Car Counting Project

This project involves detecting and counting vehicles (cars, trucks, buses, and motorbikes) crossing a defined line in a video. The counting is done using a YOLO (You Only Look Once) model for object detection, and the results are tracked using the SORT (Simple Online and Realtime Tracking) algorithm. Each time a vehicle crosses the line, the count is incremented and stored in a MySQL database.

demo

Features

• Vehicle detection using YOLOv8
• Vehicle tracking using SORT
• Counting vehicles crossing a line
• Storing counts in a MySQL database

Prerequisites

• Python 3.x
• MySQL server

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/car_counting_project.git
   cd car_counting_project

2. Install the required Python packages:

   pip install -r requirements.txt

3. Set up the MySQL database:

   • Create a database named car_counting:

     CREATE DATABASE car_counting;

   • Create the car_counts table:

     USE car_counting;
     CREATE TABLE car_counts (
         id INT AUTO_INCREMENT PRIMARY KEY,
         timestamp TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
         count INT
     );

Usage

1. Ensure the MySQL server is running and you have created the database and table as described above.

2. Edit the database.py file to include your MySQL username and password:

   conn = mysql.connector.connect(
       host="localhost",
       user="your_username",  # replace with your MySQL username
       password="your_password",  # replace with your MySQL password
       database="car_counting"  # replace with your database name
   )

3. Run the main script:

   python main.py

File Description

• main.py: Main script for detecting and tracking vehicles, and updating the count in the database.
• database.py: Script for connecting to the MySQL database and inserting count records.
• mask.png: Mask image used to define the region of interest in the video.
• graphics.png: Graphics overlay for the video.
• requirements.txt: List of required Python packages.
• Videos/: Directory containing the input video file (cars.mp4).
• Yolo-Weights/: Directory containing the YOLOv8 weights file (yolov8l.pt).

Contributing

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes.
4. Commit your changes (git commit -am 'Add new feature').
5. Push to the branch (git push origin feature-branch).
6. Create a new Pull Request.

License

This project is licensed under the MIT License.