Add torch.Tensor checks and pip badges (#3368)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

ultralytics/yolo/data/dataloaders/stream_loaders.py

@@ -301,11 +301,23 @@ class LoadTensor:
         self.paths = [getattr(im, 'filename', f'image{i}.jpg') for i, im in enumerate(im0)]
 
     @staticmethod
-    def _single_check(im):
-        """Validate and format an image to numpy array."""
-        if len(im.shape) < 4:
-            LOGGER.warning('WARNING ⚠️ torch.Tensor inputs should be BCHW format, i.e. shape(1,3,640,640).')
-            im = im.unsqueeze(0)
+    def _single_check(im, stride=32):
+        """Validate and format an image to torch.Tensor."""
+        s = f'WARNING ⚠️ torch.Tensor inputs should be BCHW i.e. shape(1, 3, 640, 640) ' \
+            f'divisible by stride {stride}. Input shape{tuple(im.shape)} is incompatible.'
+        if len(im.shape) != 4:
+            if len(im.shape) == 3:
+                LOGGER.warning(s)
+                im = im.unsqueeze(0)
+            else:
+                raise ValueError(s)
+        if im.shape[2] % stride or im.shape[3] % stride:
+            raise ValueError(s)
+        if im.max() > 1.0:
+            LOGGER.warning(f'WARNING ⚠️ torch.Tensor inputs should be normalized 0.0-1.0 but max value is {im.max()}. '
+                           f'Dividing input by 255.')
+            im = im.float() / 255.0
+
         return im
 
     def __iter__(self):