Social Distance Detection using Deep Learning
In this video, we will show Social Distancing Violation Project, developer have to add the threshold value of distancing from that distance if person came then it will give alert. In this feature user can select any input video and model will detect social distancing violation. It will identify distancing between two persons and it will also count number of person in single frame.
This project is made with Python to see if people wear face masks and stay apart to stay healthy. The project checks pictures or videos to see if people wear masks and if they’re far enough from each other. We use Python, OpenCV, and TensorFlow to do this. It helps us remember to wear masks and keep safe distances. We can make it easier to see the results with Tkinter or PyQt. This project is important for our health, especially during sickness outbreaks like COVID-19.
Advantages of Face Mask and Social Distancing Project using Python:-
1. Finds Problems Early: Tells us right away if someone isn’t wearing a mask or standing too close to others.
2. Shows Us Trends: Helps us see if more people are following the rules over time.
3. Teaches Us: Reminds us why wearing masks and staying apart are important for our health.
4. Works Everywhere: Can be used in many places like schools, offices, and public events.
5. Fits with Other Systems: Can be added to systems we already use to keep an eye on things.
Face Mask and Social Distancing Detection 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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