SRnet-Demo
May 3, 2021 ยท View on GitHub
File Test.py is the main app.
You will need to download pretrained weights for:
Place these weights in their appropriate folders (look at the .py files for their paths)
Setup a tensorflow virtual environment (tf version 1.15)
Install all dependencies.
Run test.py in the virtual env.
Note:
- This demo uses the tensorflow version of SRNET. Change the code to the pytorch version (on my github).
- Streamlit is extremely slow because it has to load weights for the CRAFT model as well as for the SRNET model. Find a way to change this. Feel free to build from scratch.
- You could perhaps write a script for the bounding box detection and remove the craft model.
- I won't be able to help / assist because I'm extremely busy.
Please maintain this codebase however you see fit. Once you have a fast demo running, you can opensource it through this repo. You'll get all credit of course.