CISC452-Project

Investigating deep learning methods for compressing and decompressing faces

Results

Refer to the paper for more details.

Reconstructed Images by the Deep Convolutional Generative Adversarial Network

Reconstructed Images by the Convolutinal Variatinoal Autoencoder

Instructions

Environment Setup

Skip 2 and 3 if you're lazy/a maniac.

1. Go to project root
2. Set up environment by running python -m venv .venv or python3 -m venv .venv
3. Run source .venv/bin/activate on Linux and MacOS, ./venv/Script/activate on Windows.
4. Run pip install -r requirements.txt

Dataset

1. Download the celebA dataset
2. Extract dataset to project root (optional, but will make your life easier)
3. Rename the dataset folder to dataset (also optional, but the skeleton code assumes it's called dataset)
4. Ensure there are no subfolders. The dataset folder should only contain images of faces.