Project
Building real-time pose detection with OpenPose
A terrific project: Open Pose Detection, a powerful real-time, multi-person tool with applications across a wide range of fields.
Where pose detection is useful
- Sports and fitness: performance analysis, injury prevention, and virtual training.
- Healthcare and rehabilitation: gait analysis and physical therapy.
- Machine learning: integration with gesture recognition and virtual reality.
- Surveillance and security: behaviour analysis and crowd monitoring.
- Motion capture.
The versions
The project has a few versions that suit different devices and cameras, since it can use a lot of memory and benefits from GPU acceleration for smoother performance.
- Versions 1 and 2 detect a single person in real time, with white or black background output in a pop-up window.
- Versions 3 and 4 detect multiple people in real time, also with white or black background output in a pop-up window.
Thanks
Thanks to Maysam Hafezparast and Arash Tabrizi for giving me the opportunity to build this project for KidoCode, under the supervision of Farhad Hossain, during the last two days of my internship. I'm proud that I was able to finish it with the given requirements and customizations, and I'm looking forward to more projects like this.
Thanks also to Mojgan Bagha for spotting my silly mistakes and helping us improve; that culture of feedback is a really good thing KidoCode teaches. I would love to work with you all again in the future.
The kid in the demo video is Ayrik Falamrzi, a student at KidoCode.