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update srgan
Browse files
models/SRGAN/srgan-cvprj.ipynb
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models/SRGAN/srgan-dl-prj.ipynb
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@@ -1,3 +0,0 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:4eb72ac34eeb3831604a783a87d65fe237d7ef6279dce4d99224ffa92f1211b3
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size 12001858
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models/SRGAN/srgan.py
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@@ -42,7 +42,7 @@ class GeneratorResnet(nn.Module):
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]
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self.upsampling = nn.Sequential(*upsampling)
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self.conv3 = nn.
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def forward(self, x):
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out1 = self.conv1(x)
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@@ -51,7 +51,7 @@ class GeneratorResnet(nn.Module):
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out = torch.add(out1, out2)
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out = self.upsampling(out)
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out = self.conv3(out)
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return out
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def inference(self, x):
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"""
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@@ -62,7 +62,7 @@ class GeneratorResnet(nn.Module):
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x = ToTensor()(x).unsqueeze(0)
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x = self.forward(x)
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x = Image.fromarray((x.squeeze(0).permute(1, 2, 0).detach().numpy() * 255).astype('uint8'))
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return
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def test(self, x):
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"""
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]
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self.upsampling = nn.Sequential(*upsampling)
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self.conv3 = nn.Conv2d(64, out_channels, kernel_size=9, stride=1, padding=4)
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def forward(self, x):
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out1 = self.conv1(x)
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out = torch.add(out1, out2)
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out = self.upsampling(out)
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out = self.conv3(out)
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return out
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def inference(self, x):
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"""
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x = ToTensor()(x).unsqueeze(0)
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x = self.forward(x)
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x = Image.fromarray((x.squeeze(0).permute(1, 2, 0).detach().numpy() * 255).astype('uint8'))
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return x
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def test(self, x):
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"""
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models/SRGAN/srgan_checkpoint.pth
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@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:252142cce821babfd7718b8a9ecb6c795e642d90fe4ccc69072c9317dc4a8982
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size 6336551
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