An implementation of Deep Recursive Residual Network for Super Resolution (DRRN), CVPR 2017
usage: main.py [-h] [--batchSize BATCHSIZE] [--nEpochs NEPOCHS] [--lr LR]
[--step STEP] [--cuda] [--resume RESUME]
[--start-epoch START_EPOCH] [--clip CLIP] [--threads THREADS]
[--momentum MOMENTUM] [--weight-decay WEIGHT_DECAY]
[--pretrained PRETRAINED]
optional arguments:
-h, --help Show this help message and exit
--batchSize Training batch size
--nEpochs Number of epochs to train for
--lr Learning rate. Default=0.1
--step Learning rate decay, Default: n=5 epochs
--cuda Use cuda?
--resume Path to checkpoint
--clip Clipping Gradients. Default=0.01
--threads Number of threads for data loader to use Default=1
--momentum Momentum, Default: 0.9
--weight-decay Weight decay, Default: 1e-4
--pretrained Path to the pretrained model, used for weight initialization (default: none)