Malek-Messaoudi/Multiple_Car_Detection

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