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.

Image segmentation on the oxford-iiit pet dataset using CNN's, GNN's and U-Nets

Training CNN based image classifiers to identify breeds of cats and dogs.

Training a Convolutional Neural Network to perform Image Segmentation on Oxford Pets Dataset

A dataset created using some images from the Oxford-IIIT Pet dataset, and then performing some data augmentation and processing

Semantic Image Segmentation task solution for the Oxford-IIIT Pet dataset using U-Net neural network, Hyperband and Transfer Learning. AGH 2023/24

CNN for classifying the breed of cats and dogs in the Oxford-IIIT Pet Dataset

Semantic segmentation with fully convolutional networks on the Oxford IIIT pet dataset.

UNet and DeepLabV3 for instance segmentation. Starting from a rgb image of a pet the network should output a segmentation mask of the pet. Deep Learning and Generative Models' practical project developed in 2025.

Image segmentation task for IIIT-Oxford Pets Dataset. Develops and compares various segmentation architectures. Also introduces important utility functions.

Deep learning-based segmentation with U-Net architecture on Oxford-IIIT Pet dataset, leveraging VGG16 model.