New Component: streamlit-terran-timeline makes it super easy to create face-recognition timelines!

Hello Streamlit community!

I’m very excited to show you some experiments I’ve been working on last week. It’s a face-recognition timeline generator tool for any kind of video!

This means you can analyze how much time actors appear on a series or a movie, calculate if Trump is more present in CNN or FoxNews, and many more scenarios! The component is called streamlit-terran-timeline and it works this way:

import streamlit as st
from streamlit_terran_timeline import generate_timeline, terran_timeline

timeline = generate_timeline("")
# Display the timeline. If the users click, you'll get the exact second of
# the part of the timeline video. By default, it returns 0.
start_time = terran_timeline(timeline)

And that’s it! You can also use the function if you want to display the video as well in your dashboard.

How did I build this? A few days ago my partners and I released Terran, a human perception library that makes super easy to build tools based images or videos.

We’d love to hear some opinions on this new component, let us know if you think it’s useful! Any feedback is more than welcome.

Thanks for your time!


Nice! Welcome to the community ! :star_struck: will test that

Feel free to add your component to our community tracker :wink:


Thanks @andfanilo! I’m trying to add the component into the list in the community tracker, but I think I don’t have sufficient permissions to do that yet :sweat: Do you know how can I get a role to edit that post?


Oh yeah I guess you need get your trust level to 1, it usually comes by reading a few topics on the forum :wink:

1 Like

very, very interesting, as soon as I have a few minutes free I am going to try it connecting it to my home cameras. do you know if anyone has already done it?


I’m using Terran for capturing the videos, it particularly accepts multiple sources of videos: files, streaming services, and local cameras. If you put the path to your camera, it should work. For example, using a path like /dev/video# in Linux.

You’ll probably need to set up the duration parameter for the generate_timeline so that you generate chunks of timelines and that’s what you actually end up plotting in the Streamlit dashboard.

Let me know if that works for you! :muscle: