Deep learning project to create new images based on the previous ones
In order to be loaded using NSRRDataLoader
, the dataset should be structured like so:
[root_dir]
│
└───View
│ │ img_1.png
│ │ img_2.png
│ ...
│
└───Depth
│ │ img_1.png
│ │ img_2.png
│ ...
│
└───Motion
│ │ img_1.png
│ │ img_2.png
│ ...
Where root_dir
can be given as an argument, and View
, Depth
and Motion
are static members of NSRRDataLoader
.
Note that corresponding tuples of (view, depth, motion) images files should share the same name, as they cannot be grouped together otherwise.
python3 unit_test.py --directory [path_to_root_dir] --filename [image_name]
Using :
-
Pytorch project template at: https://github.com/victoresque/pytorch-template
-
Pytorch implementation of SSIM: https://github.com/Po-Hsun-Su/pytorch-ssim
-
Pytorch implementation of colour-space conversions: https://github.com/jorge-pessoa/pytorch-colors