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June 24, 2020 04:17
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Testing the model and show the result
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| # Show the images and the ground truth | |
| dataiter = iter(dataloaders['test']) | |
| images, labels = dataiter.next() | |
| imshow(torchvision.utils.make_grid(images)) | |
| print('GroundTruth: ', ', '.join('%5s' % class_names[x] for x in labels)) | |
| # Predict the model | |
| images = images.to(device) | |
| labels = images.to(device) | |
| output = model_resnet(images) | |
| _, predicted = torch.max(output, 1) | |
| print('Predicted: ', ', '.join('%5s' % class_names[x] for x in predicted)) |
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