Skip to content

Video classification project as part of LeWagon's data science bootcamp

Notifications You must be signed in to change notification settings

DucVanNgo/dancemachine-by-871

 
 

Repository files navigation

Project

Goal of the project is to create a deep learning model which can learn a tiktok dance and correctly classify new videos based on whether the taught dance is included in the video or not. Check out the heroku app (API call offline)

We extract the body poses from the TikTok videos by leveraging the MediaPipe package, specifically it's body pose component to extract the landmarks from the video. Using the landmarks extracted from the body poses we calculcate the angles between key joints to adjust for height differences and as the landmark coordinates are only given relative to the image size. Lastly a tensorflow RNN model is trained based on 120 Tiktok videos (40 correct, 60 incorrect dances)

You can watch our presentation at LeWagon's Demo Day here

Team Members

DucVanNgo
wanliammar
worldlife92
DominiqueSch

Data Source

Tiktok Videos / Specifically the jiggle jiggle dance

About

Video classification project as part of LeWagon's data science bootcamp

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 87.8%
  • Python 11.1%
  • Other 1.1%