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ROS2 OpenVINO package - V0.3.0 Release
Signed-off-by: Chao Li <[email protected]>
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‎LICENSE‎

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‎README.md‎

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# ros2_openvino_toolkit
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## 1. Introduction
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The [OpenVINO™](https://software.intel.com/en-us/openvino-toolkit) toolkit quickly deploys applications and solutions that emulate human vision. Based on Convolutional Neural Networks (CNN), the Toolkit extends computer vision (CV) workloads across Intel® hardware, maximizing performance.
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This project is a ROS2 wrapper for CV API of [OpenVINO™](https://software.intel.com/en-us/openvino-toolkit), providing the following features:
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* Support CPU and GPU platforms
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* Support standard USB camera and Intel® RealSense™ camera
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* Support Video or Image file as detection source
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* Face detection
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* Emotion recognition
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* Age and gender recognition
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* Head pose recognition
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* Demo application to show above detection and recognitions
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## 2. Prerequisite
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- An x86_64 computer running Ubuntu 16.04. Below processors are supported:
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* 6th-8th Generation Intel® Core™
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* Intel® Xeon® v5 family
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* Intel® Xeon® v6 family
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- ROS2 [Bouncy](https://github.com/ros2/ros2/wiki)
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- [OpenVINO™ Toolkit](https://software.intel.com/en-us/openvino-toolkit)
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- RGB Camera, e.g. RealSense D400 Series or standard USB camera or Video/Image File
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- Graphics are required only if you use a GPU. The official system requirements for GPU are:
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* 6th to 8th generation Intel® Core™ processors with Iris® Pro graphics and Intel® HD Graphics
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* 6th to 8th generation Intel® Xeon® processors with Iris Pro graphics and Intel HD Graphics (excluding the e5 product family, which does not have graphics)
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* Intel® Pentium® processors N4200/5, N3350/5, N3450/5 with Intel HD Graphics
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Use one of the following methods to determine the GPU on your hardware:
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1. [lspci] command: GPU info may lie in the [VGA compatible controller] line.
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2. Ubuntu system: Menu [System Settings] --> [Details] may help you find the graphics information.
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3. Openvino: Download the install package, install_GUI.sh inside will check the GPU information before installation.
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## 3. Environment Setup
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- Install ROS2 [Bouncy](https://github.com/ros2/ros2/wiki) ([guide](https://github.com/ros2/ros2/wiki/Linux-Development-Setup))
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- Install Intel® RealSense™ SDK 2.0 [(tag v2.14.1)](https://github.com/IntelRealSense/librealsense/tree/v2.14.1)
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* [Install from source code](https://github.com/IntelRealSense/librealsense/blob/v2.14.1/doc/installation.md)(Recommended)
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* [Install from package](https://github.com/IntelRealSense/librealsense/blob/v2.14.1/doc/distribution_linux.md)
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- Install [OpenVINO™ Toolkit](https://software.intel.com/en-us/openvino-toolkit) ([guide](https://software.intel.com/en-us/articles/OpenVINO-Install-Linux))
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**Note**: Please use *root privileges* to run the installer when installing the core components.
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- Install OpenCL Driver for GPU
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```bash
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cd /opt/intel/computer_vision_sdk/install_dependencies
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sudo ./install_NEO_OCL_driver.sh
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```
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- Other Dependencies
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```bash
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# numpy
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pip3 install numpy
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# libboost
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sudo apt-get install -y --no-install-recommends libboost-all-dev
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cd /usr/lib/x86_64-linux-gnu
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sudo ln -s libboost_python-py35.so libboost_python3.so
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```
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## 4. Building and Installation
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- Build sample code under openvino toolkit
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```bash
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# root is required instead of sudo
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source /opt/intel/computer_vision_sdk/bin/setupvars.sh
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cd /opt/intel/computer_vision_sdk/deployment_tools/inference_engine/samples/
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mdkir build
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cd build
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cmake ..
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make
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```
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- Install ROS2_OpenVINO packages
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```bash
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mkdir -p ~/ros2_overlay_ws/src
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cd ~/ros2_overlay_ws/src
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git clone https://github.com/intel/ros2_openvino_toolkit
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git clone https://github.com/intel/ros2_object_msgs
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git clone https://github.com/ros-perception/vision_opencv -b ros2
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```
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- Build package
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```
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source ~/ros2_ws/install/local_setup.bash
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cd ~/ros2_overlay_ws
