STAT 671 Cats/Dogs Classification Demo

This demo is made for the Portland State University (PSU) STAT 671 class. Inspiration was taken from VictorRielly's voronoi repo. It shows how a simple kernel based classification algorithm, equipped with an appropriate kernel, can classify images of cats and dogs.

Usage

Before running, place images of your cats and dogs in the user_data folder. The notebook will automatically grab these images, classify them, and display them.

Installation

Install the python requirements

pip install -r requirements.txt

Launch the Jupyter notebook

jupyter notebook

Open the Cats-And-Dogs-Demo.ipynb notebook and run it.

Create Model (optional)

The demo comes with a NN model saved as a .h5 file, so there is no need to train the NN again. If you need to re-train it, follow these steps

1. Go here to download the dogs-vs-cats.zip and extract all folders at the correct hierarchies. Place it in the current working directory.
2. Now, run

python src/create_model.py

It took 5 hours of training on CPU, and ~1.5 hours on GPU. The new .h5 file will be populated in the current working directory.