回传数据解析，兼容v5和v10

ultralytics/models/yolo/obb/train.py

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+# Ultralytics YOLO 🚀, AGPL-3.0 license
+
+from copy import copy
+
+from ultralytics.models import yolo
+from ultralytics.nn.tasks import OBBModel
+from ultralytics.utils import DEFAULT_CFG, RANK
+
+
+class OBBTrainer(yolo.detect.DetectionTrainer):
+    """
+    A class extending the DetectionTrainer class for training based on an Oriented Bounding Box (OBB) model.
+
+    Example:
+        ```python
+        from ultralytics.models.yolo.obb import OBBTrainer
+
+        args = dict(model='yolov8n-obb.pt', data='dota8.yaml', epochs=3)
+        trainer = OBBTrainer(overrides=args)
+        trainer.train()
+        ```
+    """
+
+    def __init__(self, cfg=DEFAULT_CFG, overrides=None, _callbacks=None):
+        """Initialize a OBBTrainer object with given arguments."""
+        if overrides is None:
+            overrides = {}
+        overrides["task"] = "obb"
+        super().__init__(cfg, overrides, _callbacks)
+
+    def get_model(self, cfg=None, weights=None, verbose=True):
+        """Return OBBModel initialized with specified config and weights."""
+        model = OBBModel(cfg, ch=3, nc=self.data["nc"], verbose=verbose and RANK == -1)
+        if weights:
+            model.load(weights)
+
+        return model
+
+    def get_validator(self):
+        """Return an instance of OBBValidator for validation of YOLO model."""
+        self.loss_names = "box_loss", "cls_loss", "dfl_loss"
+        return yolo.obb.OBBValidator(self.test_loader, save_dir=self.save_dir, args=copy(self.args))