Skip to content

User handwriting recognition app using a CNN trained on the EMNIST ByClass dataset

License

Notifications You must be signed in to change notification settings

bvsam/handwriting-recognition

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

17 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Handwriting Recognition App

This app uses a convolutional neural network (CNN) trained on the EMNIST ByClass dataset, which contains pictures of letters and digits, to predict a letter or digit handwritten by the user on a canvas.

The CNN was created using Python and TensorFlow/Keras and was trained on Google Colab. The model has a test accuracy of ~87%.

The app was created with basic HTML, CSS and JS. Bootstrap was used for styling, Fabric.js was used for canvas interaction, and TensorFlow.js was used to load and interact with the model.

View the live demo here