Conser-vision Practice Area: Image Classification

Looking for a great way to start working with computer vision? This competition features a small dataset of wildlife captured by camera traps used in conservation research. #climate

advanced practice
1 year left
887 joined



Can you classify the wildlife species that appear in camera trap images collected by conservation researchers?

Welcome to the African jungle! In recent years, automated surveillance systems called camera traps have helped conservationists study and monitor a wide range of ecologies while limiting human interference. Camera traps are triggered by motion or heat, and passively record the behavior of species in the area without significantly disturbing their natural tendencies.

However, camera traps also generate a vast amount of data that quickly exceeds the capacity of humans to sift through. That's where machine learning can help! Advances in computer vision can help automate tasks like species detection and classification, localization, depth estimation, and individual identification so humans can more effectively learn from and protect these ecologies.

In this challenge, we will take a look at object classification for wildlife species. Classifying wildlife is an important step to sort through images, quantify observations, and quickly find those with individual species.

This is a practice competition designed to be accessible to participants at all levels. That makes it a great place to dive into the world of data science competitions and computer vision. Try your hand at image classification and see what animals your model can find!

Competition End Date:

Oct. 5, 2025, 11:59 p.m. UTC

This competition is for learning and exploring, so the deadline may be extended in the future.

How to compete

  1. Click the "Join the competition" button on the sidebar to enroll in the competition.
  2. Get familiar with the problem on the About page and Problem Description, or discuss issues on the user forum.
  3. Download the data from the Data tab.
  4. Create and train your own model. The benchmark blog post is a great place to start!
  5. Use your model to generate predictions that match the submission format. Click “Submit” in the sidebar, and then “Make new submission”. You’re in!
  6. Bonus: share your work! Click the "+" icon on the Submissions page and add a link to your approach.

Data is provided courtesy of the Wild Chimpanzee Foundation and Max Planck Institute for Evolutionary Anthropology.