fix VOC references

Author: ellisbrown

test.py

@@ -7,9 +7,9 @@
 import torch.backends.cudnn as cudnn
 import torchvision.transforms as transforms
 from torch.autograd import Variable
-from data import VOCroot, VOC_CLASSES as labelmap
+from data import VOC_ROOT, VOC_CLASSES as labelmap
 from PIL import Image
-from data import AnnotationTransform, VOCDetection, BaseTransform, VOC_CLASSES
+from data import VOCAnnotationTransform, VOCDetection, BaseTransform, VOC_CLASSES
 import torch.utils.data as data
 from ssd import build_ssd
 
@@ -20,12 +20,16 @@
                     help='Dir to save results')
 parser.add_argument('--visual_threshold', default=0.6, type=float,
                     help='Final confidence threshold')
-parser.add_argument('--cuda', default=False, type=bool,
+parser.add_argument('--cuda', default=True, type=bool,
                     help='Use cuda to train model')
-parser.add_argument('--voc_root', default=VOCroot, help='Location of VOC root directory')
-
+parser.add_argument('--voc_root', default=VOC_ROOT, help='Location of VOC root directory')
 args = parser.parse_args()
 
+if args.cuda and torch.cuda.is_available():
+    torch.set_default_tensor_type('torch.cuda.FloatTensor')
+else:
+    torch.set_default_tensor_type('torch.FloatTensor')
+
 if not os.path.exists(args.save_folder):
     os.mkdir(args.save_folder)
 
@@ -71,19 +75,22 @@ def test_net(save_folder, net, cuda, testset, transform, thresh):
                 j += 1
 
 
-if __name__ == '__main__':
+def test_voc():
     # load net
     num_classes = len(VOC_CLASSES) + 1 # +1 background
     net = build_ssd('test', 300, num_classes) # initialize SSD
     net.load_state_dict(torch.load(args.trained_model))
     net.eval()
     print('Finished loading model!')
     # load data
-    testset = VOCDetection(args.voc_root, [('2007', 'test')], None, AnnotationTransform())
+    testset = VOCDetection(args.voc_root, [('2007', 'test')], None, VOCAnnotationTransform())
     if args.cuda:
         net = net.cuda()
         cudnn.benchmark = True
     # evaluation
     test_net(args.save_folder, net, args.cuda, testset,
              BaseTransform(net.size, (104, 117, 123)),
              thresh=args.visual_threshold)
+
+if __name__ == '__main__':
+    test_voc()