diff --git a/util/misc.py b/util/misc.py
index 6d4d076..bcf7282 100644
--- a/util/misc.py
+++ b/util/misc.py
@@ -27,7 +27,7 @@
 
 # needed due to empty tensor bug in pytorch and torchvision 0.5
 import torchvision
-if float(torchvision.__version__[:3]) < 0.5:
+if float(torchvision.__version__.split('.')[1]) < 5:
     import math
     from torchvision.ops.misc import _NewEmptyTensorOp
     def _check_size_scale_factor(dim, size, scale_factor):
@@ -54,7 +54,7 @@ def _output_size(dim, input, size, scale_factor):
         return [
             int(math.floor(input.size(i + 2) * scale_factors[i])) for i in range(dim)
         ]
-elif float(torchvision.__version__[:3]) < 0.7:
+elif float(torchvision.__version__.split('.')[1]) < 7:
     from torchvision.ops import _new_empty_tensor
     from torchvision.ops.misc import _output_size
 
@@ -487,7 +487,7 @@ def interpolate(input, size=None, scale_factor=None, mode="nearest", align_corne
     This will eventually be supported natively by PyTorch, and this
     class can go away.
     """
-    if float(torchvision.__version__[:3]) < 0.7:
+    if float(torchvision.__version__.split('.')[1]) < 7:
         if input.numel() > 0:
             return torch.nn.functional.interpolate(
                 input, size, scale_factor, mode, align_corners
@@ -495,7 +495,7 @@ class can go away.
 
         output_shape = _output_size(2, input, size, scale_factor)
         output_shape = list(input.shape[:-2]) + list(output_shape)
-        if float(torchvision.__version__[:3]) < 0.5:
+        if float(torchvision.__version__.split('.')[1]) < 5:
             return _NewEmptyTensorOp.apply(input, output_shape)
         return _new_empty_tensor(input, output_shape)
     else: