As artists, it is in our DNA to allow us to create and portray our feelings and emotions through different forms and mediums. Social media has opened the doors for choreographers and dancers to showcase these emotions to broader audiences at a faster rate. Yet, amidst this exposure, the true essence of authorship often fades into the background. Many creators find their work celebrated without proper recognition, their unique expressions overshadowed in a sea of content. This is why we created trace ai—to reclaim authorship and ensure that every dancer receives the acknowledgment they deserve.
cd tracev2npm installnpm run dev
We categorize trace ai into two parts. The Full Stack and the Analysis. Tackling the full stack first, the front end was created with the React API and CSS. Now for the backend, we used both MongoDB and Firebase for handling video data and user data. We decided to have two separate backends to store the URLs of the videos uploaded, while Firebase holds the user data and the actual uploaded files of the user.