This is the Linux app named Super-résolution via CNN whose latest release can be downloaded as Release.zip. It can be run online in the free hosting provider OnWorks for workstations.
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SCREENSHOTS:
Super-résolution via CNN
DESCRIPTION:
Super-resolution using a CNN, based on the work of the DGtal team. First of all, an Nvidia graphics card (neither AMD nor Intel integrated) is highly recommended to parallelize the CNN. You will then need to install CUDA. No CUDA = dozens of times slower. This program will generate "model_epoch_ .pth" files corresponding to the model at epoch n, in a folder saved_model_u t_bs bs_tbs tbs_lr lr, where corresponds to the scale factor, bsthe size of the training batch, tbsthe size of the test batch and lrto the learning rate. Low res images should be located in a "dataset/input" folder, and high res targets in a "dataset/target" folder, where each different quality image has the same name in both folders.
Features
- GTVImageVect (C++ to compile or Linux binary to download)
- ImageMagick (Available via sudo apt install imagemagick)
- Generally speaking, a Linux, emulator or WSL
- An Nvidia graphics card (neither AMD nor Intel integrated) is highly recommended
- Parallelize the CNN
- Based on the work of the DGtal team
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/super-r-solution-via.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.