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@seanbenhur
Last active September 2, 2020 11:44
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# Load the test dataset
test_dataset = SiameseDataset(training_csv=testing_csv,training_dir=testing_dir,
transform=transforms.Compose([transforms.Resize((105,105)),
transforms.ToTensor()
])
)
test_dataloader = DataLoader(test_dataset,num_workers=6,batch_size=1,shuffle=True)
#test the network
count=0
for i, data in enumerate(test_dataloader,0):
x0, x1 , label = data
concat = torch.cat((x0,x1),0)
output1,output2 = model(x0.to(device),x1.to(device))
eucledian_distance = F.pairwise_distance(output1, output2)
if label==torch.FloatTensor([[0]]):
label="Original Pair Of Signature"
else:
label="Forged Pair Of Signature"
imshow(torchvision.utils.make_grid(concat))
print("Predicted Eucledian Distance:-",eucledian_distance.item())
print("Actual Label:-",label)
count=count+1
if count ==10:
break
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