Image classification

MOD 4.6 Deep Learning & Artificial Intelligence

Description

The objective of this tutorial is to write a complete image classification program in Python. Two classification models will be successively developed and tested: k-nearest neighbors (KNN) and neural networks (NN).

Requirements

In this tutorial we use Python 3.7 or higher and the library numpy.

Usage

The image database used for the experiments is CIFAR-10 which consists of 60 000 color images of size 32x32 divided into 10 classes (plane, car, bird, cat, ...). This database can be obtained at the address https://www.cs.toronto.edu/~kriz/cifar.html where are also given the indications to read the data.

The python file named read_cifar.py contains the functions needed to read the data.

The python file named knn.py contains the functions developping and testing the k-nearest neighbors classification model.

The python file named mlp.py contains the functions developping and testing the multilayer perceptron neural networks classification model.

Author

Myla Arab

License

MIT License