| | |
|---|
| | | print 'Loading data.' |
|---|
| | | |
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| | | 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': |
|---|
| | |
|---|
| | | label_roll = labels[:,2].float() |
|---|
| | | |
|---|
| | | pre_yaw, pre_pitch, pre_roll, angles = model(images) |
|---|
| | | yaw = angles[args.iter_ref-1][:,0].cpu().data |
|---|
| | | pitch = angles[args.iter_ref-1][:,1].cpu().data |
|---|
| | | roll = angles[args.iter_ref-1][:,2].cpu().data |
|---|
| | | yaw = angles[-1][:,0].cpu().data |
|---|
| | | pitch = angles[-1][:,1].cpu().data |
|---|
| | | roll = angles[-1][:,2].cpu().data |
|---|
| | | |
|---|
| | | # Mean absolute error |
|---|
| | | yaw_error += torch.sum(torch.abs(yaw - label_yaw) * 3) |
|---|
