YOLOX-ROS
YOLOX+ROS2 Foxy
Supported List
| Base | ROS1 C++ | ROS1 Python | ROS2 C++ | ROS2 Python |
|---|---|---|---|---|
| CPU |
|
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| CUDA |
|
|||
| CUDA (FP16) |
|
|||
| TensorRT (CUDA) |
|
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| OpenVINO |
|
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| MegEngine | ||||
| ncnn |
Installation & Demo
Python (PyTorch)
Requirements
- ROS2 Foxy
- OpenCV 4
- Python 3.8 (Ubuntu 20.04 Default)
- YOLOX Depends
- bbox_ex_msgs
Installation
Install the dependent packages based on all tutorials.
STEP 1 : YOLOX Quick-start
git clone https://github.com/Megvii-BaseDetection/YOLOX
cd YOLOX
pip3 install -U pip && pip3 install -r requirements.txt
pip3 install -v -e . # or python3 setup.py develop
pip3 install cython; pip3 install 'git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI'
STEP 2 : Install YOLOX-ROS
source /opt/ros/foxy/setup.bash
sudo apt install ros-foxy-v4l2-camera
git clone --recursive https://github.com/Ar-Ray-code/yolox_ros.git ~/ros2_ws/src/yolox_ros/
cd ~/ros2_ws
colcon build --symlink-install # weights files will be installed automatically.
(Step 2) Using CUDA
If you have NVIDIA Graphics, you can run YOLOX-ROS on GPU.
Additional installing lists
- NVIDIA Graphics Driver
- CUDA toolkit (11.0)
- torch+cuda
Step3 : Demo
Connect your web camera.
source /opt/ros/foxy/setup.bash
source ~/ros2_ws/install/local_setup.bash
ros2 launch yolox_ros_py yolox_s_cpu.launch.py
# ros2 launch yolox_ros_py yolox_s.launch.py # <- GPU
C++ (OpenVINO)
- Docker Images is Released.
Requirements
- ROS2 Foxy
- OpenCV 4
- OpenVINO
- bbox_ex_msgs
Step1 : Installation
source /opt/ros/foxy/setup.bash
sudo apt install ros-foxy-v4l2-camera
source /opt/intel/openvino_2021/bin/setupvars.sh
cd ~/ros2_ws/src
git clone --recursive https://github.com/Ar-Ray-code/YOLOX-ROS.git
# Download onnx file and Convert to IR format.
./YOLOX-ROS/weights/openvino/install.bash yolox_nano
Step2 : Demo
Connect your web camera.
source /opt/ros/foxy/setup.bash
source ~/ros2_ws/install/local_setup.bash
ros2 launch yolox_ros_cpp yolox_openvino.launch.py
C++ (TensorRT)
Docker Images is Released.
Topic
Subscribe
- image_raw (
sensor_msgs/Image)
Publish
-
yolox/image_raw : Resized image (
sensor_msgs/Image) -
yololx/bounding_boxes : Output BoundingBoxes like darknet_ros_msgs (
bboxes_ex_msgs/BoundingBoxes)※ If you want to use
darknet_ros_msgs, replacebboxes_ex_msgswithdarknet_ros_msgs.
Parameters
- Check launch files.
Composition
- Supports C++ only.
Reference
@article{yolox2021,
title={YOLOX: Exceeding YOLO Series in 2021},
author={Ge, Zheng and Liu, Songtao and Wang, Feng and Li, Zeming and Sun, Jian},
journal={arXiv preprint arXiv:2107.08430},
year={2021}
}
Contributors
About writer
- Ar-Ray : Japanese student.
- Blog (Japanese) : https://ar-ray.hatenablog.com/
- Twitter : https://twitter.com/Ray255Ar
l
I've tried using the Dockerfile for Jetson Nano found in the yolox_ros_cpp folder, but the build fails at the 19th and 21st build commands (installing the onnxoptimizer from git and installing YOLOX from git) - if you have this image hosted on Dockerhub, I should be able to test and see if that will work by just downloading the built image.
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