demosaicnet
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Published
20 hours ago •
mgharbi
mgharbi
A minimal torch implementation of [Gharbi2016]
Deep Joint Demosaicking and Denoising
SiGGRAPH Asia 2016
Michaël Gharbi [email protected] Gaurav Chaurasia Sylvain Paris Frédo Durand
A minimal pytorch implementation of "Deep Joint Demosaicking and Denoising" [Gharbi2016]
Installation
From this repo:
python setup.py install
Using pip:
pip install demosaicnet
Then run the demo script with:
python scripts/demosaicnet_demo.py output
To train a dummy model on the demo dataset provided, run:
python scripts/train.py --data demosaicnet/data/dummy_dataset --checkpoint_dir ckpt
To build and update the whee:
pip install wheel twine
make distribution
make upload_distribution
FAQ
- How is noise handled? Where is the pretrained model? The noise-aware model is not implementation, see the earlier Caffe implementation for that https://github.com/mgharbi/demosaicnet_caffe
-
How do I train this? The script
scripts/train.pyis a good start to setup your training job, but I haven't tested it yet, I recommend rolling your own.
mgharbi