Person Counter

Inspiration

The waiting times at the uOttawa gyms (and never knowing when its busy!)

What it does

Our app tracks the capacity of any room using computer vision, and displays the capacity on a web app as a percentage. Each person who is identified is given an ID, and thus we only track when new people enter the field of vision of the video input.

How we built it

Python + OpenCV library, Django

Challenges we ran into

Communication between our program and the web app, as well as accuracy of the counter.

Accomplishments that we're proud of

Fixing the accuracy issues, implementing OpenCV for the first time in a project together, and learning how to set-up a web app with Django!

What we learned

How powerful computer vision can be, the importance of having a strong team, and the power of collaboration (especially w/ fellow hackers - s/o to those who helped us run our test cases!)

And a LOT about web app development!

What's next for Person Counter

Some other applications we thought of for this program were...

• Integration with security cameras (possibly snapshots of faces using feature detection?)
• Integration all over uOttawa to help students find out where the busiest parts of campus are at each time of the day