update test.py

test.py

@@ -23,6 +23,7 @@ def test(cfg,
          multi_label=True):
     # Initialize/load model and set device
     if model is None:
+        is_training = False
         device = torch_utils.select_device(opt.device, batch_size=batch_size)
         verbose = opt.task == 'test'
 
@@ -47,6 +48,7 @@ def test(cfg,
         if device.type != 'cpu' and torch.cuda.device_count() > 1:
             model = nn.DataParallel(model)
     else:  # called by train.py
+        is_training = True
         device = next(model.parameters()).device  # get model device
         verbose = False
 
@@ -61,7 +63,7 @@ def test(cfg,
 
     # Dataloader
     if dataloader is None:
-        dataset = LoadImagesAndLabels(path, imgsz, batch_size, rect=True, single_cls=opt.single_cls)
+        dataset = LoadImagesAndLabels(path, imgsz, batch_size, rect=True, single_cls=opt.single_cls, pad=0.5)
         batch_size = min(batch_size, len(dataset))
         dataloader = DataLoader(dataset,
                                 batch_size=batch_size,
@@ -91,7 +93,7 @@ def test(cfg,
             t0 += torch_utils.time_synchronized() - t
 
             # Compute loss
-            if hasattr(model, 'hyp'):  # if model has loss hyperparameters
+            if is_training:  # if model has loss hyperparameters
                 loss += compute_loss(train_out, targets, model)[1][:3]  # GIoU, obj, cls
 
             # Run NMS