o 0j9@sddlmZmZmZmZmZddlZddlm Z ddl m Z m Z ddl mZddlmZd d lmZd d lmZejGd d d eZe dGdddeZdS))AnyDictListOptionalUnionN)pipeline_requires_extra) HPIConfigPaddlePredictorOption) DetResult) benchmark)(AutoParallelImageSimpleInferencePipeline) BasePipelinecseZdZdZddddddddedeedeedeeeefd eed e d ee eeefe fd dffd dZ dde ee eeje ejfde deeefefd efddZZS)_SmallObjectDetectionPipelinezSmall Object Detection PipelineNFdeviceengine engine_config pp_optionuse_hpip hpi_configconfigrrrrrrreturnc sFtjd||||||d||dd} || |_| d|_dS)a Initializes the small object detection pipeline. Args: config (Dict): Configuration dictionary containing model and other parameters. device (Optional[str], optional): The device to use for prediction. Defaults to `None`. engine (Optional[str], optional): Inference engine. Defaults to `None`. engine_config (Optional[Dict[str, Any]], optional): Engine-specific config. Defaults to `None`. pp_option (Optional[PaddlePredictorOption], optional): Paddle predictor options. Defaults to `None`. use_hpip (bool, optional): Whether to use HPIP. Defaults to `False`. hpi_config (Optional[Union[Dict[str, Any], HPIConfig]], optional): HPIP configuration. Defaults to `None`. r SubModulesSmallObjectDetection thresholdN)super__init__Z create_modelsmall_object_detection_modelr) selfrrrrrrrkwargsZ#small_object_detection_model_config __class__r|/var/www/html/Deteccion_Ine/venv/lib/python3.10/site-packages/paddlex/inference/pipelines/small_object_detection/pipeline.pyr s" z&_SmallObjectDetectionPipeline.__init__inputrcks|j||dEdHdS)aoPredicts small object detection results for the given input. Args: input (str | list[str] | np.ndarray | list[np.ndarray]): The input image(s) or path(s) to the images. threshold (Optional[float]): The threshold value to filter out low-confidence predictions. Default is None. If None, it will use the default threshold specified during initialization. If a dictionary is provided, it should have integer keys corresponding to the class IDs and float values representing the respective thresholds for each class. If a single float value is provided, it will be used as the threshold for all classes. **kwargs: Additional keyword arguments that can be passed to the function. Returns: DetResult: The predicted small object detection results. )rN)r!)r"r'rr#rrr&predictJsz%_SmallObjectDetectionPipeline.predictN)__name__ __module__ __qualname____doc__rrstrrr boolrr r rnpZndarrayintfloatr r( __classcell__rrr$r&rsB  .rZcvc@s$eZdZdZeddZddZdS)SmallObjectDetectionPipelineZsmall_object_detectioncCstSr))r)r"rrr& _pipeline_clsesz*SmallObjectDetectionPipeline._pipeline_clscCs|ddddS)NrrZ batch_size)get)r"rrrr&_get_batch_sizeisz,SmallObjectDetectionPipeline._get_batch_sizeN)r*r+r,entitiespropertyr5r8rrrr&r4as   r4)typingrrrrrnumpyr0Z utils.depsrmodelsr r Zmodels.object_detection.resultr Zutils.benchmarkr Z _parallelrbaserZ time_methodsrr4rrrr&s     E