Real-Time Crowd Counting using OpenCV Python
Video-Based People Counting leverages neural networks to provide accurate and real-time counts of people within a designated area. This application analyzes video footage, ensuring precise counting even in crowded or dynamic environments. The system finds applications in retail analytics, event management, and public spaces, offering valuable insights into visitor trends and crowd dynamics. The neural networks’ adaptability and efficiency contribute to the effectiveness of people counting in various contexts.
Crowd Counting and Density Based Estimation refers to counting the number of people with density estimation present in certain area. Day to day population density increases and it does complexity of the calculations.
Person Detection and Counting using YOLO
Software Requirements :-
- Coding Language : Python
- Implementation: Software Framework.
- Operating system : Windows 10 / 11.
- Graphical User Interface : Tkinter
Hardware Requirement:-
- Input Devices : Keyboard, Mouse.
- System : Pentium i3 Processor.
- Hard Disk : 500 GB.
- RAM : 4 GB.
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