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YOLOX-ROSの紹介
Ar-Ray(GitHub: github/Ar-Ray-code)
自己紹介
• 高専専攻科2年(≒ 大学4年生)
• 2020~ ブログを書いています!(最近は月3本程度💦)
• ロボットベンチャー企業でアルバイトしています←後述
• 2021~ 高専生向けにROSの講習会を実施(ROSjp #45)
 来月までには大きな発表ができるかも…?
YOLOXとは何なのか
• YOLOXのROS2移植パッケージ
• YOLOXとは(GitHub (Megvii-BaseDetection/YOLOX)からの引用)
 アンカーフリーな物体検出プログラム
 Yolov3〜v5と比べて高性能(らしい)
 Apache 2.0 License!
 学習はPyTorchだが、実行は広く対応(TensorRT、ONNX、OpenVINO、
ncnn...)
• スター数100超え(https://github.com/Ar-Ray-code/YOLOX-ROS)
環境構築(Galactic)
• ROS2- Foxy/Galactic/Rollingに対応(Humble対応予定)
• ONNX Runtimeが最もサポートが広いのでこのバージョンを推奨
 NVIDIA GPUならGPU処理が効く (onnxruntime-gpu)
 X86-64 CPUだと結構速く実行できる
> sudo apt install ros-galactic-desktop ros-galactic-v4l2-camera
> source /opt/ros/galactic/setup.bash
> pip3 install yolox # Jetsonは依存pkgの手動インストールが必要
> git clone https://github.com/Ar-Ray-code/YOLOX-ROS.git --recursive ~/ros2_ws/src/YOLOX-ROS
> cd ~/ros2_ws/
> colcon build --symlink-install# Jetsonは依存pkgの手動インストールが必要
> source ~/ros2_ws/install/setup.bash
> ros2 launch yolox_ros_py yolox_nano_onnx.launch.py video_device:=/dev/video0
【構築】
【実行】
YOLOX-ROSのデモプログラム
Webカメラ
(v4l2-camera)
画像
(image-publisher)
動画
(YouTube-publisher)
YOLOX-ROSのデモプログラム
Gazebo
Unity
(RenderTexture2ROS2Image)
採用事例
HarvestX株式会社
・植物工場向けの授粉・収穫ロボットの開発
・イチゴや花の検出部分のYOLOXへの乗り換え
イチゴ検出の様子
(アルゴリズム変更前) 植物工場の環境
速度編
対象デバイス
YOLOX-ROSの対応状況
Python3
デモプログラムの実行用
C++ (TensorRT・OpenVINO)
実装向け・高速
C++の実装は全てComposableNodeです
• C++ TensorRTを使用(ROS2-Galactic)
• Jetsonは以下の3種類を使用
 Jetson Nano (4GB)
 Jetson AGX Xavier (32GB)
 Jetson AGX Orin (32GB)※
 Jetson AGX Orinのみ最新のr34.1
• 開始後10秒後から15秒付近のfps値を参考に比較
 開始直後はfpsが落ちる傾向がある
• 比較用にdarknet_ros_fp16の実行速度も掲載
 darknet_ros_fp16は最新のdarknet-YOLOv4の動作確認用ROS2パッケージ
 https://github.com/Ar-Ray-code/darknet_ros_fp16
速度(Jetson編)
速度(Jetson編)
速度(Jetson編)
2.8倍
2.7倍
140fps ?
130fps ?
90fps ?
Jetson OrinのAI演算性能はRTX2080Ti(Desktop)とほぼ同じ
(TensorRTなしの場合)
現時点のTensorRTはJetson Orinに
最適化されていない
速度(その他)
おわりに
• ROS2初めてでも、まず使ってみてください!
• YOLOX-ROSにissueやプルリクあれば送ってください❗

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YOLOX-ROSの紹介.pdf