test_sign.py

# 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