Contributors (All equally contributed):
- Ahmet Melek
- Onur Boyar
- Furkan Gürsoy
- Burak Satar
We restore very dark images to high quality and visible images.
Our purposes on this project are:
1- Reproduce the results of Learning to See in the Dark project, as can be seen here: https://github.com/cchen156/Learning-to-See-in-the-Dark
2- Obtain results faster via optimization of the code.
3- Trying to have better results with modifications. (optional goal)
4- Testing different architectures on this problem. (optional goal)
inzva AI Projects #2 - Image Restoration Project
1- Paths and hyperparameters can be set at the top of test_Sony.py and train_Sony.py files.
2- The files will be read from respective input and ground truth directories.
3- The size of the deep neural network will be decided based on hyperparameters.
4- Training and test sets are generated based on the first characters of the filenames. Please refer to the code for specific implementation.
5- Output images and trained models will be saved in result and checkpoint directories.
6- For both training and test; epoch, loss, time information are printed during execution.
Let us know if you spot any error or have any suggestions.