## Ultralytics YOLOv8 Example Applications This repository features a collection of real-world applications and walkthroughs, provided as either Python files or notebooks. Explore the examples below to see how YOLOv8 can be integrated into various applications. ### Ultralytics YOLO Example Applications | Title | Format | Contributor | | -------------------------------------------------------------------------------------------------------------- | ------------------ | --------------------------------------------------- | | [YOLO ONNX Detection Inference with C++](./YOLOv8-CPP-Inference) | C++/ONNX | [Justas Bartnykas](https://github.com/JustasBart) | | [YOLO OpenCV ONNX Detection Python](./YOLOv8-OpenCV-ONNX-Python) | OpenCV/Python/ONNX | [Farid Inawan](https://github.com/frdteknikelektro) | | [YOLO .Net ONNX Detection C#](https://www.nuget.org/packages/Yolov8.Net) | C# .Net | [Samuel Stainback](https://github.com/sstainba) | | [YOLOv8 on NVIDIA Jetson(TensorRT and DeepStream)](https://wiki.seeedstudio.com/YOLOv8-DeepStream-TRT-Jetson/) | Python | [Lakshantha](https://github.com/lakshanthad) | ### How to Contribute We welcome contributions from the community in the form of examples, applications, and guides. To contribute, please follow these steps: 1. Create a pull request (PR) with the `[Example]` prefix in the title, adding your project folder to the `examples/` directory in the repository. 1. Ensure that your project meets the following criteria: - Utilizes the `ultralytics` package. - Includes a `README.md` file with instructions on how to run the project. - Avoids adding large assets or dependencies unless absolutely necessary. - The contributor is expected to provide support for issues related to their examples. If you have any questions or concerns about these requirements, please submit a PR, and we will be more than happy to guide you.