Crowd Counting using Yolo
People Counting and Detection in Historical places utilizes neural networks to monitor and analyze crowd dynamics. By processing video feeds, the system accurately counts and tracks the movement of people in various areas. This application aids in optimizing space utilization, ensuring crowd safety, and facilitating efficient crowd management. The neural networks’ capability to handle diverse scenarios and crowd sizes enhances the accuracy and reliability of people counting.
People Counting and Detection in Historical places utilizes neural networks to monitor and analyze crowd dynamics. By processing video feeds, the system accurately counts and tracks the movement of people in various areas. This application aids in optimizing space utilization, ensuring crowd safety, and facilitating efficient crowd management. The neural networks’ capability to handle diverse scenarios and crowd sizes enhances the accuracy and reliability of people counting.
Person Detection and Counting using Machine Learning
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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