Daniele Moro and Oghenemaro Anuyah

CS 497 Applied Deep Learning Final Project

Winner of top 3 final presentations in the class.

This is a bot that automatically generates personal compliments based on a user's image and written emotional state. It uses a seq2seq model with an LSTM and GLOVE embeddings.

For more details, see FinalReport.pdf

1. Set up a Python 3 environment with the packages found in env.txt
2. Download glove.6B.zip from the Glove site and place the files in the root directory
3. Run RedditDownload.ipynb to download the data for training and extract the visual features from the images.
4. Run ToastBot.ipynb to train and evaluate a model that uses both the visual and textual features. You can also evaluate our existing model by loading model.h5 before evaluation.
5. (Optional) run ToastBot_images.ipynb and ToastBot_text.ipynb to train and evaluate models that only use either textual or image data respectively.

To run the web server for easy interaction with the compliment generator, run ToastBot_server.py, and it will start up a Flask server on your localhost. The server will use ToastBot_predict.py to run the compliment generation, so make sure this file is loading the appropriate model.