Python program to find the art movement and the artist the input image most probably would have come from.

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

This code has been tested under Python 3.6

Here are the few packages needed to run the file tests/predict.py

pandas
numpy
pillow
tensorflow
h5py
scipy
pyyaml
keras
wikipedia

To install the above libraries, go to terminal if on UNIX or bash if on Windows and type in the following command

pip install pandas numpy pillow h5py scipy pyyaml tensorflow keras wikipedia

Two more direcctories need to be created to carry out the tests. Inside the main repository directory, creates two directories named images and data. Inside images put all the image files that are needed to carry out the desired predictions. Inside data two models are needed to be stored to make the predictions. They can be downloaded from here. Inside data, one more file named all_data_info.csv is needed that can be downloaded from kaggle through this link.

• Satvik Shukla - satvikshukla

This project is licensed under the MIT License - see the LICENSE.md file for details

• Painter by numbers competition for providing the data to make the models.
• This repository for acting as reference for style transfer