DID-MDN
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Train residue extraction network from scratch
Guidance from README.md
python derain_train_2018.py --dataroot ./facades/DID-MDN-training/Rain_Medium/train2018new --valDataroot ./facades/github --exp ./check --netG ./pre_trained/netG_epoch_9.pth.
Make sure you download the training sample and put in the right folder
Code Snippet in derain_train_2018.py
netG=net.Dense_rain()
if opt.netG != '':
netG.load_state_dict(torch.load(opt.netG))
print(netG)
Why fine-tune on top of a pre-trained model?