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A project for Le Wagon Batch #805 by Eloho Kemi, Flavien Kuss-Vargas, Saul Wegzryn, and YiWen Hon

We created a Deep Convolutional Generative Adversarial Network (DC GAN) and trained it on 3600 images of Abstract Expressionist art. We also created an Autoencoder and K-Nearest Neighbours model to evaluate the output of our deep learning model.

The live project is showcased at https://share.streamlit.io/FlavKV/website/website.py

Huge thank you to Yassine, Yannis, Cristophe, Julio, Marie, and all the other Le Wagon staff for being so patient and generous with their time and knowledge.

We also utilised the resources below when working on our project:

Generating modern art using GAN

Creating Romantic period art with Tensorflow DCGAN

Content-based image retrieval using autoencoders

WikiArt Kaggle dataset