Real-Time People Counting System | YOLOv8 + Python | AI Project Tutorial with Source Code | Tamil

In this Tamil explained (தமிழில் விளக்கப்படும்) AI project tutorial, you will learn how to build a real-time People Counting & Tracking System using YOLOv8, Python, OpenCV, and Tkinter. This system detects, tracks, and counts people entering and exiting a location in real time — perfect for shopping malls, offices, events, smart buildings, and IoT-based occupancy management systems. This project is highly useful for Tamil engineering students, final-year projects, and real-world AI deployments. 🔹 What You’ll Learn ✅ Set up Python with OpenCV, YOLOv8 & Tkinter ✅ Detect & track people using YOLOv8 pre-trained weights ✅ Count entries & exits in real-time ✅ Handle occlusion, crowding & lighting challenges ✅ Build a Tkinter GUI to visualize live occupancy data 🔹 Technologies Used Python 3.x OpenCV (Real-time computer vision) YOLOv8 (Object detection) Tkinter GUI ⭐ Get Full Source Code + 21 Computer Vision Projects (For Tamil Students) 🎓 Want this complete People Counting System (source code + dataset + documentation) AND 21 more real-world Computer Vision projects with certificate? 👉 Unlock everything here → https://www.udemy.com/course/computer-vision-mastery-real-time-projects-opencv-python-ai-yolo/?couponCode=CV21PROJECTSMASTERY ✅ Full source code ✅ 21 AI + CV Projects ✅ Project reports ✅ Datasets ✅ Certificate of Completion ✅ Lifetime access 🔥 Limited-time Udemy deal active — check the price before it ends! 🧠 Core Techniques Used in This Project Computer Vision OpenCV Object Detection Object Tracking Machine Learning Python Artificial Intelligence Image Processing Deep Learning ⏱ People Counting System – Timestamps 01:30–04:00 → Introduction How people counting works, where it is used (shops, offices, events). 04:00–07:30 → System Requirements Hardware (camera), software, and environment setup. 07:30–12:00 → Installing Python & Dependencies Installing Python, OpenCV, NumPy, tracking libraries. 12:00–16:30 → Project Overview How detection + tracking + counting work together. 16:30–20:00 → Google Colab / Local Setup Runtime setup, GPU enabling, folder structure. 20:00–22:30 → Uploading / Preparing Dataset Video files, frame extraction, people dataset. 22:30–26:00 → YOLO / Detection Model Setup Cloning repo, weights, model configuration. 26:00–29:30 → Dataset Visualization Previewing frames, confirming detection quality. 29:30–33:00 → Entry / Exit Line Setup (ROI) Drawing entry line, exit line, region-of-interest explanation. 33:00–41:00 → Tracking Logic Implementation Using SORT/DeepSORT, assigning IDs, preventing double counts. 41:00–48:00 → Counting Logic Line-crossing detection, direction logic, handling crowded scenes. 48:00–54:30 → Real-time People Counting Live camera feed interpretation, overlays, FPS optimization. 54:30–57:00 → Conclusion Final output, accuracy summary, and next steps. ✨ Who Should Watch? 👨‍🎓 Students learning AI & Computer Vision 👨‍💻 Developers building real-time tracking systems 🏢 Professionals working on Smart Buildings & IoT 📊 Anyone interested in People Analytics Want to unlock Full Course: https://www.udemy.com/course/computer-vision-mastery-real-time-projects-opencv-python-ai-yolo/?referralCode=C219F7481A635FD9196A 🔥 Subscribe for more videos 💡 Got questions? Drop them in the comments below. 👍 If you find this video insightful, don't forget to like and share it with others 📲 Follow us on social media for more exciting updates and content: Instagram:https://www.instagram.com/scratchlearn/ Facebook:https://www.facebook.com/scratchlearn1/ #python #peoplecounting #yolov8 #opencv #computervision #aiproject #pythonprojects #deeplearning #machinelearning #finalyearprojects #sma rtbuildings #peopleanalytics #aiwithpython #tamiltech #pythonintamil #opencvpython #cv #occupancymanagement #scratchlearn