https://github.com/shaadclt/vehicle-tracking-counting-yolov8

This Jupyter notebook project uses YOLOv8 for vehicle tracking and implements a line crossing detection algorithm. The system counts vehicles that cross a specified line in a video, annotates the frames, and generates an output video with visualizations.
https://github.com/shaadclt/vehicle-tracking-counting-yolov8

Last synced: 6 months ago
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This Jupyter notebook project uses YOLOv8 for vehicle tracking and implements a line crossing detection algorithm. The system counts vehicles that cross a specified line in a video, annotates the frames, and generates an output video with visualizations.

• Host: GitHub
• URL: https://github.com/shaadclt/vehicle-tracking-counting-yolov8
• Owner: shaadclt
• Created: 2024-01-02T16:07:42.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2024-01-02T17:33:26.000Z (almost 2 years ago)
• Last Synced: 2025-04-09T17:01:55.454Z (6 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 2.63 MB
• Stars: 4
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Vehicle Tracking and Counting with YOLOv8

![yolo](https://github.com/shaadclt/Vehicle-Counter-YOLOv8/assets/98437584/4d37dfee-9711-4722-9ace-a15fb3e20553)

## Overview

This Jupyter notebook project uses YOLOv8 for vehicle tracking and implements a line crossing detection algorithm. The system counts vehicles that cross a specified line in a video, annotates the frames, and generates an output video with visualizations.

## Dependencies

- OpenCV

- Ultralytics YOLO

- supervision

## Setup

1. Clone the repository:

   ```bash

   git clone https://github.com/shaadclt/Vehicle-Counter-YOLOv8.git

   cd Vehicle-Counter-YOLOv8

   ```

## Usage

1. Open the Jupyter notebook:

  ```bash

  jupyter notebook

  ```

2. Run the **'vehicle_counter.ipynb'** notebook.

## Configuration

- Adjust line coordinates: **'START'** and **'END'** in the notebook.

- Configure YOLOv8 model parameters as needed.

## Results

The output video output_single_line.mp4 will be generated with annotated frames showing object tracks and the count of objects that crossed the line.

## Acknowledgements

- This project uses the YOLOv8 model from Ultralytics.