willyfh / cat-breed-classification-using-cnn

Cat Breed Classification Using Convolutional Neural Networks

Cat Breed Classification Using Convolutional Neural Networks

Overview

In this project, I built a machine learning model capable of classifying images of cat breeds on the Oxford-IIIT Pet Dataset [1]. The convolutional neural network (CNN) model built in this project has a better accuracy compare than a previous model created by Parkhi et al. [2]. Transfer learning is performed to transfer the knowledge of previously trained CNN in order to get a better accuracy.

Attention: the notebook was executed & tested using GPU. So please make sure the GPU is available to avoid unexpected error.

You may also find the notebok file from this Google Colab page : https://colab.research.google.com/drive/17JsvgWQKitcmM18E9bd-eCQIZ6p5ES6d

Prerequisites (the installation cell is provided in the notebook):

• torch==1.3.1
• torchvision==0.4.2
• numpy==1.15.4
• pandas==0.24.2
• matplotlib==3.0.3
• tqdm==4.38.0
• sklearn==0.20.3`1
• seaborn==0.8.1

The dataset which will be used for this project can be downloaded by executing the 'Download' cell in the notebook.

Sample of correct predictions

References

[1] https://www.robots.ox.ac.uk/~vgg/data/pets/

[2] https://www.robots.ox.ac.uk/~vgg/publications/2012/parkhi12a/