|hQddlmZddlmZddlmZmZmZmZddlm Z ddl m Z ddl m Z mZddlmZGdd e j"j$Zy ) )copy)Path)AnyDictOptionalUnion)yolo) PoseModel) DEFAULT_CFGLOGGER) plot_resultsc eZdZdZeddfdeeeefffd Z ddee ee eeeffdee ee fde de fd Zfd Zd Zd Zdeeefffd ZxZS) PoseTrainera A class extending the DetectionTrainer class for training YOLO pose estimation models. This trainer specializes in handling pose estimation tasks, managing model training, validation, and visualization of pose keypoints alongside bounding boxes. Attributes: args (dict): Configuration arguments for training. model (PoseModel): The pose estimation model being trained. data (dict): Dataset configuration including keypoint shape information. loss_names (tuple): Names of the loss components used in training. Methods: get_model: Retrieve a pose estimation model with specified configuration. set_model_attributes: Set keypoints shape attribute on the model. get_validator: Create a validator instance for model evaluation. plot_training_samples: Visualize training samples with keypoints. plot_metrics: Generate and save training/validation metric plots. get_dataset: Retrieve the dataset and ensure it contains required kpt_shape key. Examples: >>> from ultralytics.models.yolo.pose import PoseTrainer >>> args = dict(model="yolo11n-pose.pt", data="coco8-pose.yaml", epochs=3) >>> trainer = PoseTrainer(overrides=args) >>> trainer.train() N overridesc|i}d|d<t||||t|jjt r>|jjj dk(rtjdyyy)a8 Initialize a PoseTrainer object for training YOLO pose estimation models. This initializes a trainer specialized for pose estimation tasks, setting the task to 'pose' and handling specific configurations needed for keypoint detection models. Args: cfg (dict, optional): Default configuration dictionary containing training parameters. overrides (dict, optional): Dictionary of parameter overrides for the default configuration. _callbacks (list, optional): List of callback functions to be executed during training. Notes: This trainer will automatically set the task to 'pose' regardless of what is provided in overrides. A warning is issued when using Apple MPS device due to known bugs with pose models. Examples: >>> from ultralytics.models.yolo.pose import PoseTrainer >>> args = dict(model="yolo11n-pose.pt", data="coco8-pose.yaml", epochs=3) >>> trainer = PoseTrainer(overrides=args) >>> trainer.train() Nposetaskmpsz}Apple MPS known Pose bug. Recommend 'device=cpu' for Pose models. See https://github.com/ultralytics/ultralytics/issues/4031.) super__init__ isinstanceargsdevicestrlowerr warning)selfcfgr _callbacks __class__s a/var/www/html/test/engine/venv/lib/python3.12/site-packages/ultralytics/models/yolo/pose/train.pyrzPoseTrainer.__init__)st,  I" & i4 dii&& ,1A1A1G1G1IU1R NNN 2S ,rweightsverbosereturnct||jd|jd|jd|}|r|j||S)a Get pose estimation model with specified configuration and weights. Args: cfg (str | Path | dict, optional): Model configuration file path or dictionary. weights (str | Path, optional): Path to the model weights file. verbose (bool): Whether to display model information. Returns: (PoseModel): Initialized pose estimation model. ncchannels kpt_shape)r'chdata_kpt_shaper$)r dataload)rrr#r$models r! get_modelzPoseTrainer.get_modelJsK" DIIdO *(=diiXcNdnu   JJw  r"c^t||jd|j_y)z+Set keypoints shape attribute of PoseModel.r)N)rset_model_attributesr,r.r))rr s r!r1z PoseTrainer.set_model_attributescs# $&#yy5 r"cd|_tjj|j|j t |j|jS)z=Return an instance of the PoseValidator class for validation.)box_loss pose_loss kobj_losscls_lossdfl_loss)save_dirrr) loss_namesr r PoseValidator test_loaderr8rr callbacksrs r! get_validatorzPoseTrainer.get_validatorhsGVyy&&   t}}4 ?W[WeWe'  r"cHt|jd|jy)z!Plot training/validation metrics.T)fileron_plotN)r csvrAr=s r! plot_metricszPoseTrainer.plot_metricsos$((t||Dr"crt|}d|vr#td|jjd|S)a/ Retrieve the dataset and ensure it contains the required `kpt_shape` key. Returns: (dict): A dictionary containing the training/validation/test dataset and category names. Raises: KeyError: If the `kpt_shape` key is not present in the dataset. r)zNo `kpt_shape` in the z1. See https://docs.ultralytics.com/datasets/pose/)r get_datasetKeyErrorrr,)rr,r s r!rEzPoseTrainer.get_datasetss>w"$ d "3DIINN3CCtuv v r")NNT)__name__ __module__ __qualname____doc__r rrrrrrrboolr r/r1r>rCrE __classcell__)r s@r!rr s6'd_c8DcN3KF;?.2  eCtCH~56 7%T *+   26  E T#s(^  r"rN)rpathlibrtypingrrrrultralytics.modelsr ultralytics.nn.tasksr ultralytics.utilsr r ultralytics.utils.plottingr detectDetectionTrainerrr"r!rVs7--#*13s$++..sr"