (episode_idx >= total_episodes - 1 or actions is None) and reset_to_recorded_data:
                 print(f"Reached the end of available episodes ({episode_idx + 1}/{total_episodes})")
                 break
 

workflows/robotic_ultrasound/scripts/simulation/evaluation/README.md

@@ -67,6 +67,28 @@ If no prediction source arguments (`--method-name`, etc.) are provided via the c
 
 The script expects predicted trajectory files to be found at `data_root/file_pattern`.
 
+## Downloading Model Weights
+
+The four policy models discussed in the evaluation (Pi0-400, Pi0-800 w/ cosmos, GR00T-N1-400, and GR00T-N1-800 w/ cosmos) can be obtained using the `i4h_asset_helper` utility. This utility helps manage and download versioned assets.
+
+To integrate these models into your workflow, you would typically define an `Assets` class that inherits from `BaseI4HAssets`, specifying the asset identifiers. Below is an example demonstrating how these might be structured.
+
+```python
+from i4h_asset_helper import BaseI4HAssets
+
+class Assets(BaseI4HAssets):
+    Pi0_400 = "Policies/LiverScan/Pi0"
+    Pi0_800 = "Policies/LiverScan/Pi0_Cosmos"
+    GR00TN1_400 = "Policies/LiverScan/GR00TN1"
+    GR00TN1_800 = "Policies/LiverScan/GR00TN1_Cosmos"
+
+my_assets = Assets()
+```
+
+You can then use these definitions in your scripts to get the local path to the downloaded model files, for example:
+`pi0_400_model = my_assets.Pi0_400`
+`gr00t_800_model = my_assets.GR00TN1_800`
+
 ## Understanding the Outputs & Experiment Results Comparison
 
 The `evaluate_trajectories.py` script generates several outputs to help you assess the performance of trajectory prediction methods. Below is a description of these outputs, along with an example showcasing a comparison between Pi0 and GR00T-N1 models.

workflows/robotic_ultrasound/scripts/simulation/examples/ultrasound_raytracing.py

@@ -232,13 +232,13 @@ def add_mesh(filename, material_name):
         default_curvilinear_probe_params = {
             "num_elements": 256,
             "sector_angle": 73.0,  # degrees
-            "radius": 45.0,         # mm
-            "frequency": 2.5,       # MHz
+            "radius": 45.0,  # mm
+            "frequency": 2.5,  # MHz
             "elevational_height": 7.0,  # mm
             "num_el_samples": 1,
-            "f_num": 1.0,          # unitless
-            "speed_of_sound": 1.54, # mm/us
-            "pulse_duration": 2.0   # cycles
+            "f_num": 1.0,  # unitless
+            "speed_of_sound": 1.54,  # mm/us
+            "pulse_duration": 2.0,  # cycles
         }
 
         default_sim_params = {
@@ -292,7 +292,7 @@ def add_mesh(filename, material_name):
             num_el_samples=probe_params["num_el_samples"],
             f_num=probe_params["f_num"],
             speed_of_sound=probe_params["speed_of_sound"],
-            pulse_duration=probe_params["pulse_duration"]
+            pulse_duration=probe_params["pulse_duration"],
         )
 
         # Create simulator

workflows/robotic_ultrasound/scripts/simulation/utils/assets.py

@@ -23,7 +23,7 @@ class Assets(BaseI4HAssets):
     panda = "Robots/Franka/Collected_panda_assembly/panda_assembly.usda"
     phantom = "Props/ABDPhantom/phantom.usda"
     table_with_cover = "Props/VentionTableWithBlackCover/table_with_cover.usd"
-    policy_ckpt = "Policies/LiverScan"
+    policy_ckpt = "Policies/LiverScan/Pi0"
     organs = "Props/ABDPhantom/Organs"
 
 

workflows/telesurgery/docker/Dockerfile

@@ -70,7 +70,7 @@ ENV PYTHON_EXECUTABLE=/workspace/isaaclab/_isaac_sim/python.sh
 # # Set up the Simulation
 RUN --mount=type=ssh \
     $PYTHON_EXECUTABLE -m pip install --no-deps \
-        git+ssh://[email protected]/isaac-for-healthcare/i4h-asset-catalog.git@main
+        git+ssh://[email protected]/isaac-for-healthcare/i4h-asset-catalog.git@v0.2.0rc1
 
 RUN mkdir -p /workspace/third_party