This project is a Deep learning model used to convert images to monet style paintings, the whole project is written in Python and using the Tensorflow 2 library
Download the repository and run pip install -r requirements.txt to install all the required libraries
To use the model to generate paintings run the useGenerator.py code.
example: python useGenerator.py model/generator.h5 test_images/test1.jpg
the first parameter is the location of the generator, the second one is the location of the image to convert.
The generator model is a trained VGG19 model without the Sequential head connected to a not-trained flipped (from end to start) VGG19 model, pretty simular to an Auto Encoder architecture but without the Dense layer in the middle.
At first I tried to build it using CycleGAN, Som errors accurd so i tried to tackle the problam using simple GAN, it worked fine but didnt add colors to the results, then I returned to the CycleGan and made it work.
Got the dataset from Kaggle, I’m Something of a Painter Myself, cleaned it a little bit for my needs, You can find my final dataset here, Its splitted to landskape and paintings already in numpy files, the images are 256 256 3.
All of the presented examples are new photos I found online, They are not even a part of the dataset!
