updates

train.py

@@ -40,8 +40,10 @@ def train(
 
     lr0 = 0.001
     cutoff = -1  # backbone reaches to cutoff layer
+    start_epoch = 0
+    best_loss = float('inf')
     if resume:
-        checkpoint = torch.load(latest, map_location='cpu')
+        checkpoint = torch.load('weights/yolov3.pt', map_location='cpu')
 
         # Load weights to resume from
         model.load_state_dict(checkpoint['model'])
@@ -65,9 +67,6 @@ def train(
         del checkpoint  # current, saved
 
     else:
-        start_epoch = 0
-        best_loss = float('inf')
-
         # Initialize model with backbone (optional)
         if cfg.endswith('yolov3.cfg'):
             load_darknet_weights(model, weights + 'darknet53.conv.74')