Merge pull request #11 from NVIDIA-ISAAC-ROS/release-dp-2

Isaac ROS 0.20.0 (DP2)

Author: hemalshahNV

CONTRIBUTING.md

@@ -0,0 +1,14 @@
+# Isaac ROS Contribution Rules
+
+Any contribution that you make to this repository will
+be under the Apache 2 License, as dictated by that
+[license](http://www.apache.org/licenses/LICENSE-2.0.html):
+
+> **5. Submission of Contributions.** Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions.
+
+Contributors must sign-off each commit by adding a `Signed-off-by: ...`
+line to commit messages to certify that they have the right to submit
+the code they are contributing to the project according to the
+[Developer Certificate of Origin (DCO)](https://developercertificate.org/).
+
+[//]: # (202201002)

LICENSE

@@ -1,50 +1,62 @@
-# Tutorial with Isaac Sim
+# Tutorial for DNN Image Segmentation with Isaac Sim
+
+<div align="center"><img alt="Coloured Segmentation Mask" src="../resources/Isaac_sim_peoplesemsegnet_shuffleseg_rqt.png" width="600px" title="U-Net Shuffleseg result in rqt_image_view"/></div>
+
+## Overview
+
+This tutorial walks you through a pipeline for [Image Segmentation](https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_image_segmentation) of people using images from Isaac Sim.
+
+## Tutorial Walkthrough
 
 1. Complete the [Quickstart section](../README.md#quickstart) in the main README till step 9.
 2. Launch the Docker container using the `run_dev.sh` script:
+
     ```bash
     cd ~/workspaces/isaac_ros-dev/src/isaac_ros_common && \
       ./scripts/run_dev.sh
     ```
+
 3. Inside the container, build and source the workspace:  
+
     ```bash
     cd /workspaces/isaac_ros-dev && \
       colcon build --symlink-install && \
       source install/setup.bash
     ```
+
 4. Install and launch Isaac Sim following the steps in the [Isaac ROS Isaac Sim Setup Guide](https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_common/blob/main/docs/isaac-sim-sil-setup.md)
-5. Open up the Isaac ROS Common USD scene (using the "content" window) located at:   
+5. Open up the Isaac ROS Common USD scene (using the "content" window) located at:
    `omniverse://localhost/NVIDIA/Assets/Isaac/2022.1/Isaac/Samples/ROS2/Scenario/carter_warehouse_apriltags_worker.usd`.
 
    And wait for it to load completely.
    > **Note:** To use a different server, replace `localhost` with `<your_nucleus_server>`
 6. Go to the stage tab and select `/World/Carter_ROS`, then in properties tab -> Transform -> Translate -> X change `-3.0` to `0.0`.
     <div align="center"><img src="../resources/Isaac_sim_set_carter.png" width="400px"/></div>
-</br>
-7.  Change the left camera topic name. Go to the stage tab and select `/World/Carter_ROS/ROS_Cameras/ros2_create_camera_left_rgb`, properties tab -> Compute Node -> Inputs -> topicName change `rgb_left` to `image`.
+
+7. Change the left camera topic name. Go to the stage tab and select `/World/Carter_ROS/ROS_Cameras/ros2_create_camera_left_rgb`, properties tab -> Compute Node -> Inputs -> topicName change `rgb_left` to `image`.
     <div align="center"><img src="../resources/Isaac_sim_topic_rename.png" width="400px"/></div>
-</br>
 8. Press **Play** to start publishing data from the Isaac Sim application.
     <div align="center"><img src="../resources/Isaac_sim_image_segmentation.png" width="800px"/></div>
-</br>
+
 9. Run the following launch files to start the inferencing:
-    
-```bash
-    ros2 launch isaac_ros_unet isaac_ros_unet_triton.launch.py model_name:=peoplesemsegnet_shuffleseg model_repository_paths:=['/tmp/models'] input_binding_names:=['input_2:0'] output_binding_names:=['argmax_1'] network_output_type:='argmax'
-```
-</br>
+
+    ```bash
+        ros2 launch isaac_ros_unet isaac_ros_unet_triton.launch.py model_name:=peoplesemsegnet_shuffleseg model_repository_paths:=['/tmp/models'] input_binding_names:=['input_2:0'] output_binding_names:=['argmax_1'] network_output_type:='argmax'
+    ```
+
 10. Visualize and validate the output of the package by launching `rqt_image_view` in another terminal:
 
-```bash
-cd ~/workspaces/isaac_ros-dev/src/isaac_ros_common && \
-      ./scripts/run_dev.sh
-```
-Then launch `rqt_image_view`:
-```bash
-    ros2 run rqt_image_view rqt_image_view
-```
-Then inside the `rqt_image_view` GUI, change the topic to `/unet/colored_segmentation_mask` to view a colorized segmentation mask. 
+    ```bash
+    cd ~/workspaces/isaac_ros-dev/src/isaac_ros_common && \
+        ./scripts/run_dev.sh
+    ```
+
+    Then launch `rqt_image_view`:
+
+    ```bash
+        ros2 run rqt_image_view rqt_image_view
+    ```
 
-<div align="center"><img alt="Coloured Segmentation Mask" src="../resources/Isaac_sim_peoplesemsegnet_shuffleseg_rqt.png" width="350" title="U-Net Shuffleseg result in rqt_image_view"/></div>
+    Then inside the `rqt_image_view` GUI, change the topic to `/unet/colored_segmentation_mask` to view a colorized segmentation mask.
 
