Lane Detection

This project implements a basic lane detection algorithm using computer vision techniques. The current method works well for straight lanes but has difficulty predicting lanes on curves. A future version will address this limitation.

Features

• 🚗 Detects lanes on roads using image processing.
• 📏 Works well for straight roads.
• 🖥 Uses OpenCV and NumPy for image processing.

❌ Limitations

• The current implementation struggles with curved lanes.
• Performance may vary under different lighting and weather conditions.

📦 Requirements

Ensure you have the following installed before running the code:

• Python 3.x 🐍
• OpenCV 👀
• NumPy 🔢
• Jupyter Notebook 📓 (if running the .ipynb file)

Install dependencies using:

pip install opencv-python numpy jupyter

🚀 Running the Project

1. Clone the repository or download the notebook.
2. Open the LaneDetection.ipynb file in Jupyter Notebook.
3. Run the cells step by step to process the input images or video.
4. View the detected lanes on the processed output.

🖼 Output Example

🔜 Future Improvements

• ✅ Improved lane detection for curved roads.
• 🧠 Integration with deep learning models for better accuracy.
• 🎥 Real-time lane detection using video input.

Stay tuned for the next version with enhanced capabilities! 🚀