updates

train.py

@@ -40,8 +40,6 @@ def train(
 
     # Initialize model
     model = Darknet(cfg, img_size).to(device)
-    # for m in model.modules():
-    #     weights_init_normal(m)  # set weight distributions
 
     # Optimizer
     lr0 = 0.001  # initial learning rate
@@ -56,7 +54,7 @@ def train(
     if resume:  # Load previously saved model
         if transfer:  # Transfer learning
             chkpt = torch.load(weights + 'yolov3.pt', map_location=device)
-            model.load_state_dict({k: v for k, v in chkpt['model'].items() if v.numel() > 1 and v.shape[0] != nf},
+            model.load_state_dict({k: v for k, v in chkpt['model'].items() if v.numel() > 1 and v.shape[0] != 255},
                                   strict=False)
             for p in model.parameters():
                 p.requires_grad = True if p.shape[0] == nf else False