-**Note:** The raw segmentation is also published to `/unet/raw_segmentation_mask`. However, the raw pixels correspond to the class labels and so the output is unsuitable for human visual inspection.
+    **Note:** The raw segmentation is also published to `/unet/raw_segmentation_mask`. However, the raw pixels correspond to the class labels and so the output is unsuitable for human visual inspection.

README.md

@@ -14,7 +14,7 @@ If you have an [Argus-compatible camera](https://github.com/NVIDIA-ISAAC-ROS/isa
 To start the graph, follow the steps below:
 
 1. Follow the [Quickstart section](../README.md#quickstart) up to step 7 in the main README.
-   
+
 2. Outside the container, clone additional repositories required to run Argus-compatible camera under `~/workspaces/isaac_ros-dev/src`.
 
     ```bash
@@ -29,30 +29,38 @@ To start the graph, follow the steps below:
     git clone https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_image_pipeline
     ```
 
-3.  Inside the container, build and source the workspace:
+3. Inside the container, build and source the workspace:
+
     ```bash
     cd /workspaces/isaac_ros-dev && \
       colcon build --symlink-install && \
       source install/setup.bash
     ```
-4.  (Optional) Run tests to verify complete and correct installation:
+
+4. (Optional) Run tests to verify complete and correct installation:
+
     ```bash
     colcon test
     ```
 
 5. Run the following launch files to start the graph:
+
     ```bash
     ros2 launch isaac_ros_unet isaac_ros_argus_unet_triton.launch.py model_name:=peoplesemsegnet_shuffleseg model_repository_paths:=['/tmp/models'] input_binding_names:=['input_2:0'] output_binding_names:=['argmax_1'] network_output_type:='argmax'
     ```
 
 6. Visualize and validate the output of the package by launching `rqt_image_view` in another terminal:
     In another terminal, enter the Docker container again:
+
     ```bash
     cd ~/workspaces/isaac_ros-dev/src/isaac_ros_common && \
       ./scripts/run_dev.sh
     ```
+
     Then launch `rqt_image_view`:
+
     ```bash
     ros2 run rqt_image_view rqt_image_view
     ```
+
     Then inside the `rqt_image_view` GUI, change the topic to `/unet/colored_segmentation_mask` to view a colorized segmentation mask. You may also view the raw segmentation, which is published to `/unet/raw_segmentation_mask`, where the raw pixels correspond to the class labels making it unsuitable for human visual inspection.

docs/tutorial-isaac-sim.md

@@ -1,10 +1,19 @@
-# Copyright (c) 2021-2022, NVIDIA CORPORATION.  All rights reserved.
+# SPDX-FileCopyrightText: NVIDIA CORPORATION & AFFILIATES
+# Copyright (c) 2021-2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 #
-# NVIDIA CORPORATION and its licensors retain all intellectual property
-# and proprietary rights in and to this software, related documentation
-# and any modifications thereto.  Any use, reproduction, disclosure or
-# distribution of this software and related documentation without an express
-# license agreement from NVIDIA CORPORATION is strictly prohibited.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# SPDX-License-Identifier: Apache-2.0
 
 cmake_minimum_required(VERSION 3.5)
 project(isaac_ros_unet LANGUAGES C CXX)
@@ -52,19 +61,9 @@ install(TARGETS unet_decoder_node
   RUNTIME DESTINATION bin
 )
 
-# Install extensions directory
-if( ${ARCHITECTURE} STREQUAL "x86_64" )
-  install(DIRECTORY gxf/lib/gxf_x86_64/ DESTINATION share/${PROJECT_NAME}/gxf)
-elseif( ${ARCHITECTURE} STREQUAL "aarch64" )
-  install(DIRECTORY gxf/lib/gxf_jetpack50/ DESTINATION share/${PROJECT_NAME}/gxf)
-endif()
 
 if(BUILD_TESTING)
   find_package(ament_lint_auto REQUIRED)
-
-  # Ignore copyright notices since we use custom NVIDIA Isaac ROS Software License
-  set(ament_cmake_copyright_FOUND TRUE)
-
   ament_lint_auto_find_test_dependencies()
 
   find_package(launch_testing_ament_cmake REQUIRED)

docs/tutorial-nitros-graph.md

@@ -1,11 +1,20 @@
 %YAML 1.2
-# Copyright (c) 2022, NVIDIA CORPORATION.  All rights reserved.
+# SPDX-FileCopyrightText: NVIDIA CORPORATION & AFFILIATES
+# Copyright (c) 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 #
-# NVIDIA CORPORATION and its licensors retain all intellectual property
-# and proprietary rights in and to this software, related documentation
-# and any modifications thereto.  Any use, reproduction, disclosure or
-# distribution of this software and related documentation without an express
-# license agreement from NVIDIA CORPORATION is strictly prohibited.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# SPDX-License-Identifier: Apache-2.0
 ---
 name: segmentation_postprocessor
 components: