This repository is modified from Xyfuture/hpc_backbone for easier and faster deployment and test:
- Change the backend framework to Flask
- Delete Redis Message Queue
Note: "Using Flask in this way is by far the easiest way to start serving your PyTorch models, but it will not work for a use case with high performance requirements." DEPLOYING PYTORCH IN PYTHON VIA A REST API WITH FLASK
Related Deep Learning Models:
- LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
- Code for this paper: https://github.com/saic-mdal/lama
- DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better, ICCV 2019
- Code for this paper: https://github.com/VITA-Group/DeblurGANv2
Download model weight to models/big_lama/weight/
and models/deblur_gan/weight/
Install dependencies:
pip install -r requirements.txt
Start server
python app.py