Removed unecessary testing scripts

natanielruiz

2017-09-13 b2316888f61893aff1229c24002d903df79499cb

Removed unecessary testing scripts

 code/batch_testing_preangles.py

@@ -50,7 +50,7 @@
    # 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)


 code/test.py

@@ -34,6 +34,7 @@
    parser.add_argument('--save_viz', dest='save_viz', help='Save images with pose cube.',
          default=False, type=bool)
    parser.add_argument('--iter_ref', dest='iter_ref', default=1, type=int)
    parser.add_argument('--dataset', dest='dataset', help='Dataset type.', default='AFLW2000', type=str)

    args = parser.parse_args()

@@ -64,8 +65,18 @@
    transforms.RandomCrop(224), transforms.ToTensor(),
    transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])])

    pose_dataset = datasets.AFLW2000(args.data_dir, args.filename_list,
    if args.dataset == 'AFLW2000':
        pose_dataset = datasets.AFLW2000(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 == '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)

 code/test_AFLW.py

File was deleted

 code/test_AFLW_preangles.py

File was deleted

 code/test_biwi.py

File was deleted

 code/test_biwi_preangles.py

File was deleted

 code/test_preangles.py

@@ -33,6 +33,7 @@
          default=1, type=int)
    parser.add_argument('--save_viz', dest='save_viz', help='Save images with pose cube.',
          default=False, type=bool)
    parser.add_argument('--dataset', dest='dataset', help='Dataset type.', default='AFLW2000', type=str)

    args = parser.parse_args()

@@ -48,7 +49,7 @@
    # 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)

@@ -66,8 +67,18 @@
    transforms.RandomCrop(224), transforms.ToTensor(),
    transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])])

    pose_dataset = datasets.AFLW2000(args.data_dir, args.filename_list,
    if args.dataset == 'AFLW2000':
        pose_dataset = datasets.AFLW2000(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 == '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)