# yolov8-object-tracking
**Repository Path**: o1o2oxxx/yolov8-object-tracking
## Basic Information
- **Project Name**: yolov8-object-tracking
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: AGPL-3.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-12-06
- **Last Updated**: 2025-12-06
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
# yolov8-object-tracking
This is compatible only with `ultralytics==8.0.0`. However, I highly recommend using the latest version of the Ultralytics package and referring to the official Ultralytics codebase here: [GitHub Repository](https://github.com/ultralytics/ultralytics/).
[](https://muhammadrizwanmunawar.medium.com/train-yolov8-on-custom-data-6d28cd348262)
### Steps to run Code
- Clone the repository
```bash
https://github.com/RizwanMunawar/yolov8-object-tracking.git
```
- Move to the cloned folder
```bash
cd yolov8-object-tracking
```
- Install the ultralytics package
```bash
pip install ultralytics==8.0.0
```
- Do tracking with the mentioned command below
```bash
#video file
python yolo\v8\detect\detect_and_trk.py model=yolov8s.pt source="test.mp4" show=True
#imagefile
python yolo\v8\detect\detect_and_trk.py model=yolov8m.pt source="path to image"
#Webcam
python yolo\v8\detect\detect_and_trk.py model=yolov8m.pt source=0 show=True
#External Camera
python yolo\v8\detect\detect_and_trk.py model=yolov8m.pt source=1 show=True
```
- Output file will be created in the `runs/detect/train` with the original filename
### Results 📊
| YOLOv8s Object Tracking |
YOLOv8m Object Tracking |
 |
 |
### References 🔗
- 🔗 https://github.com/ultralytics/ultralytics
- 🔗 https://github.com/abewley/sort
- 🔗 https://docs.ultralytics.com/
**Some of my articles/research papers | Computer vision awesome resources for learning | How do I appear to the world? 🚀**
| Article Title & Link | Published Date |
|-----------------------|----------------|
| [Ultralytics YOLO11: Object Detection and Instance Segmentation🤯](https://muhammadrizwanmunawar.medium.com/ultralytics-yolo11-object-detection-and-instance-segmentation-88ef0239a811) |  |
| [Parking Management using Ultralytics YOLO11](https://muhammadrizwanmunawar.medium.com/parking-management-using-ultralytics-yolo11-fba4c6bc62bc) |  |
| [My 🖐️Computer Vision Hobby Projects that Yielded Earnings](https://muhammadrizwanmunawar.medium.com/my-️computer-vision-hobby-projects-that-yielded-earnings-7923c9b9eead) |  |
| [Best Resources to Learn Computer Vision](https://muhammadrizwanmunawar.medium.com/best-resources-to-learn-computer-vision-311352ed0833) |  |
| [Roadmap for Computer Vision Engineer](https://medium.com/augmented-startups/roadmap-for-computer-vision-engineer-45167b94518c) |  |
| [How did I spend 2022 in the Computer Vision Field](https://www.linkedin.com/pulse/how-did-i-spend-2022-computer-vision-field-muhammad-rizwan-munawar) |  |
| [Domain Feature Mapping with YOLOv7 for Automated Edge-Based Pallet Racking Inspections](https://www.mdpi.com/1424-8220/22/18/6927) |  |
| [Exudate Regeneration for Automated Exudate Detection in Retinal Fundus Images](https://ieeexplore.ieee.org/document/9885192) |  |
| [Feature Mapping for Rice Leaf Defect Detection Based on a Custom Convolutional Architecture](https://www.mdpi.com/2304-8158/11/23/3914) |  |
| [Yolov5, Yolo-x, Yolo-r, Yolov7 Performance Comparison: A Survey](https://aircconline.com/csit/papers/vol12/csit121602.pdf) |  |
| [Explainable AI in Drug Sensitivity Prediction on Cancer Cell Lines](https://ieeexplore.ieee.org/document/9922931) |  |
| [Train YOLOv8 on Custom Data](https://medium.com/augmented-startups/train-yolov8-on-custom-data-6d28cd348262) |  |
**More Information**
For more details, you can reach out to me on [Medium](https://muhammadrizwanmunawar.medium.com/) or connect with me on [LinkedIn](https://www.linkedin.com/in/muhammadrizwanmunawar/)