Build an AI People Counter | Retail Analytics & Crowd Tracking | Computer Vision Project 2025

📊 Transform video feeds into actionable data! In this comprehensive tutorial, you'll learn how to build a accurate Real-Time People Counting System using Python, OpenCV, and object tracking.

▶ *WATCH THE FULL PROJECT TUTORIAL:* [ https://youtu.be/VAx0elypsrg?si=7kPH4reDdjbaR8Gw ]

⬇️ **SOURCE CODE & DATASET:** [ https://www.scratchlearn.com/projects/people-counting-detection.html ]
This computer vision project is perfect for retail analytics, smart building occupancy monitoring, event management, and serves as a fantastic portfolio piece for students and developers.

In this hands-on guide, you will learn how to:
✅ Perform real-time object detection using YOLO (You Only Look Once) to identify people.
✅ Implement the Deep SORT algorithm for robust, persistent object tracking.
✅ Define virtual counting lines or zones to track entries and exits.
✅ Log count data to a CSV or database for further analysis and visualization.
✅ Calculate crucial metrics like footfall, occupancy, and dwell time.

🛠 **Technologies & Libraries Used:**
- Python Programming
- OpenCV (Computer Vision)
- YOLOv8 (from Ultralytics)
- Deep SORT (Object Tracking)
- NumPy, Pandas (Data Handling)
- Optional: TensorFlow/PyTorch

📁 **Project Files:**
- Complete Python Source Code
- Pre-trained YOLO model weights
- Sample video datasets for testing
- Step-by-step Jupyter Notebook

This tutorial is ideal for you if you're searching for: real-time people counting, people counter system, OpenCV project, object tracking, YOLO deep learning, retail analytics, footfall analysis, crowd counting, visitor counter, computer vision tutorial, and final year project ideas.

#peopleanalytics #opencv #yolov8 #deep #python #computervision #ai #dataanalytics #retailtech #smartbuilding #coding #programming #project #sourcecode #artificialintelligence #scratchlearn

Видео Build an AI People Counter | Retail Analytics & Crowd Tracking | Computer Vision Project 2025 канала ScratchLearnEnglish