o ॵi @sddlmZmZmZmZddlmZddlmZddl m Z ddl m Z m Z ddlmZddlmZmZddlmZdd lmZdd lmZeZejejejd ejejejd Gd d d e ZdS))AnyDictOptionalUnion) Pipelines) OutputKeys)DetectionOutput)InputPipeline) PIPELINES) LoadImage Preprocessor)Tasks'show_image_object_detection_auto_result) get_logger) module_namecseZdZ ddedeeffdd Zdedeee fffdd Z deee fde eee fe ffd d Z d e eee fe fdeee ffd dZdddZZS)TinynasDetectionPipelineNmodel preprocessorc stjd||d|dS)aObject detection pipeline, currently only for the tinynas-detection model. Args: model: A str format model id or model local dir to build the model instance from. preprocessor: A preprocessor instance to preprocess the data, if None, the pipeline will try to build the preprocessor according to the configuration.json file. kwargs: The args needed by the `Pipeline` class. )rrN)super__init__)selfrrkwargs __class__rf/home/ubuntu/.local/lib/python3.10/site-packages/modelscope/pipelines/cv/tinynas_detection_pipeline.pyrs z!TinynasDetectionPipeline.__init__inputreturncst|}t|SN)r convert_to_ndarrayr preprocess)rrimgrrrr"(s  z#TinynasDetectionPipeline.preprocesscCs||dS)a[The forward method of this pipeline. Args: input: The input data output from the `preprocess` procedure. Returns: A model output, either in a dict format, or in a standard `DetectionOutput` dataclass. If outputs a dict, these keys are needed: class_ids (`Tensor`, *optional*): class id for each object. boxes (`Tensor`, *optional*): Bounding box for each detected object in [left, top, right, bottom] format. scores (`Tensor`, *optional*): Detection score for each object. r#)r)rrrrrforward,sz TinynasDetectionPipeline.forwardinputscCsX|d|d|d}}}|durtjgtjgtjgi}|Stj|tj|tj|i}|S)Nboxesscores class_ids)rSCORESLABELSBOXES)rr%bboxesr'labelsoutputsrrr postprocess>s  z$TinynasDetectionPipeline.postprocesscCst|||dSr r)rimg_pathresult save_pathrrr show_resultQsz$TinynasDetectionPipeline.show_resultr )__name__ __module__ __qualname__strrr rr rrr"rrr$r/r3 __classcell__rrrrrs.     rN)typingrrrrmodelscope.metainformodelscope.outputsrmodelscope.outputs.cv_outputsrmodelscope.pipelines.baser r modelscope.pipelines.builderr modelscope.preprocessorsr r modelscope.utils.constantrmodelscope.utils.cv.image_utilsrmodelscope.utils.loggerrloggerregister_module domain_specific_object_detectiontinynas_detectionimage_object_detectionrrrrrs&