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https://github.com/vivaldini/yolov6-uav
This repository contains a ROS noetic package for YOLOv6 to recognize objects from UAV and provide their positions.
https://github.com/vivaldini/yolov6-uav
Last synced: 12 days ago
JSON representation
This repository contains a ROS noetic package for YOLOv6 to recognize objects from UAV and provide their positions.
- Host: GitHub
- URL: https://github.com/vivaldini/yolov6-uav
- Owner: vivaldini
- License: gpl-3.0
- Created: 2023-03-31T13:27:56.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2023-03-31T14:03:47.000Z (about 1 year ago)
- Last Synced: 2024-02-29T06:34:27.420Z (4 months ago)
- Language: HTML
- Size: 2.46 MB
- Stars: 3
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Lists
- awesome-yolo-object-detection - vivaldini/yolov6-uav - uav?style=social"/> : This repository contains a ROS noetic package for YOLOv6 to recognize objects from UAV and provide their positions. (Other Versions of YOLO)
README
# Yolo v6 Object Detection from UAV Images
This repository contains a ROS noetic package for YOLOv6 to recognize objects from UAV and provide their positions.
Based on ROS Package for Yolov6 developed by @lukazso
This package works together with MRS System, it is a easy to simulate UAV.
## Build Status
| Component | 20.04 |
| ------------------- | ------------------- |
| RMA | |
Features
- UAV
- Bluefox or Real-sense D-435
- Odometry
## Dependencies and Requirements
### Step 1 - Instal MRS System
Follow the instructions [here](https://github.com/ctu-mrs/mrs_uav_system#installation) (on Installation topic) to install MRS System or use the commands:
```bash
cd /tmp
echo '
GIT_PATH=~/git
mkdir -p $GIT_PATH
cd $GIT_PATH
sudo apt-get -y install git
git clone https://github.com/ctu-mrs/mrs_uav_system
cd mrs_uav_system
git checkout master
git pull
./install.sh -g $GIT_PATH
source ~/.bashrc' > clone.sh && source clone.sh
```
### Step 2 - Environment
Clone this repository into your catkin workspace, and looking for the setup and install dependencies:
```bash
cd ~/Your_worspace/src
git clone https://github.com/JorgelHenri/ocean_trash_world
```
### Step 3 - Yolo
Following ROS packages are required:
- [vision_msgs](http://wiki.ros.org/vision_msgs)
```bash
sudo apt-get install ros-noetic-vision-msgs
roscd vision_msgs
```
- [geometry_msgs](http://wiki.ros.org/geometry_msgs)
```bash
sudo apt-get install ros-noetic-geometry-msgs
roscd geometry_msgs
```
Clone this repository into your catkin workspace:
```bash
cd ~/Your_worspace/src
git clone https://github.com/vivaldini/yolo-uav
```
The Python requirements are listed in the requirements.txt. You can simply install them as
```bash
cd ~/Your_worspace/src/yolov6-uav
pip install -r requirements.txt
```
Build the package
```bash
cd ~/Your_worspace/src/yolov6-uav
catkin build
```
### Using the simulator and Testing the Yolo
- Parameters configuration
In the file ~/Your_worspace/ocean_trash_world/offshore_uav_pack/start/session.yml, line 21 change the world environment "ballontrash.launch" to "trash.launch", and if necessary the camera.
In the file ~/Your_worspace/yolov6-uav/src/detect.py line 150, change it for your worspace and choose the weigths for your trainning models. For the garbage set as yolo_v6_simulated.pt
Before you launch the yolov6.launch node, adjust the camera and YOLOv6 weights topics in the launch file according to the sensors and topics that you are using.
- Run the simulator
This scenario opens a sea area containing some garbage and spawn a UAV.
```bash
cd ~/Your_worspace/src/ocean_trash_world/offshore_uav_pack/start
$ ./start.sh
```
In the Gazebo to start the simulation press the button ***Play
- Starting the Yolo
Copy the files of trainning available in this [drive](https://drive.google.com/drive/u/0/folders/1ulBtT66721qDCoDw9gpyJTilHD3LmQww) inside the folder "/yolov6-uav/launch/yolo_weigths"
```bash
roslaunch yolov6-uav yolov6.launch
```
Each time a new image is received it is then fed into YOLOv6.
***Notes
- The detections are published using the [vision_msgs/Detection2DArray](http://docs.ros.org/en/api/vision_msgs/html/msg/Detection2DArray.html) message type.
- The detections will be published under `/yolov6/out_topic`.
- If you set the `visualize` parameter to `true`, the detections will be drawn into
the image, which is then published under `/yolov6/yolov6/visualization`.
- Move the UAV
In the terminal where you executed the environment, go to the "Status tab" and press
-- "h" to appear the command control of the UAV, and
-- "Shift + R" to operate the UAV manually.
***Note: Move the UAV to view the garbage.
- Visualization
```bash
rqt_image_view
topic /yolo6/yolov6/visualization
```
### Extra 1: Ways to stop the simulation
Press “CTRL + a” and after “k” in the prompt.
If something remains open:
```bash
alias killg='killall gzclient && killall gzserver && killall rosmaster'
killall px4
tmux kill-server
```
## Support
For support send email [email protected] and [email protected]