This repository contains a single page website that enables users to draw digits (0-9) by hand and have the digits classified in real time as they are drawn by a machine learning model trained against the MNIST dataset.
Python 3.5+ is required for compatibility with all required modules
# Clone this repository git clone https://github.com/marcacohen/mnist-draw.git # Change to the repo root directory cd mnist-draw # Install required modules pip install -r requirements.txt
To launch the website, begin by starting a Python server from the repository folder:
# Start Python server (use Python 3) python -m http.server --cgi 8000
Then open a browser and navigate to
An example of the website's interface is shown below. Users are guided to draw a digit (0-9) on the empty canvas and watch the page try to classify your digit as you draw.
Results are displayed as a bar graph where each classification label recieves a score between 0.0 and 1.0 from the machine learning model. Clear the canvas with the 'Clear' button to draw and process other digits.
Machine Learning Model
The model I'm using for this page a convolutional neural network (CNN) built using Keras/TensorFlow on a Google Tensor Processing Unit (TPU). The model is explained in depth and is available for you to build yourself here.
Thanks to rhammell for the original Python version and to zackakil for adding support for Tensorflow.js. In this version I added predicting while you draw, deployed the example UI on Cloud Run (bit.ly/mco-mnist-draw), and deployed a Colab notebook (bit.ly/mco-mnist-lab) so you can build your own version of this model, with the UI widget integrated right into the notebook.