9imSSKJrJrJrJrJr SSKrSSKJ r SSK J r SSK J r SSKJr SS KJr S S KJr S S KJr \ R,"S S\55r\ "S5"SS\55rg))AnyDictListOptionalUnionN)pipeline_requires_extra)InstanceSegResult) benchmark) HPIConfig)PaddlePredictorOption)(AutoParallelImageSimpleInferencePipeline) BasePipelinec^\rSrSrSrSS\S\S\S\S\ \ \\\ 4\ 4S S4 U4S jjjr SS \ \\\\R \\R 4S \ \S4S \4S jjrSrU=r$)_InstanceSegmentationPipelinezInstance Segmentation PipelineNconfigdevice pp_optionuse_hpip hpi_configreturncr>[TU]X#XES9 USSnURU5UlUSUlg)ah Initializes the class with given configurations and options. Args: config (Dict): Configuration dictionary containing model and other parameters. device (str): The device to run the prediction on. Default is None. pp_option (PaddlePredictorOption): Options for PaddlePaddle predictor. Default is None. use_hpip (bool, optional): Whether to use the high-performance inference plugin (HPIP) by default. Defaults to False. hpi_config (Optional[Union[Dict[str, Any], HPIConfig]], optional): The default high-performance inference configuration dictionary. Defaults to None. )rrrr SubModulesInstanceSegmentation thresholdN)super__init__ create_modelinstance_segmentation_modelr)selfrrrrr"instance_segmentation_model_config __class__s z/var/www/html/land-doc-ocr/venv/lib/python3.13/site-packages/paddlex/inference/pipelines/instance_segmentation/pipeline.pyr &_InstanceSegmentationPipeline.__init__ sW*   .4L-A ". *,0+<+< ., (# URXS9ShvN gN7f)aPredicts instance segmentation results for the given input. Args: input (str | list[str] | np.ndarray | list[np.ndarray]): The input image(s) or path(s) to the images. threshold (Union[float, None]): The threshold value to filter out low-confidence predictions. Default is None. **kwargs: Additional keyword arguments that can be passed to the function. Returns: InstanceSegResult: The predicted instance segmentation results. )rN)r")r#r)rkwargss r&predict%_InstanceSegmentationPipeline.predictAs 33E3OOOs )r"r)NNFNN)__name__ __module__ __qualname____firstlineno____doc__rstrrboolrrrr r rnpndarrayfloatr r,__static_attributes__ __classcell__)r%s@r&rrs( +/AE III) I  I U4S>9#<=> I IIH)-PS$s)RZZbjj1AABP%P  PPr(rcvc.\rSrSrSr\S5rSrSrg)InstanceSegmentationPipelineTinstance_segmentationc[$r.)r)r#s r& _pipeline_cls*InstanceSegmentationPipeline._pipeline_clsXs,,r(c2USSRSS5$)Nrr batch_size)get)r#rs r&_get_batch_size,InstanceSegmentationPipeline._get_batch_size\s l#$:;?? aPPr(N) r/r0r1r2entitiespropertyrArGr9rIr(r&r=r=Ts&H --Qr(r=)typingrrrrrnumpyr6 utils.depsr #models.instance_segmentation.resultr utils.benchmarkr utils.hpir utils.pp_optionr _parallelrbaser time_methodsrr=rIr(r&rVsn432D("4@ 4PL4P4PnQ#KQQr(