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All Projects → kayr7 → PyTorch-SRGAN

kayr7 / PyTorch-SRGAN

Licence: Apache-2.0 License
PyTorch version of the paper: "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"

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pytorchvgg19srganpytorch-srresnet

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PyTorch-SRGAN

Source: SRResNetVgg5,4: (Ground Truth: )

PyTorch version of the paper: Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network (currently it does not implement the GAN, but the srresnet + vgg19-5,4 loss)

you can train a net from scratch: (optionally start training with just the pixel-wise loss on the resnet part: python srresnet.py --image-dir traindir --cuda --pretraining --images 16384 --batchSize 16)

(use --pretrained modelfile.pth to continue from a pretraining or previous run for example) python srresnet.py --image-dir traindir --cuda --images 16384 --batchSize 16

and then inference with the arguments: --pretrained model/model_epoch_80.pth --testing --test-image BSDS300/images/train/100075.jpg

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