Often times when watching a lecture video the content that the lecturer writes on the board is quite representative of the the content of the lecture as a whole. This content, if provide in form of images, can become a helpful tool for students for revising concepts.
What it does
My project takes as input lecture videos and generates summary images that consist of all the content that was written on the board. Also a student can click on the board content to set the video to the timestamp at which that particular content was written.
How I built it
The video is first split into frames by sampling at 1fps
Challenges I ran into
Since i did not have access to a GPU locally, testing the whole pipeline was difficult as inference time on my MacBook Air was around 8-10 seconds per frame and I needed to annotate over thousand images. I ended up having to rely on google colab to generate the annotations and then use them locally.