Crowd Counting using YOLO
This project is based on Real-Time People Counting System using Python. In this system user have to provide input video to machine learning model and model will count the total number of people counting inside and outside to building, we have to make one prediction border so that system will classify the inside and outside part of building. Simultaneously it will check the person status like they are Tracking, Waiting, etc. This machine learning model also gave unique id to each person for counting and it will count separately how many people going outside and inside.
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.
People Counting IN and Out from Building using Python
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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