Vehicle Detection and Counting using OpenCV

This project demonstrates vehicle detection and counting in a video using OpenCV and background subtraction. It processes a video file, detects moving vehicles, and counts them as they cross a defined line.

Features

• Detects moving vehicles in a video stream
• Counts vehicles as they cross a virtual line
• Uses background subtraction and contour detection
• Displays real-time video with bounding boxes and counters

Requirements

• Python 3.x
• OpenCV (opencv-python, opencv-contrib-python)
• NumPy

Installation

1. Clone this repository or download the source code.
2. Install the required Python packages:

   pip install opencv-python opencv-contrib-python numpy

Usage

1. Place your input video file as video.mp4 in the project directory (or update the filename in vehicle.py).
2. Run the script:

   python vehicle.py

3. The script will display the video with detected vehicles and a counter.

File Structure

• vehicle.py - Main script for vehicle detection and counting
• video.mp4 - Input video file (replace with your own video if needed)
• README.md - Project documentation

How it Works

• The script uses background subtraction to detect moving objects (vehicles).
• Contours are found and filtered by size to identify vehicles.
• When a vehicle's center crosses a predefined line, the counter is incremented.

Customization

• To use a different video, change the filename in vehicle.py:

  cap = cv2.VideoCapture('your_video.mp4')

• Adjust count_line_position, min_width_react, and min_height_react for different video perspectives or vehicle sizes.

Vehicle Classification

Vehicles are classified into three types based on their size:

• Small
• Medium
• Large

The script displays counters for each type in real time.

Using a Webcam

To use your computer's webcam instead of a video file, change the following line in vehicle.py:

cap = cv2.VideoCapture(0)

Exiting the Program

To exit the video window, press the Enter key.

Troubleshooting

• If the video window does not appear or only shows a black screen, check that video.mp4 exists and is a valid video file.
• For webcam issues, ensure your camera is connected and accessible.
• If you see errors or nothing happens, run the script from the terminal and check for error messages.

License

This project is for educational purposes.