Welcome to the Dojo Hackathon 2025! In this exciting cross-functional challenge, participants will compete to solve a real-world computer vision challenge.

## **📋 Competition Overview**
The challenge is a binary image classification task: building models to accurately determine whether a given image contains an empty plate or a not-empty plate.

With a dataset of over 350 labeled plate images, competitors will explore the data, experiment with preprocessing techniques, and train machine learning models to achieve the highest accuracy.

The competition's scoring metric is accuracy (how often are your predictions correct), but there will be a special place in my heart reserved for the individual or team with the most inventive solution!

## **🎯 Goal**
Develop a predictive model that can reliably classify plates as empty or not-empty. Success will depend on creative problem-solving, effective data preprocessing, and innovative model tuning.