This repository houses notebooks belonging to the "GAN Getting-Started" competition, hosted by Kaggle. The notebooks have been set up by three students of team 2 of the Radboud University Masters course "Machine Learning in Practice".
The dataset consists of 7028 real-life photos and 300 images from Claude Monet. All the images are RBG with a size of 256x256.
The goal of this competition is to generate Monet-style images out of the real-life photos using GAN-based models. For our implementations we decided to use CycleGAN.
The notebooks present in this repository were directly downloaded from Kaggle. The notebooks were written in Python and ran on a Kaggle TPU v3-8 accelerator. Additionally, libraries like Tensorflow, Keras, numpy and scipy were used.
Prashans Dixit (2021, April). 📝Coleridge Initiative-EDA📚 & Baseline Model🎯. https://www.kaggle.com/prashansdixit/coleridge-initiative-eda-baseline-model