where-is-waldo

Where’s Waldo: Train an AI Model to Find Waldo

Welcome to the Where’s Waldo AI Lab! 🎉 In this project, you’ll explore the world of Artificial Intelligence 🤖 and learn how to train a Vision Transformer model to solve one of the most beloved visual puzzles—finding Waldo. 🔍

Support-Ukraine

🧑‍🌾 Lecturer: Teerapong Panboonyuen (P’Kao), Ph.D.

📧 Contact:


📥 Download Resources

Easily access the slides and Google Colab notebook for a seamless learning experience:

About the Lab

Where’s Waldo is a classic puzzle where Waldo, a character in a red-striped shirt, red beanie, and glasses, is hidden among hundreds of people in busy scenes. 🧑‍🤝‍🧑 In this lab, you’ll use cutting-edge AI techniques to teach a computer to spot Waldo faster than any human can! 🚀

This activity is designed for students and beginners curious about AI and machine learning. No prior knowledge of AI is required—just bring your curiosity and enthusiasm! 😄


What You’ll Learn


Getting Started

Prerequisites

  1. A laptop or PC 💻 (50 computers will be available for participants in the workshop)
  2. A Google account to access Google Colab (free) 🌐
  3. Basic familiarity with Python 🐍 is helpful but not required

Steps to Join the Lab

  1. Clone this repository:
    git clone https://github.com/kaopanboonyuen/where-is-waldo  
    cd where-is-waldo  
    
  2. Open the provided Google Colab notebook:
  3. Follow the step-by-step instructions in the notebook to:
    • Load the Where’s Waldo dataset 🧑‍💻
    • Preprocess images for training 🖼️
    • Train your AI model using Vision Transformers 🚀
  4. Experiment with your trained model to see how quickly it can find Waldo! ⏱️

Event Details

📅 Date: 26 December 2024
📍 Venue: อาคารศูนย์ประชุมอุทยานวิทยาศาสตร์ประเทศไทย (Thailand Science Park Convention Center)
🎓 Instructor: Teerapong Panboonyuen (P’Kao)


Why Participate?


Explore More

Check out the full presentation:
Waldo AI: The Ultimate Hide-and-Seek Showdown - Slides 📜

Access the Google Colab notebook:
Waldo AI Notebook 🌐


License

This project is licensed under the MIT License. See the LICENSE file for more details. 📜


Contributing

We welcome contributions! 🌱 If you’d like to improve the lab or add more features, feel free to submit a pull request. 🔄


References


Contact

For any questions or issues, reach out to:
👨‍🏫 Teerapong Panboonyuen (P’Kao)
📧 Email: kao.panboonyuen@gmail.com