For labelling you can use BBOX or anything that is friendly with YOLO
How to get started: https://drive.google.com/file/d/1L6AJDgrG3DzuDQhHzu-XnsHfL6SJSOyP/view?usp=sharing
I recommend looking into: https://github.com/AlexeyAB/darknet
BBOX for labelling: https://drive.google.com/file/d/1zy2duo2lZXkVcst5DWbmQPmHPeLnQ-Gj/view?usp=sharing
DarkMark and DarkHelp for advance labelling and augmentation: https://github.com/stephanecharette/DarkMark
- https://www.immersivelimit.com/datasets/cigarette-butts
- https://www.kaggle.com/estebanpacanchique/cigarette-butt
My dataset and weights: https://drive.google.com/drive/folders/1FedP8PPMcz5fOFMcLrToPjFqonRJZlUE
The YOLO packages have been tested under ROS Melodic and Jetpack 4.5 (Ubuntu 18.04/also headless) with a Jetson Nano Developer Kit.
In order to install darknet_ros, clone the latest version using SSH (see how to set up an SSH key) from this repository into your catkin workspace and compile the package using ROS.
!!!ALERT THIS ONLY WORKS FOR opencv3!!! Use this repo for opencv4 https://github.com/kunaltyagi/darknet_ros/tree/opencv4 but only yolov2-v3 works
cd catkin_workspace/src
git clone --recursive [email protected]:mathiebhan/darknet_ros.git
cd ../
To maximize performance, make sure to build in Release mode. You can specify the build type by setting
catkin_make -DCMAKE_BUILD_TYPE=Release
or using the Catkin Command Line Tools
catkin build darknet_ros -DCMAKE_BUILD_TYPE=Release
The weights can be downloaded from my drive. (Also the labelled images)
Put it in this file location: catkin_workspace/src/darknet_ros/darknet_ros/yolo_network_config/weights/
Source your workspace: source devel/setup.bash
cd /src/darknet_ros/darknet_ros/launch
you can then launch roslaunch darknet_ros_usb_cam.launch
Of course usb_cam is needed from ROS https://github.com/ros-drivers/usb_cam (sudo apt install ros-melodic-usb-cam) and CSI cam from https://github.com/sfalexrog/jetson_camera. For IPcamera https://github.com/alireza-hosseini/ipcamera_driver.
In order to use your own detection objects you need to provide your weights and your cfg file inside the directories:
catkin_workspace/src/darknet_ros/darknet_ros/yolo_network_config/cfg/
In addition, you need to create your config file for ROS where you define the names of the detection objects. You need to include it inside:
catkin_workspace/src/darknet_ros/darknet_ros/config/
Then in the launch file you have to point to your new config file in the line:
<rosparam command="load" ns="darknet_ros" file="$(find darknet_ros)/config/your_config_file.yaml"/>
Use the YoloDistanceMeasurement folder. For YOLOV4/tiny use folder YOLOV4. Remember to download the weights from my repo.
pip install opencv_python
pip install numpy
pip install pandas
pip install matplotlib
pip install Pillow
Then run python3 object_detection.py
Use the YoloDistanceImages folder. Remember to download the weights from my repo.
On terminal/cmd type python butt.py
