Fix LoadStreams final frame bug (#4387)

Co-authored-by: Nadim Bou Alwan <64587372+nadinator@users.noreply.github.com>

ultralytics/cfg/__init__.py

@@ -442,5 +442,5 @@ def copy_default_cfg():
 
 
 if __name__ == '__main__':
-    # Example Usage: entrypoint(debug='yolo predict model=yolov8n.pt')
+    # Example: entrypoint(debug='yolo predict model=yolov8n.pt')
     entrypoint(debug='')

ultralytics/data/converter.py

@@ -36,11 +36,12 @@ def convert_coco(labels_dir='../coco/annotations/', use_segments=False, use_keyp
         use_keypoints (bool, optional): Whether to include keypoint annotations in the output.
         cls91to80 (bool, optional): Whether to map 91 COCO class IDs to the corresponding 80 COCO class IDs.
 
-    Raises:
-        FileNotFoundError: If the labels_dir path does not exist.
+    Example:
+        ```python
+        from ultralytics.data.converter import convert_coco
 
-    Example Usage:
-        convert_coco(labels_dir='../coco/annotations/', use_segments=True, use_keypoints=True, cls91to80=True)
+        convert_coco('../datasets/coco/annotations/', use_segments=True, use_keypoints=False, cls91to80=True)
+        ```
 
     Output:
         Generates output files in the specified output directory.

ultralytics/data/loaders.py

@@ -79,19 +79,18 @@ class LoadStreams:
     def update(self, i, cap, stream):
         """Read stream `i` frames in daemon thread."""
         n, f = 0, self.frames[i]  # frame number, frame array
-        while self.running and cap.isOpened() and n < f:
+        while self.running and cap.isOpened() and n < (f - 1):
             # Only read a new frame if the buffer is empty
             if not self.imgs[i]:
                 n += 1
                 cap.grab()  # .read() = .grab() followed by .retrieve()
                 if n % self.vid_stride == 0:
                     success, im = cap.retrieve()
-                    if success:
-                        self.imgs[i].append(im)  # add image to buffer
-                    else:
+                    if not success:
+                        im = np.zeros(self.shape[i], dtype=np.uint8)
                         LOGGER.warning('WARNING ⚠️ Video stream unresponsive, please check your IP camera connection.')
-                        self.imgs[i].append(np.zeros(self.shape[i]))
                         cap.open(stream)  # re-open stream if signal was lost
+                    self.imgs[i].append(im)  # add image to buffer
             else:
                 time.sleep(0.01)  # wait until the buffer is empty
 

ultralytics/engine/exporter.py

@@ -463,6 +463,7 @@ class Exporter:
         yaml_save(f / 'metadata.yaml', self.metadata)  # add metadata.yaml
         return str(f), None
 
+    @try_export
     def export_coreml(self, prefix=colorstr('CoreML:')):
         """YOLOv8 CoreML export."""
         mlmodel = self.args.format.lower() == 'mlmodel'  # legacy *.mlmodel export format requested

ultralytics/nn/modules/conv.py

@@ -175,15 +175,6 @@ class RepConv(nn.Module):
         kernelid, biasid = self._fuse_bn_tensor(self.bn)
         return kernel3x3 + self._pad_1x1_to_3x3_tensor(kernel1x1) + kernelid, bias3x3 + bias1x1 + biasid
 
-    def _avg_to_3x3_tensor(self, avgp):
-        channels = self.c1
-        groups = self.g
-        kernel_size = avgp.kernel_size
-        input_dim = channels // groups
-        k = torch.zeros((channels, input_dim, kernel_size, kernel_size))
-        k[np.arange(channels), np.tile(np.arange(input_dim), groups), :, :] = 1.0 / kernel_size ** 2
-        return k
-
     def _pad_1x1_to_3x3_tensor(self, kernel1x1):
         if kernel1x1 is None:
             return 0

ultralytics/utils/checks.py

@@ -437,11 +437,17 @@ def check_amp(model):
     Args:
         model (nn.Module): A YOLOv8 model instance.
 
+    Example:
+        ```python
+        from ultralytics import YOLO
+        from ultralytics.utils.checks import check_amp
+
+        model = YOLO('yolov8n.pt').model.cuda()
+        check_amp(model)
+        ```
+
     Returns:
         (bool): Returns True if the AMP functionality works correctly with YOLOv8 model, else False.
-
-    Raises:
-        AssertionError: If the AMP checks fail, indicating anomalies with the AMP functionality on the system.
     """
     device = next(model.parameters()).device  # get model device
     if device.type in ('cpu', 'mps'):