transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])])
if args.dataset == 'Pose_300W_LP':
pose_dataset = datasets.Pose_300W_LP(args.data_dir, args.filename_list, transformations)
elif args.dataset == 'Pose_300W_LP_random_ds':
pose_dataset = datasets.Pose_300W_LP_random_ds(args.data_dir, args.filename_list, transformations)
elif args.dataset == 'AFLW2000':
pose_dataset = datasets.AFLW2000(args.data_dir, args.filename_list, transformations)
elif args.dataset == 'AFLW2000_ds':
pose_dataset = datasets.AFLW2000_ds(args.data_dir, args.filename_list, transformations)
elif args.dataset == 'BIWI':
pose_dataset = datasets.BIWI(args.data_dir, args.filename_list, transformations)
elif args.dataset == 'AFLW':
pose_dataset = datasets.AFLW(args.data_dir, args.filename_list, transformations)
elif args.dataset == 'AFLW_aug':
pose_dataset = datasets.AFLW_aug(args.data_dir, args.filename_list, transformations)
elif args.dataset == 'AFW':
pose_dataset = datasets.AFW(args.data_dir, args.filename_list, transformations)
else:
print 'Error: not a valid dataset name'
sys.exit()
test_loader = torch.utils.data.DataLoader(dataset=pose_dataset,
batch_size=args.batch_size,
num_workers=2)
model.cuda(gpu)
print 'Ready to test network.'
# Test the Model
model.eval() # Change model to 'eval' mode (BN uses moving mean/var).
transformations,
bin_width_degrees)
elif args.dataset == 'AFLW2000':
pose_dataset = datasets.AFLW2000(args.data_dir, args.filename_list,
transformations, bin_width_degrees)
elif args.dataset == 'AFLW2000_ds':
pose_dataset = datasets.AFLW2000_ds(args.data_dir, args.filename_list,
transformations, bin_width_degrees)
elif args.dataset == 'BIWI':
pose_dataset = datasets.BIWI(args.data_dir, args.filename_list,
transformations, bin_width_degrees)
elif args.dataset == 'AFLW':
pose_dataset = datasets.AFLW(args.data_dir, args.filename_list,
transformations, bin_width_degrees)
elif args.dataset == 'AFLW_aug':
pose_dataset = datasets.AFLW_aug(args.data_dir, args.filename_list,
transformations, bin_width_degrees)
elif args.dataset == 'AFW':
pose_dataset = datasets.AFW(args.data_dir, args.filename_list,
transformations, bin_width_degrees)
else:
print 'Error: not a valid dataset name'
sys.exit()
test_loader = torch.utils.data.DataLoader(dataset=pose_dataset,
batch_size=args.batch_size,
num_workers=2)
model.cuda(gpu)
print 'Ready to test network.'
# Test the Model
