- Anaconda or Miniconda
- Python = 3.8
- PyTorch = 1.10.2
- NVIDIA GPU (24 GB recommended) + CUDA = 11.3
- Linux
-
Clone repo
git clone https://github.com/95anantsingh/NYU-SuperGAN.git cd NYU-SuperGAN
-
Create conda environment
conda env create -f environment.yml
-
Download weights
wget -i SuperGAN/weight_urls --directory-prefix SuperGAN/data/weights
cd SuperGAN
conda activate SuperGAN
python faceswap.py
Now play data/output/output.mp4
to see results
Make necessary changes in faceswap.py for different input videos.
SuperGAN
contains all the project filesSuperGAN/data
contains input output videos and pretrained weightsSuperGAN/faceswap.py
main inference file
Project report can be found at docs/SuperGAN_Report.pdf
Ideal setup is with NVIDIA Quadro RTX 8000 (48 GB GDDR6) on Linux
SuperGAN is released under Apache License Version 2.0.
If you have any question, please email [email protected]
This Project was part of graduate level Deep Learning course at New York University