ultralytics 8.0.45 segment CUDA and DDP callback fixes (#1137)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>

ultralytics/yolo/engine/exporter.py

@@ -292,7 +292,10 @@ class Exporter:
     @try_export
     def _export_onnx(self, prefix=colorstr('ONNX:')):
         # YOLOv8 ONNX export
-        check_requirements('onnx>=1.12.0')
+        requirements = ['onnx>=1.12.0']
+        if self.args.simplify:
+            requirements += ['onnxsim', 'onnxruntime-gpu' if torch.cuda.is_available() else 'onnxruntime']
+        check_requirements(requirements)
         import onnx  # noqa
 
         LOGGER.info(f'\n{prefix} starting export with onnx {onnx.__version__}...')
@@ -326,7 +329,6 @@ class Exporter:
         # Simplify
         if self.args.simplify:
             try:
-                check_requirements(('onnxsim', 'onnxruntime-gpu' if torch.cuda.is_available() else 'onnxruntime'))
                 import onnxsim
 
                 LOGGER.info(f'{prefix} simplifying with onnxsim {onnxsim.__version__}...')
@@ -508,9 +510,8 @@ class Exporter:
         try:
             import tensorflow as tf  # noqa
         except ImportError:
-            check_requirements(
-                f"tensorflow{'-macos' if MACOS else '-aarch64' if ARM64 else '' if torch.cuda.is_available() else '-cpu'}"
-            )
+            cuda = torch.cuda.is_available()
+            check_requirements(f"tensorflow{'-macos' if MACOS else '-aarch64' if ARM64 else '' if cuda else '-cpu'}")
             import tensorflow as tf  # noqa
         check_requirements(('onnx', 'onnx2tf', 'sng4onnx', 'onnxsim', 'onnx_graphsurgeon', 'tflite_support',
                             'onnxruntime-gpu' if torch.cuda.is_available() else 'onnxruntime'),

ultralytics/yolo/engine/model.py

@@ -64,7 +64,7 @@ class YOLO:
             Performs prediction using the YOLO model.
 
     Returns:
-        list[ultralytics.yolo.engine.results.Results]: The prediction results.
+        list(ultralytics.yolo.engine.results.Results): The prediction results.
     """
 
     def __init__(self, model='yolov8n.pt') -> None:

ultralytics/yolo/engine/results.py

@@ -111,14 +111,14 @@ class Results:
 
         Args:
             show_conf (bool): Whether to show the detection confidence score.
-            line_width (float, optional): The line width of the bounding boxes. If None, it is automatically scaled to the image size.
-            font_size (float, optional): The font size of the text. If None, it is automatically scaled to the image size.
+            line_width (float, optional): The line width of the bounding boxes. If None, it is scaled to the image size.
+            font_size (float, optional): The font size of the text. If None, it is scaled to the image size.
             font (str): The font to use for the text.
             pil (bool): Whether to return the image as a PIL Image.
-            example (str): An example string to display in the plot. Useful for indicating the expected format of the output.
+            example (str): An example string to display. Useful for indicating the expected format of the output.
 
         Returns:
-            None or PIL Image: If `pil` is True, the image will be returned as a PIL Image. Otherwise, nothing is returned.
+            (None) or (PIL.Image): If `pil` is True, a PIL Image is returned. Otherwise, nothing is returned.
         """
         img = deepcopy(self.orig_img)
         annotator = Annotator(img, line_width, font_size, font, pil, example)
@@ -284,7 +284,7 @@ class Masks:
         orig_shape (tuple): Original image size, in the format (height, width).
 
     Properties:
-        segments (list): A list of segments which includes x, y, w, h, label, confidence, and mask of each detection masks.
+        segments (list): A list of segments which includes x, y, w, h, label, confidence, and mask of each detection.
 
     Methods:
         cpu(): Returns a copy of the masks tensor on CPU memory.

ultralytics/yolo/engine/trainer.py

@@ -181,7 +181,7 @@ class BaseTrainer:
                 LOGGER.info(f'Running DDP command {cmd}')
                 subprocess.run(cmd, check=True)
             except Exception as e:
-                LOGGER.warning(e)
+                raise e
             finally:
                 ddp_cleanup(self, str(file))
         else:

ultralytics/yolo/engine/validator.py

@@ -63,7 +63,6 @@ class BaseValidator:
             dataloader (torch.utils.data.DataLoader): Dataloader to be used for validation.
             save_dir (Path): Directory to save results.
             pbar (tqdm.tqdm): Progress bar for displaying progress.
-            logger (logging.Logger): Logger to log messages.
             args (SimpleNamespace): Configuration for the validator.
         """
         self.dataloader = dataloader