This project uses TensorFlow and Keras to build a Convolutional Neural Network (CNN) for classifying two different styles of art: Japanese and Rococo. The implementation includes data preparation, model training, and a Flask application for making predictions.
The dataset used in this project is sourced from WikiArt - Art Movements/Styles.
- data_preparation.ipynb: Jupyter Notebook for reading images and creating train, test, and validate datasets.
- implementation.ipynb: Jupyter Notebook for reading and augmenting images, building and training the CNN model, and running validation.
- app/:
- app.py: Flask application for predicting the art style using the trained model.
- static/: Folder for storing static files (images in this case).
- templates/: HTML templates for the Flask application.
run the flask app using python app.py Make sure you have all the dependancies installed
