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[P] Machine Learning: Doodle Recognition with Convolutional Neural Network

Hi all,

I’m launching a step-by-step video tutorial series on making a game like “Quick, Draw!”. As you probably know, it is an online game that challenges players to draw a doodle and then artificial intelligence guesses what the drawings represent. So I thought this group would appreciate this project.

Using Phaser 2 framework and Tensorflow.js library, I’ve created a complete HTML5 game called Doodle Predictor that runs directly in the browser and recognizes doodles.

To classify drawings, the game uses Machine Learning with a Convolutional Neural Network. The model is trained on a small subset of the Quick Draw Dataset.

I tried to make this project easy enough for someone without any machine learning experience to follow. So if you are interested in it, here are the links:

 

Video Episode 1:

Introduction

 

Video Episode 2:

Part 1 – Project Setup

Part 2 – Getting Data

Part 3 – Building Model

Part 4 – Training Model

 

Video Episode 3: (coming soon)

Part 5 – Predicting Samples

Part 6 – Drawing Doodles

Part 7 – Recognizing Doodles

Part 8 – Adding More Categories

 

Video Episode 4: (coming soon)

Game Demo

 


Play Doodle Predictor on my blog:

https://www.askforgametask.com/tutorial/doodle-recognition-convolutional-neural-network-intro

 

Source Code available on Github:

https://github.com/ssusnic/Machine-Learning-Doodle-Recognition

 

submitted by /u/ssusnic
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.