Oxford IIIT Pet Dataset Classification with PyTorch

This repository contains a PyTorch implementation for classifying the Oxford IIIT Pet Dataset using K-Nearest Neighbors (KNN) and ResNet. The goal is to differentiate the results obtained using these two approaches.

Dataset

The Oxford IIIT Pet Dataset is a widely used dataset for fine-grained classification of pet images. It includes images of 37 different breeds of dogs and cats.

Models Used

K-Nearest Neighbors (KNN)

The KNN algorithm is employed for classifying the images in the dataset. The choice of K and other hyperparameters can be configured in the code.

ResNet-34

We utilize the ResNet-34 architecture pre-trained on the ImageNet-1K dataset. This pre-trained model is used for linear evaluation and fine-tuning on the Oxford IIIT Pet Dataset.

Collaborators

Special thanks to the following collaborators who contributed to this project:

• Hiruni Wijewardena
• Dilani Widanapathiranage
• Chathuni Wijegunawardana