1. Copy the paintings.zip from Google Drive into the Project folder
2. Extract the paintings.zip file.
3. Delete the paintings.zip file.

1. Install Python 3.6.3
2. Open a Terminal in your Project Folder
3. Create a Virtual Environment with python3 -m venv ./venv
4. Activate the Virtual Environment with source venv/bin/activate
5. Install the requirements with pip install -r requirements.txt

1. Run training.py once. At first it won't work since Keras is not yet configured, but this will create a .keras folder in $HOME
2. Open the file .keras/keras.json in your Home directory.
3. Change the backend entry to 'theano'.
4. Change the image_data_format entry to channels_first
5. Save and exit the file.
6. Now, you should be able to run training.py without errors!

• All configurations can be made in config.py. I pushed the ones that are most interesting to the top of the file.
• The layers of the CNN can be changed in cnn.py. Make sure that the Flatten() layer is always the last one.

• Run the training.py script. This script trains and validates the CNN.

https://blog.keras.io/building-powerful-image-classification-models-using-very-little-data.html https://keras.io/ https://github.com/inejc/painters/blob/master/painters/train_cnn.py https://www.wga.hu/index1.html