limalkasadith/OxfordIIITPet-classification

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

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