o V hG@sTdZddlmZddlmZddlmZddlmZddl m Z Gdd d eZ d S) ag Interface for Baidu's RT-DETR, a Vision Transformer-based real-time object detector. RT-DETR offers real-time performance and high accuracy, excelling in accelerated backends like CUDA with TensorRT. It features an efficient hybrid encoder and IoU-aware query selection for enhanced detection accuracy. References: https://arxiv.org/pdf/2304.08069.pdf )Model)RTDETRDetectionModel)RTDETRPredictor) RTDETRTrainer)RTDETRValidatorcs>eZdZdZd deddffdd Zedefdd ZZ S) RTDETRa Interface for Baidu's RT-DETR model, a Vision Transformer-based real-time object detector. This model provides real-time performance with high accuracy. It supports efficient hybrid encoding, IoU-aware query selection, and adaptable inference speed. Attributes: model (str): Path to the pre-trained model. Examples: >>> from ultralytics import RTDETR >>> model = RTDETR("rtdetr-l.pt") >>> results = model("image.jpg") rtdetr-l.ptmodelreturnNcstj|dddS)a0 Initialize the RT-DETR model with the given pre-trained model file. Args: model (str): Path to the pre-trained model. Supports .pt, .yaml, and .yml formats. Raises: NotImplementedError: If the model file extension is not 'pt', 'yaml', or 'yml'. detect)r taskN)super__init__)selfr  __class__S/var/www/vscode/kcb/lib/python3.10/site-packages/ultralytics/models/rtdetr/model.pyr$s zRTDETR.__init__cCsdttttdiS)z Returns a task map for RT-DETR, associating tasks with corresponding Ultralytics classes. Returns: (dict): A dictionary mapping task names to Ultralytics task classes for the RT-DETR model. r ) predictor validatortrainerr )rrrr)rrrrtask_map0s zRTDETR.task_map)r ) __name__ __module__ __qualname____doc__strrpropertydictr __classcell__rrrrrs  rN) rultralytics.engine.modelrultralytics.nn.tasksrpredictrtrainrvalrrrrrrs