o W h @sLddlmZddlmZddlmZddlmZmZGdddejj Z dS))copy)yolo)OBBModel) DEFAULT_CFGRANKcs:eZdZdZeddffdd Zd ddZdd ZZS) OBBTraineraw A class extending the DetectionTrainer class for training based on an Oriented Bounding Box (OBB) model. Attributes: loss_names (Tuple[str]): Names of the loss components used during training. Methods: get_model: Return OBBModel initialized with specified config and weights. get_validator: Return an instance of OBBValidator for validation of YOLO model. Examples: >>> from ultralytics.models.yolo.obb import OBBTrainer >>> args = dict(model="yolo11n-obb.pt", data="dota8.yaml", epochs=3) >>> trainer = OBBTrainer(overrides=args) >>> trainer.train() Ncs(|duri}d|d<t|||dS)a Initialize an OBBTrainer object for training Oriented Bounding Box (OBB) models. This trainer extends the DetectionTrainer class to specialize in training models that detect oriented bounding boxes. It automatically sets the task to 'obb' in the configuration. Args: cfg (dict, optional): Configuration dictionary for the trainer. Contains training parameters and model configuration. overrides (dict, optional): Dictionary of parameter overrides for the configuration. Any values here will take precedence over those in cfg. _callbacks (list, optional): List of callback functions to be invoked during training. Examples: >>> from ultralytics.models.yolo.obb import OBBTrainer >>> args = dict(model="yolo11n-obb.pt", data="dota8.yaml", epochs=3) >>> trainer = OBBTrainer(overrides=args) >>> trainer.train() Nobbtask)super__init__)selfcfg overrides _callbacks __class__U/var/www/vscode/kcb/lib/python3.10/site-packages/ultralytics/models/yolo/obb/train.pyr szOBBTrainer.__init__TcCs6t||jd|jd|otdkd}|r|||S)a Return OBBModel initialized with specified config and weights. Args: cfg (str | dict | None): Model configuration. Can be a path to a YAML config file, a dictionary containing configuration parameters, or None to use default configuration. weights (str | Path | None): Path to pretrained weights file. If None, random initialization is used. verbose (bool): Whether to display model information during initialization. Returns: (OBBModel): Initialized OBBModel with the specified configuration and weights. Examples: >>> trainer = OBBTrainer() >>> model = trainer.get_model(cfg="yolov8n-obb.yaml", weights="yolov8n-obb.pt") ncchannels)rchverbose)rdatarload)r r weightsrmodelrrr get_model5s$ zOBBTrainer.get_modelcCs&d|_tjj|j|jt|j|jdS)z@Return an instance of OBBValidator for validation of YOLO model.)box_losscls_lossdfl_loss)save_dirargsr) loss_namesrr OBBValidator test_loaderr!rr" callbacks)r rrr get_validatorLszOBBTrainer.get_validator)NNT) __name__ __module__ __qualname____doc__rr rr' __classcell__rrrrr s  rN) rultralytics.modelsrultralytics.nn.tasksrultralytics.utilsrrdetectDetectionTrainerrrrrrs