49 lines
1.8 KiB
Python
49 lines
1.8 KiB
Python
# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
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from copy import copy
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from ultralytics.models import yolo
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from ultralytics.nn.tasks import OBBModel
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from ultralytics.utils import DEFAULT_CFG, RANK
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class OBBTrainer(yolo.detect.DetectionTrainer):
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"""
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A class extending the DetectionTrainer class for training based on an Oriented Bounding Box (OBB) model.
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Attributes:
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loss_names (Tuple[str]): Names of the loss components used during training.
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Methods:
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get_model: Return OBBModel initialized with specified config and weights.
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get_validator: Return an instance of OBBValidator for validation of YOLO model.
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Examples:
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>>> from ultralytics.models.yolo.obb import OBBTrainer
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>>> args = dict(model="yolo11n-obb.pt", data="dota8.yaml", epochs=3)
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>>> trainer = OBBTrainer(overrides=args)
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>>> trainer.train()
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"""
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def __init__(self, cfg=DEFAULT_CFG, overrides=None, _callbacks=None):
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"""Initialize a OBBTrainer object with given arguments."""
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if overrides is None:
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overrides = {}
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overrides["task"] = "obb"
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super().__init__(cfg, overrides, _callbacks)
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def get_model(self, cfg=None, weights=None, verbose=True):
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"""Return OBBModel initialized with specified config and weights."""
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model = OBBModel(cfg, ch=3, nc=self.data["nc"], verbose=verbose and RANK == -1)
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if weights:
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model.load(weights)
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return model
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def get_validator(self):
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"""Return an instance of OBBValidator for validation of YOLO model."""
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self.loss_names = "box_loss", "cls_loss", "dfl_loss"
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return yolo.obb.OBBValidator(
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self.test_loader, save_dir=self.save_dir, args=copy(self.args), _callbacks=self.callbacks
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)
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