Using Teachable Machine Models in Scratch

Apps used:

1. Scratch mod with AI extensions  – https://playground.raise.mit.edu/create/

2. Teachable Machine – https://teachablemachine.withgoogle.com/

Introduction

Once you’ve trained a machine learning model using Teachable Machine, it’s time to bring it to life in practical applications. This article explains how to integrate your model into Scratch, turning it into a computer vision controller for games and multimedia projects.

Setting Up Scratch for AI Integration

Step 1: Access the Modified Scratch Version

• Visit Playground Raise, a modified Scratch platform with AI extensions.
• Add the Teachable Machine extension to enable ML model integration.

Step 2: Import Your Model

• Use the Teachable Machine block to paste the model’s URL, generated during the training process.
• Confirm that the model is active by checking the green light indicator.

Building an Interactive Application

Example: Sprite Movement

1. Connect the Model Prediction Block:
   • Use the forever loop to display the model’s predictions (e.g., “Left,” “Right,” “Nothing”) through the say block.
2. Add Motion:
   • Create conditions for movement:
     • If the prediction is “Left,” move the Sprite left.
     • If the prediction is “Right,” move it right.
     • If “Nothing,” reset its position.

Extending Your Project

• Create Games: Use gestures to control falling object games, car driving simulations, or other creative applications.
• Enhance Conditions: Add more gestures or refine the logic for smoother interactions.

Benefits of Using Teachable Machine with Scratch

1. Interactive Learning: Combines coding, machine learning, and creative thinking.
2. Ease of Use: Simplifies complex AI concepts for students of all levels.
3. Limitless Possibilities: Encourages experimentation with multimedia projects.

Conclusion

By integrating Teachable Machine models into Scratch, students and educators can explore endless possibilities for creating interactive, AI-powered projects. This hands-on approach bridges the gap between AI theory and practical application, sparking creativity and innovation.