ultralytics 8.0.92 updates and fixes (#2361)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Yonghye Kwon <developer.0hye@gmail.com>
Co-authored-by: introvin <vinod.4166@gmail.com>
Co-authored-by: marinmarcillat <58145636+marinmarcillat@users.noreply.github.com>
Co-authored-by: BIGBOSS-FOX <47949596+BIGBOSS-FOX@users.noreply.github.com>

ultralytics/__init__.py

@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = '8.0.91'
+__version__ = '8.0.92'
 
 from ultralytics.hub import start
 from ultralytics.vit.sam import SAM

ultralytics/tracker/track.py

@@ -47,7 +47,7 @@ def on_predict_postprocess_end(predictor):
         tracks = predictor.trackers[i].update(det, im0s[i])
         if len(tracks) == 0:
             continue
-        idx = tracks[:, -1].tolist()
+        idx = tracks[:, -1].astype(int)
         predictor.results[i] = predictor.results[i][idx]
         predictor.results[i].update(boxes=torch.as_tensor(tracks[:, :-1]))
 

ultralytics/vit/sam/modules/mask_generator.py

@@ -82,8 +82,8 @@ class SamAutomaticMaskGenerator:
             memory.
         """
 
-        assert (points_per_side is None) != (point_grids is
-                                             None), 'Exactly one of points_per_side or point_grid must be provided.'
+        assert (points_per_side is None) != (point_grids is None), \
+            'Exactly one of points_per_side or point_grid must be provided.'
         if points_per_side is not None:
             self.point_grids = build_all_layer_point_grids(
                 points_per_side,

ultralytics/yolo/engine/predictor.py

@@ -115,10 +115,8 @@ class BasePredictor:
             im (torch.Tensor | List(np.ndarray)): (N, 3, h, w) for tensor, [(h, w, 3) x N] for list.
         """
         if not isinstance(im, torch.Tensor):
-            auto = all(x.shape == im[0].shape for x in im) and self.model.pt
-            if not auto:
-                LOGGER.warning(
-                    'WARNING ⚠️ Source shapes differ. For optimal performance supply similarly-shaped sources.')
+            same_shapes = all(x.shape == im[0].shape for x in im)
+            auto = same_shapes and self.model.pt
             im = np.stack([LetterBox(self.imgsz, auto=auto, stride=self.model.stride)(image=x) for x in im])
             im = im[..., ::-1].transpose((0, 3, 1, 2))  # BGR to RGB, BHWC to BCHW, (n, 3, h, w)
             im = np.ascontiguousarray(im)  # contiguous

ultralytics/yolo/utils/__init__.py

@@ -259,13 +259,14 @@ def yaml_save(file='data.yaml', data=None):
         # Create parent directories if they don't exist
         file.parent.mkdir(parents=True, exist_ok=True)
 
+    # Convert Path objects to strings
+    for k, v in data.items():
+        if isinstance(v, Path):
+            dict[k] = str(v)
+
+    # Dump data to file in YAML format
     with open(file, 'w') as f:
-        # Dump data to file in YAML format, converting Path objects to strings
-        yaml.safe_dump({k: str(v) if isinstance(v, Path) else v
-                        for k, v in data.items()},
-                       f,
-                       sort_keys=False,
-                       allow_unicode=True)
+        yaml.safe_dump(data, f, sort_keys=False, allow_unicode=True)
 
 
 def yaml_load(file='data.yaml', append_filename=False):
@@ -759,7 +760,7 @@ ENVIRONMENT = 'Colab' if is_colab() else 'Kaggle' if is_kaggle() else 'Jupyter'
 TESTS_RUNNING = is_pytest_running() or is_github_actions_ci()
 set_sentry()
 
-# OpenCV Multilanguage-friendly functions ------------------------------------------------------------------------------------
+# OpenCV Multilanguage-friendly functions ------------------------------------------------------------------------------
 imshow_ = cv2.imshow  # copy to avoid recursion errors
 
 

ultralytics/yolo/utils/plotting.py

@@ -481,9 +481,6 @@ def feature_visualization(x, module_type, stage, n=32, save_dir=Path('runs/detec
         stage (int): Module stage within the model.
         n (int, optional): Maximum number of feature maps to plot. Defaults to 32.
         save_dir (Path, optional): Directory to save results. Defaults to Path('runs/detect/exp').
-
-    Returns:
-        None: This function does not return any value; it saves the visualization to the specified directory.
     """
     for m in ['Detect', 'Pose', 'Segment']:
         if m in module_type:

ultralytics/yolo/v8/detect/train.py

@@ -212,7 +212,6 @@ class Loss:
             pred_scores.detach().sigmoid(), (pred_bboxes.detach() * stride_tensor).type(gt_bboxes.dtype),
             anchor_points * stride_tensor, gt_labels, gt_bboxes, mask_gt)
 
-        target_bboxes /= stride_tensor
         target_scores_sum = max(target_scores.sum(), 1)
 
         # cls loss
@@ -221,6 +220,7 @@ class Loss:
 
         # bbox loss
         if fg_mask.sum():
+            target_bboxes /= stride_tensor
             loss[0], loss[2] = self.bbox_loss(pred_distri, pred_bboxes, anchor_points, target_bboxes, target_scores,
                                               target_scores_sum, fg_mask)