Update lib/models/YOLOP.py

lib/models/YOLOP.py

@@ -14,7 +14,7 @@ sys.path.append(os.getcwd())
 from lib.models.common import Conv, SPP, Bottleneck, BottleneckCSP, Focus, Concat, Detect, SharpenConv
 from torch.nn import Upsample
 #from lib.utils import check_anchor_order
-from lib.core.evaluate import SegmentationMetric
+#from lib.core.evaluate import SegmentationMetric
 #from lib.utils.utils import time_synchronized
 
 def check_anchor_order(m):
@@ -545,18 +545,3 @@ def get_net(cfg, **kwargs):
     m_block_cfg = YOLOP
     model = MCnet(m_block_cfg, **kwargs)
     return model
-
-
-if __name__ == "__main__":
-    from torch.utils.tensorboard import SummaryWriter
-    model = get_net(False)
-    input_ = torch.randn((1, 3, 256, 256))
-    gt_ = torch.rand((1, 2, 256, 256))
-    metric = SegmentationMetric(2)
-    model_out,SAD_out = model(input_)
-    detects, dring_area_seg, lane_line_seg = model_out
-    Da_fmap, LL_fmap = SAD_out
-    for det in detects:
-        print(det.shape)
-    print(dring_area_seg.shape)
-    print(lane_line_seg.shape)