Player Pose Recognition using Machine Learning
In this blog, we will explain the working of Human Pose Recognition using Image Processing, this project trained on large dataset of images that contains multiple classes of different sports activities position like address, takeaway, mid backswing, top of swing, pre-impact, release, finish. It will identify the position of player. It works on input images or real time laptop front camera, in which laptop front camera will open and we can use external camera to detect the human posture.
Human Activity Recognition using Deep 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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