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https://github.com/alexandrefch/ros-yolov7

ROS package that implement a light yolov7 version in ros node style that allow user to run inference easely.
https://github.com/alexandrefch/ros-yolov7

noetic object-detection opencv python python3 ros ros-noetic ros-package torch yolov7

Last synced: 10 days ago
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ROS package that implement a light yolov7 version in ros node style that allow user to run inference easely.

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README

        

# ROS package for official YOLOv7

![Ros](https://img.shields.io/badge/Ros-Noetic-informational?style=for-the-badge&logo=ROS)
![Python](https://img.shields.io/badge/Python-3.8-informational?style=for-the-badge&logo=Python&logoColor=FFFFFF)

> **Note**

> This ROS noetic package is an implementation of the [official yolov7](https://github.com/WongKinYiu/yolov7), most credit goes to them.


Rviz

**Fig.1** RViz view of detection projection from a Gazebo Simulation

## :rocket: Installation from source

First you need to download all required source, like the [ros-image-transport-py](https://github.com/alexandrefch/ros-image-transport-py) package, that manage automaticly image stream.
Moreover you might need some python package like [OpenCV](https://github.com/opencv/opencv), you can install them by simply execute `pip install opencv-python` or better compile from source for GPU.

### :gear: Clone and Compile

Clone thoose two packages inside the `src` directory of your catkin workspace.

```shell
git clone https://github.com/alexandrefch/ros-yolov7.git
git clone https://github.com/alexandrefch/ros-image-transport-py.git
```

Now you can compile them using your catkin tool (`catkin_make`, `catkin_build` ...).

## :clipboard: Configuration

### Weight

You can download some of the the YOLOv7 weights from the [official repository](https://github.com/WongKinYiu/yolov7) or use your own.

### Classes

Classes should be stored inside a simple text file where each single line represent a classe, like in the exemple below.

```
car
bus
person
bike
motorcycle
traffic light
truck
person
```

### Launch file

```xml






















```

## :black_nib: Citation

If you use this package in a scientific way or public way, don't forget to mention the official Yolov7 paper, and star their work on their [github repo](https://github.com/WongKinYiu/yolov7).

```
@article{wang2022yolov7,
title={{YOLOv7}: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors},
author={Wang, Chien-Yao and Bochkovskiy, Alexey and Liao, Hong-Yuan Mark},
journal={arXiv preprint arXiv:2207.02696},
year={2022}
}
```