Smart Parking System

The Smart Parking System is an end-to-end solution that leverages Computer Vision and Machine Learning to automate the detection of vacant parking spaces in real-time. By analyzing video feeds, the system identifies available spots, manages reservations, and provides a dynamic interface for both operators and users. Key Features Automated Spot Detection: Uses a trained Machine Learning model (model.p) and image processing techniques to classify parking slots as "Empty" or "Occupied". Real-time Video Processing: Processes MP4/AVI files and applies coordinate-based masking to monitor hundreds of parking spots simultaneously. Integrated Reservation System: Features a logic-driven booking engine that tracks "Detected Availability" versus "Reserved Spots" to provide an accurate "Final Availability" count. Interactive Dashboard: A professional Streamlit-based web interface that displays live metrics, annotated visual results, and administrative controls. Optimized Performance: Includes adjustable sample rates to balance processing accuracy with computational speed. Technical Architecture Backend: Built with FastAPI to handle asynchronous requests for detection, reservations, and status updates. Frontend: Developed using Streamlit for a responsive, user-friendly data visualization experience. AI/ML Core: Utilizes Scikit-learn for classification and OpenCV for sophisticated frame manipulation and bounding box rendering. Data Handling: Uses NumPy for numerical arrays and Pillow for high-quality image encoding/decoding. Tech Stack Languages: Python. Libraries: FastAPI, Streamlit, OpenCV, Scikit-learn, Scikit-image, NumPy, Pickle. Deployment: Capable of running locally or as a Hugging Face Space. Would you like me to create a professional LinkedIn post based on this description to help you showcase your work?