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Digit_Recognition

Final Project for class:

Basics of Machine Learning

Instructor

Dr. Paweł Morkisz

Description:

The program is trained using MNIST dataset to predict handwritten digits. There is a GUI for users to draw their own digits using a mouse. The program can predict digits that users draw using their mouse. It can also be used to predict digits in images if they are provided as an input.

Structure:

Digit Recognition:
-evaluateModel.py ->To evaluate model.h5.
-model.h5 ->Model created in saveModel.py
-saveModel.py ->Preprocess the data and creates te model
-predictGUI.py ->GUI to predict handwritten digits

Report.pdf: ->Pdf of the report

Usage:

To use the application, simply run predictGUI.py.

Language, Version, IDE

Python 3.8, Pycharm Community Edition 2020.2.3

Requirements:

python -m pip install keras tensorflow Pillow opencv-python

You don't have to run saveModel.py to create a model because model.h5 is already included in the repository. If you wish to create a new model on you computer, you can run saveModel.py and a new model will be created.

Example Image

digit

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A program that can guess digits drawn by users.

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