| | |
| | | # ResNet101 with 3 outputs. |
| | | # model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 23, 3], 66) |
| | | # ResNet50 |
| | | model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 6, 3], 66) |
| | | model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 6, 3], 66, 0) |
| | | # ResNet18 |
| | | # model = hopenet.Hopenet(torchvision.models.resnet.BasicBlock, [2, 2, 2, 2], 66) |
| | | |
| | |
| | | print 'Loading data.' |
| | | |
| | | transformations = transforms.Compose([transforms.Scale(224), |
| | | transforms.RandomCrop(224), transforms.ToTensor(), |
| | | transforms.CenterCrop(224), transforms.ToTensor(), |
| | | transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])]) |
| | | |
| | | if args.dataset == 'AFLW2000': |