Baseline Released 🎁

We hope you have been following the development around the challenge.

Today, we are finally releasing a baseline, which was promised in the last townhall.

Did you miss the townhall?
You can check about it here: πŸ“Ή Town Hall Recording & Resources from top participants

:books: About the Baseline

The baseline contains fast heuristic implementations of some simple ideas.

  • Purchase images with more labels - For multilabel datasets, often having images with more than one label gives a boost for deep learning models.
  • Purchase uncertain images - Purchase images which have the most uncertainty in their predictions. While many methods exists to measure uncertainty, a simple output probability based heuristic method is used here.
  • Purchase images to balance labels - Well balanced datasets can improve model performance in deep learning. We set a uniform target distribution and try to purchase labels to get closer to that distribution. The provided code can try to purchase labels to any target distribution.

:student: Learn more about the implementation here.
:robot: Jump to the codebase directly here.
:sparkles: Looking for more resources to explore? Check out this thread.

:mag: Ok, talk is easy, how does it perform?

Well, as it stands, the baseline is currently on 5th position on the whole leaderboard.

:thinking: Do you have additional questions?

Feel free to drop them in this thread and we can reply them asap.
What are you waiting for? Let’s get started with the submissions! :sparkles:


This is great! Going to try plugging in some of my ideas (just when I was about to post my low tier baseline :sweat_smile:).