o 0jD@sddlmZmZmZmZmZmZmZddlZ ddl m Z ddl m Z mZddlmZddlmZd d lmZd d lmZejGd d d eZe dGdddeZdS))AnyDictListLiteralOptionalTupleUnionN)pipeline_requires_extra) HPIConfigPaddlePredictorOption) SegResult) benchmark)(AutoParallelImageSimpleInferencePipeline) BasePipelinecseZdZdZddddddddedeedeedeeeefd eed e d ee eeefe fd dffd dZ dde ee eeje ejfde eddeeefd efddZZS)_SemanticSegmentationPipelinezSemantic Segmentation PipelineNFdeviceengine engine_config pp_optionuse_hpip hpi_configconfigrrrrrrreturnc sFtjd||||||d||dd} || |_| d|_dS)aInitializes the semantic segmentation 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 SubModulesSemanticSegmentation target_sizeN)super__init__Z create_modelsemantic_segmentation_modelr) selfrrrrrrrkwargsZ"semantic_segmentation_model_config __class__r {/var/www/html/Deteccion_Ine/venv/lib/python3.10/site-packages/paddlex/inference/pipelines/semantic_segmentation/pipeline.pyr"s" z&_SemanticSegmentationPipeline.__init__inputrcks|j||dEdHdS)a^Predicts semantic 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. target_size (Literal[-1] | None | int | tuple[int]): The Image size model used to do prediction. Default is None. If it's set to -1, the original image size will be used. If it's set to None, the previous level's setting will be used. If it's set to an integer value, the image will be rescaled to the size of (value, value). If it's set to a tuple of two integers, the image will be rescaled to the size of (height, width). **kwargs: Additional keyword arguments that can be passed to the function. Returns: SegResult: The predicted segmentation results. )rN)r#)r$r)rr%r r r(predictJsz%_SemanticSegmentationPipeline.predictN)__name__ __module__ __qualname____doc__rrstrrr boolrr r"rnpZndarrayrintrrr+ __classcell__r r r&r(rsB  .rZcvc@s$eZdZdZeddZddZdS)SemanticSegmentationPipelineZsemantic_segmentationcCstSr,)r)r$r r r( _pipeline_clsesz*SemanticSegmentationPipeline._pipeline_clscCs|ddddS)NrrZ batch_size)get)r$rr r r(_get_batch_sizeisz,SemanticSegmentationPipeline._get_batch_sizeN)r-r.r/entitiespropertyr7r:r r r r(r6as   r6)typingrrrrrrrnumpyr3Z utils.depsr modelsr r Z#models.semantic_segmentation.resultrZutils.benchmarkrZ _parallelrbaserZ time_methodsrr6r r r r(s$     E