# Multiple Car & Person Detection — YOLOv8x (Fine-Tuned)

This repository provides a fine-tuned YOLOv8x model for real-time detection of multiple cars and persons in images and videos.  
It is designed for applications such as traffic monitoring, smart-city analytics, pedestrian awareness, and video surveillance.

## Key Features

- Detects multiple objects per frame:
  - car
  - person
- Real-time performance depending on hardware
- High detection accuracy using YOLOv8x
- Works on both images and videos
- Built with Ultralytics YOLOv8

## Model Details

| Property | Value |
|----------|-------|
| Base Architecture | YOLOv8x |
| Task | Object Detection |
| Framework | Ultralytics |
| Detected Classes | person, car |
| Input | Images / Video |
| Output | Bounding boxes + confidence scores |

This model was fine-tuned on datasets containing vehicles and pedestrians in urban environments, optimized for scenarios where multiple vehicles and people appear in the same scene.

## Installation

Install the required dependencies:

```bash
pip install ultralytics opencv-python torch torchvision
```


## Model Files

Multiple_car_detection.pt.pt - Best model from training


## Example 

![image](https://cdn-uploads.huggingface.co/production/uploads/67bc31088cf27f32cbcf927f/-dofHf6uErv0FzIKmBhrq.png)


## Citation

If you use this model, please cite:

```bibtex
@misc{multiple-car-detection-2025,
  author       = {Malek Messaoudi and Yassine Mhirsi},
  title        = {Multiple Car and Persons Detection},
  year         = {2025},
  publisher    = {Hugging Face},
}

```


## license

license: mit