o W h@sddlmZmZddlmZddlmZddlmZmZddl m Z m Z m Z ddl mZGdd d e eZGd d d eZGd d d e eZGddde eZdS))copydeepcopy)SegmentationTrainer) YOLOESegModel) DEFAULT_CFGRANK) YOLOETrainerYOLOETrainerFromScratchYOLOEVPTrainer)YOLOESegValidatorcs:eZdZdZeddffdd Zd ddZdd ZZS) YOLOESegTrainera Trainer class for YOLOE segmentation models. This class combines YOLOETrainer and SegmentationTrainer to provide training functionality specifically for YOLOE segmentation models. Attributes: cfg (dict): Configuration dictionary with training parameters. overrides (dict): Dictionary with parameter overrides. _callbacks (list): List of callback functions for training events. Ncs |duri}t|||dS)a Initialize the YOLOESegTrainer class. This class combines YOLOETrainer and SegmentationTrainer to provide training functionality specifically for YOLOE segmentation models. Args: cfg (Dict): Configuration dictionary with training parameters. overrides (Dict, optional): Dictionary with parameter overrides. _callbacks (List, optional): List of callback functions for training events. N)super__init__)selfcfg overrides _callbacks __class__[/var/www/vscode/kcb/lib/python3.10/site-packages/ultralytics/models/yolo/yoloe/train_seg.pyrs zYOLOESegTrainer.__init__TcCsNtt|tr |dn||jdt|jdd|otdkd}|r%|||S)a Return YOLOESegModel initialized with specified config and weights. Args: cfg (dict | str): Model configuration dictionary or YAML file path. weights (str, optional): Path to pretrained weights file. verbose (bool): Whether to display model information. Returns: (YOLOESegModel): Initialized YOLOE segmentation model. yaml_filechannelsncPchrverbose)r isinstancedictdataminrload)rrweightsrmodelrrr get_model+s  zYOLOESegTrainer.get_modelcCs"d|_t|j|jt|j|jdS)z Create and return a validator for YOLOE segmentation model evaluation. Returns: (YOLOESegValidator): Validator for YOLOE segmentation models. )boxsegclsdfl)save_dirargsr) loss_namesr test_loaderr,rr- callbacks)rrrr get_validatorDszYOLOESegTrainer.get_validatorNNT) __name__ __module__ __qualname____doc__rrr'r1 __classcell__rrrrr s  r c@seZdZdZdddZdS)YOLOEPESegTrainerz Fine-tune YOLOESeg model in linear probing way. This trainer specializes in fine-tuning YOLOESeg models using a linear probing approach, which involves freezing most of the model and only training specific layers. NTcCs:tt|tr |dn||jd|jd|otdkd}|jd`|dus(Jd|r/|||t |jd }| |}| |||jd |jt|jdjd d d |jdjd d <t|jdjd d d |jdjd d <t|jdjd d d |jdjd d <|`||S) a Return YOLOESegModel initialized with specified config and weights for linear probing. Args: cfg (dict | str): Model configuration dictionary or YAML file path. weights (str, optional): Path to pretrained weights file. verbose (bool): Whether to display model information. Returns: (YOLOESegModel): Initialized YOLOE segmentation model configured for linear probing. rrrrrNz7Pretrained weights must be provided for linear probing.namesrTr)rr r!r"rr&savper$evallistvalues get_text_pe set_classesfusepercv3requires_grad_train)rrr%rr&r9tperrrr'Ys*     ...zYOLOEPESegTrainer.get_modelr2)r3r4r5r6r'rrrrr8Qsr8c@eZdZdZdS)YOLOESegTrainerFromScratchz,Trainer for YOLOE segmentation from scratch.Nr3r4r5r6rrrrrHrHc@rG)YOLOESegVPTrainerz'Trainer for YOLOE segmentation with VP.NrIrrrrrKrJrKN)rrultralytics.models.yolo.segmentrultralytics.nn.tasksrultralytics.utilsrrrEr r r valr r r8rHrKrrrrs   C3