https://www.kaggle.com/competitions/gan-getting-started/overview
Computer vision has advanced tremendously in recent years and GANs are now capable of mimicking objects in a very convincing way. But creating museum-worthy masterpieces is thought of to be, well, more art than science.
A GAN consists of at least two neural networks: a generator model and a discriminator model. The generator is a neural network that creates the images.
The dataset contains 2 directories: monet_jpg, and photo_jpg. The monet directories contain Monet paintings, used to train the model. The photo directories contain photos.
The task is to add Monet-style to these images and generate JPEG images.
Monet images {Training dataset}: 300
Photos {From which, Monet style photos need to be generated}: 7038