changed data/loaders and engine/predictor so they accept 1 channel images for predictions

ultralytics/data/loaders.py

@@ -249,7 +249,7 @@ class LoadImages:
         else:
             # Read image
             self.count += 1
-            im0 = cv2.imread(path)  # BGR
+            im0 = cv2.imread(path, cv2.IMREAD_GRAYSCALE)  # BGR
             if im0 is None:
                 raise FileNotFoundError(f'Image Not Found {path}')
             s = f'image {self.count}/{self.nf} {path}: '

ultralytics/engine/predictor.py

@@ -122,7 +122,8 @@ class BasePredictor:
         not_tensor = not isinstance(im, torch.Tensor)
         if not_tensor:
             im = np.stack(self.pre_transform(im))
-            im = im[..., ::-1].transpose((0, 3, 1, 2))  # BGR to RGB, BHWC to BCHW, (n, 3, h, w)
+            im = np.expand_dims(im, -1)
+            im = im[..., ::].transpose((0, 3, 1, 2))  # BGR to RGB, BHWC to BCHW, (n, 3, h, w)
             im = np.ascontiguousarray(im)  # contiguous
             im = torch.from_numpy(im)