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:

pip install ultralytics opencv-python torch torchvision

Model Files

Multiple_car_detection.pt.pt - Best model from training

Example

Citation

If you use this model, please cite:

@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