diff --git a/models/common.py b/models/common.py
index c898d94a921a..cfa688ba940b 100644
--- a/models/common.py
+++ b/models/common.py
@@ -387,13 +387,13 @@ def __init__(self, weights='yolov5s.pt', device=torch.device('cpu'), dnn=False,
             context = model.create_execution_context()
             bindings = OrderedDict()
             fp16 = False  # default updated below
-            dynamic_input = False
+            dynamic = False
             for index in range(model.num_bindings):
                 name = model.get_binding_name(index)
                 dtype = trt.nptype(model.get_binding_dtype(index))
                 if model.binding_is_input(index):
                     if -1 in tuple(model.get_binding_shape(index)):  # dynamic
-                        dynamic_input = True
+                        dynamic = True
                         context.set_binding_shape(index, tuple(model.get_profile_shape(0, index)[2]))
                     if dtype == np.float16:
                         fp16 = True
@@ -471,12 +471,14 @@ def forward(self, im, augment=False, visualize=False, val=False):
             im = im.cpu().numpy()  # FP32
             y = self.executable_network([im])[self.output_layer]
         elif self.engine:  # TensorRT
-            if im.shape != self.bindings['images'].shape and self.dynamic_input:
-                self.context.set_binding_shape(self.model.get_binding_index('images'), im.shape)  # reshape if dynamic
+            if self.dynamic and im.shape != self.bindings['images'].shape:
+                i_in, i_out = (self.model.get_binding_index(x) for x in ('images', 'output'))
+                self.context.set_binding_shape(i_in, im.shape)  # reshape if dynamic
                 self.bindings['images'] = self.bindings['images']._replace(shape=im.shape)
-            assert im.shape == self.bindings['images'].shape, (
-                f"image shape {im.shape} exceeds model max shape {self.bindings['images'].shape}" if self.dynamic_input
-                else f"image shape {im.shape} does not match model shape {self.bindings['images'].shape}")
+                self.bindings['output'].data.resize_(tuple(self.context.get_binding_shape(i_out)))
+            s = self.bindings['images'].shape
+            assert im.shape == s, f"image shape {im.shape} " + \
+                                  f"exceeds model max shape {s}" if self.dynamic else f"does not match model shape {s}"
             self.binding_addrs['images'] = int(im.data_ptr())
             self.context.execute_v2(list(self.binding_addrs.values()))
             y = self.bindings['output'].data