Watch Vehicle Parking Detection using Python | OpenCV + Deep Learning | AI Project + Source Code Video Tutorial

🚗 Welcome to this hands-on AI & Computer Vision Project — Vehicle Parking Detection using Python, OpenCV, and Deep Learning! In this step-by-step video, you’ll learn how to detect and track available parking spaces automatically using AI-based image processing and computer vision techniques. Perfect for students, developers, and researchers looking for an AI project with real-world applications. 🧠 What You’ll Learn in This Project: ✅ Detect occupied and free parking slots in real time ✅ Implement deep learning-based object detection models ✅ Integrate OpenCV for image and video processing ✅ Build a complete AI-powered parking management system ✅ Visualize parking occupancy data using Python ⚙️ Technologies & Tools Used: 🔹 Python 🐍 🔹 OpenCV (Computer Vision) 🔹 Deep Learning (TensorFlow / Keras) 🔹 YOLO / CNN Models 🔹 Real-Time Video Processing 🕒 Vehicle Parking Management System Project Timeline 00:00 - 01:30 → Introduction & Project Overview (Traffic Reduction, Space Counting) 01:31 - 03:00 → Folder Structure & Key Project Files (Media, Images, Static, Templates) 03:01 - 04:30 → Required Libraries & Packages (Flask, OpenCV, NumPy, Ultralytics, CV Zone) 04:31 - 06:00 → Initial Setup: Importing Libraries, Loading Pre-trained Yolo V1 Model 06:01 - 07:30 → Car Parking Polygon Coordinates & Roboflow Setup for Drawing Polygons 07:31 - 09:00 → User Management: Registration, Login, and Data Storage in JSON Files 09:01 - 10:30 → Flask API Setup: Index, Register, Login, About, and Submit Contact 10:31 - 12:00 → Video Input Handling & Polygon Selection for Different Parking Lots 12:01 - 13:30 → Object Detection: Bounding Boxes, Confidence Scores, and Class Filtering 13:31 - 15:00 → Tracking Vehicles: Unique ID Assignment and Detection in Polygon Zones 15:01 - 16:30 → Counting Occupied and Available Parking Spaces 16:31 - 18:00 → Rendering Output: Drawing Polygons, Occupied Color Codes (Red/Green) 18:01 - 19:30 → Displaying Detection Results & Information Overlays (Total, Occupied, Available) 19:31 - 21:00 → Running Video Inference & Handling Frame Captures 21:01 - 22:30 → Saving Frame Images and Exporting Contact/User Data 22:31 - 24:00 → Completing Inference Execution & Flask Application Running (Ports, IP) 24:01 - 25:48 → Demo Walkthrough: Login, Video Submission, Live Parking Count Updates & Conclusion 💡 Why This Project? Smart Parking is a crucial component of modern AI-powered smart cities. Learn how vehicle parking detection systems improve efficiency, reduce congestion, and optimize parking management using the power of Artificial Intelligence & Deep Learning. 🎓 Want this full project (source code + dataset + documentation) AND 21 more Computer Vision projects with certificate? 👉 Visit here → [ https://www.udemy.com/course/computer-vision-mastery-real-time-projects-opencv-python-ai-yolo/?referralCode=C219F7481A635FD9196A ]] #VehicleParkingDetection #aiprojects #pythonprojects #deeplearning #opencv #computervision #smartparking #aidetection #machinelearning #sourcecode #scratchlearn