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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
YOLOv8 Object Tracking Using PyTorch, OpenCV and Ultralytics
| Date | Stars |
|---|---|
| 2026-07-24 | 371 |
| 2026-07-25 | 371 |
| 2026-07-28 | 371 |
| 2026-07-30 | 371 |
| 2026-08-06 | 371 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# 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 📊
<table>
<tr>
<td>YOLOv8s Object Tracking</td>
<td>YOLOv8m Object Tracking</td>
</tr>
<tr>
<td><img src="https://user-images.githubusercontent.com/62513924/211671576-7d39829a-f8f5-4e25-b30a-530548c11a24.png"></td>
<td><img src="https://user-images.githubusercontent.com/62513924/211672010-7415ef8b-7941-4545-8434-377d94675299.png"></td>
</tr>
</table>
### Star History
[](https://www.star-history.com/#RizwanMunawar/yolov8-object-tracking&type=date&legend=top-left)
### 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.orExcerpt of 5,188 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:cfc40c6604058148, topic:computer-vision, topic:object-detection, topic:object-tracking