h\SSKJrJr SSKJr SSKJr SSKJr SSKJ r J r J r SSK J r "SS \ \5r"S S \5r"S S \ \5r"SS\ \5rg))copydeepcopy)SegmentationTrainer) YOLOESegModel)RANK) YOLOETrainerYOLOETrainerFromScratchYOLOEVPTrainer)YOLOESegValidatorc(\rSrSrSrSSjrSrSrg)YOLOESegTrainer a Trainer class for YOLOE segmentation models. This class combines YOLOETrainer and SegmentationTrainer to provide training functionality specifically for YOLOE segmentation models, enabling both object detection and instance segmentation capabilities. Attributes: cfg (dict): Configuration dictionary with training parameters. overrides (dict): Dictionary with parameter overrides. _callbacks (list): List of callback functions for training events. Nc[[U[5(aUSOUURS[ URSS5U=(a [ S:HS9nU(aUR U5 U$)a[ Return YOLOESegModel initialized with specified config and weights. Args: cfg (dict | str, optional): 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)selfcfgweightsrmodels a/home/james-whalen/.local/lib/python3.13/site-packages/ultralytics/models/yolo/yoloe/train_seg.py get_modelYOLOESegTrainer.get_modelsd *3 5 5C 3yy$499T?B'*    JJw  cSUl[URUR[ UR 5UR S9$)z Create and return a validator for YOLOE segmentation model evaluation. Returns: (YOLOESegValidator): Validator for YOLOE segmentation models. )boxsegclsdfl)save_dirargs _callbacks) loss_namesr test_loaderr+rr, callbacks)rs r" get_validatorYOLOESegTrainer.get_validator3s:5   t}}4 ?W[WeWe  r%)r.NNT)__name__ __module__ __qualname____firstlineno____doc__r#r1__static_attributes__r%r"rr s 2  r%rc"\rSrSrSrSSjrSrg)YOLOEPESegTrainer@ak 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 for efficient adaptation to new tasks. Attributes: data (dict): Dataset configuration containing channels, class names, and number of classes. Nc$[[U[5(aUSOUURSURSU=(a [S:HS9nUR S?UcS5eU(aURU5 UR5 [URSR55nURU5nURXV5 UR SRUR5 [UR SR SS 5R#S 5UR SR SS '[UR SR S S 5R#S 5UR SR S S '[UR SR S S 5R#S 5UR SR S S 'U?UR%5 U$) a Return YOLOESegModel initialized with specified config and weights for linear probing. Args: cfg (dict | str, optional): 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. rrrrrz7Pretrained weights must be provided for linear probing.namesrTr)rrrrrr!savperevallistvalues get_text_pe set_classesfusepercv3requires_grad_train)rrr rr!r?tpes r"r#YOLOEPESegTrainer.get_modelKs *3 5 5C 3yy$yy*   KKO !"]$]]"  JJw  TYYw'..01& %% BUXX&$,U[[_-@-@-CA-F$G$V$VW[$\ BAq!$,U[[_-@-@-CA-F$G$V$VW[$\ BAq!$,U[[_-@-@-CA-F$G$V$VW[$\ BAq! H  r%r:r3)r4r5r6r7r8r#r9r:r%r"r<r<@s (r%r<c\rSrSrSrSrg)YOLOESegTrainerFromScratchvzVTrainer for YOLOE segmentation models trained from scratch without pretrained weights.r:Nr4r5r6r7r8r9r:r%r"rOrOvs`r%rOc\rSrSrSrSrg)YOLOESegVPTrainer|zKTrainer for YOLOE segmentation models with Vision Prompt (VP) capabilities.r:NrQr:r%r"rSrS|sUr%rSN)rrultralytics.models.yolo.segmentrultralytics.nn.tasksrultralytics.utilsrrKr r r valr rr<rOrSr:r%r"rYsX ?."HH"0 l$70 f3+3l !8/  (B r%