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colcon build --symlink-install
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```
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## 5. Running the Demo
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1. Preparation
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- copy label files (excute _once_)
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```bash
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sudo cp ~/ros2_overlay_ws/src/ros2_openvino/data/labels/emotions-recognition/FP32/emotions-recognition-retail-0003.labels /opt/intel/computer_vision_sdk/deployment_tools/intel_models/emotions-recognition-retail-0003/FP32
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```
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- set OpenVINO toolkit ENV
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```bash
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source /opt/intel/computer_vision_sdk/bin/setupvars.sh
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```
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- set ENV LD_LIBRARY_PATH
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```bash
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export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/intel/computer_vision_sdk/deployment_tools/inference_engine/samples/build/intel64/Release/lib
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```
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2. run sample code with command-line arguments for <b>image or video</b> detection
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```bash
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ros2 run dynamic_vino_sample dynamic_vino_sample -m <model_path_for_face_detection> -m_em <model_path_for_emotion_detection> -m_ag <model_path_for_age_and_gender_detection> -m-hp <model_path_for_headpose_detection> -i <input_type> -i_path <file_directory> -d <device> -d_em <device> -d_ag <device> -d_hp <device>
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```
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Options for &lt;input_type&gt;: _Image_ or _Video_.
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Options for &lt;device&gt;: _CPU_ or _GPU_. Default is _CPU_.
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For example,
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```bash
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ros2 run dynamic_vino_sample dynamic_vino_sample -m /opt/intel/computer_vision_sdk/deployment_tools/intel_models/face-detection-adas-0001/FP32/face-detection-adas-0001.xml -m_em /opt/intel/computer_vision_sdk/deployment_tools/intel_models/emotions-recognition-retail-0003/FP32/emotions-recognition-retail-0003.xml -m_ag /opt/intel/computer_vision_sdk/deployment_tools/intel_models/age-gender-recognition-retail-0013/FP32/age-gender-recognition-retail-0013.xml -m-hp /opt/intel/computer_vision_sdk/deployment_tools/intel_models/head-pose-estimation-adas-0001/FP32/head-pose-estimation-adas-0001.xml -i Image -i_path <file_directory> -d CPU -d_em CPU -d_ag GPU -d_hp GPU
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```
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3. run sample code with command-line arguments for <b>video stream from camera</b> detection
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```bash
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ros2 run dynamic_vino_sample dynamic_vino_sample -m <model_path_for_face_detection> -m_em <model_path_for_emotion_detection> -m_ag <model_path_for_age_and_gender_detection> -m-hp <model_path_for_headpose_detection> -i <input_type> -d <device> -d_em <device> -d_ag <device> -d_hp <device>
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```
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Options for &lt;input_type&gt;: _StandardCamera_ or _RealSenseCamera_. Default is _StandardCamera_.
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Options for &lt;device&gt;: _CPU_ or _GPU_. Default is _CPU_.
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For example,
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```bash
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ros2 run dynamic_vino_sample dynamic_vino_sample -m /opt/intel/computer_vision_sdk/deployment_tools/intel_models/face-detection-adas-0001/FP32/face-detection-adas-0001.xml -m_em /opt/intel/computer_vision_sdk/deployment_tools/intel_models/emotions-recognition-retail-0003/FP32/emotions-recognition-retail-0003.xml -m_ag /opt/intel/computer_vision_sdk/deployment_tools/intel_models/age-gender-recognition-retail-0013/FP32/age-gender-recognition-retail-0013.xml -m-hp /opt/intel/computer_vision_sdk/deployment_tools/intel_models/head-pose-estimation-adas-0001/FP32/head-pose-estimation-adas-0001.xml -i StandardCamera -d CPU -d_em CPU -d_ag GPU -d_hp GPU
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```
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4. run sample code with parameters extracted from [yaml](https://github.intel.com/otc-rse/ros2_openvino/blob/master/vino_param_lib/param/pipeline.yaml).
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```bash
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ros2 run dynamic_vino_sample pipeline_with_params
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```
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## 6. Interfaces
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### 6.1 Topic
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- Face Detection:
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```/openvino_toolkit/faces```([object_msgs:msg:ObjectsInBoxes](https://github.com/intel/ros2_object_msgs/blob/master/msg/ObjectsInBoxes.msg))
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- Emotion Detection:
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```/openvino_toolkit/emotions```([people_msgs:msg:EmotionsStamped](https://github.intel.com/otc-rse/ros2_openvino/blob/master/people_msgs/msg/EmotionsStamped.msg))
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- Age and Gender Detection:
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```/openvino_toolkit/age_genders```([people_msgs:msg:AgeGenderStamped](https://github.intel.com/otc-rse/ros2_openvino/blob/master/people_msgs/msg/AgeGenderStamped.msg))
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- Head Pose:
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```/openvino_toolkit/headposes```([people_msgs:msg:HeadPoseStamped](https://github.intel.com/otc-rse/ros2_openvino/blob/master/people_msgs/msg/HeadPoseStamped.msg))
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## 7. Known Issues
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- Parameters "-m_ag, -m_hp, -m_em" should be optional, but samples throw exception without them.
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- Parameters "-n_ag, -n_hp, -n_em" doesn't work. The maximum number of face/age/headpose/emotion is always 16.
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- Standard USB camera can be unexpected launched with input parameter "-i RealSenseCamera".
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###### *Any security issue should be reported using process at https://01.org/security*

‎data/labels/emotions-recognition/FP32/emotions-recognition-retail-0003.labels‎

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neutual
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happy
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sad
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supprise
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anger

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