🛣️ Road Lane Detection Using Python and OpenCV

This project implements a real-time lane detection system using Python, OpenCV, and NumPy. It processes video frames to detect road lanes using edge detection, region masking, and Hough line transformation. Ideal for self-driving car simulations, computer vision practice, or academic projects.

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📁 Project Structure

Road-Lane-Detection/

├── input.mp4 # Sample road video for lane detection 
├── RoadLaneDetectionUsingPythonAndOpenCV.py # Main Python script for lane detection
├── venv/ # Virtual environment folder
└── README.md # Project overview and instructions

🚀 How to Run

🔧 Step-by-Step Setup

1. Clone this repository
2. Create a virtual environment:

bash python -m venv venv

Activate the virtual environment:

On Windows: .\venv\Scripts\activate

On Mac/Linux: source venv/bin/activate

Install required libraries:

pip install opencv-python numpy

Run the script:

bash python solution.py Press q to quit the video window.

📦 Required Libraries

Library Purpose opencv-python Image processing and video I/O numpy Array operations and math

Install all with:

bash pip install opencv-python numpy

📹 What It Does

Converts each video frame to grayscale

Applies Gaussian blur and Canny edge detection

Masks the region of interest (road area)

Detects lane lines using Hough Transform

Averages and visualizes left/right lane boundaries

Overlays detected lanes on the original video

Output ====>

🛠️ Technologies Used

Python

OpenCV

NumPy

VS Code (for development)