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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))
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