Wpf(*dZddlZddlZddlmZmZddlmZddlmZddl m Z ddl m Z ddl mZdd lmZdd lmZdd lmZdd lmZdd lmZddlmZddlmZddlmZej Z!ej"Z#ej$Z%e j&Z'ej(Z)ej*Z+ej,Z-dZ.dZ/dZ0dZ1dZ2dZ3dZ4dZ5dZ6dZ7dZ8dZ9ej:GddZ;ej:Gdd ZGd&d'ej?Z@dS)(z%MediaPipe interactive segmenter task.N)ListOptional)packet_creator) packet_getter)image)!image_segmenter_graph_options_pb2)segmenter_options_pb2)keypoint base_options) task_info) doc_controls)base_vision_task_api)image_processing_options)vision_task_running_mode)render_data_pb2confidence_masksCONFIDENCE_MASKS category_mask CATEGORY_MASKimage_in image_outroi_inROI norm_rect_in NORM_RECTIMAGEzFmediapipe.tasks.vision.interactive_segmenter.InteractiveSegmenterGraphcheZdZUdZdZeeeje d<dZ eeje d<dS)InteractiveSegmenterResulta]Output result of InteractiveSegmenter. confidence_masks: multiple masks of float image where, for each mask, each pixel represents the prediction confidence, usually in the [0, 1] range. category_mask: a category mask of uint8 image where each pixel represents the class which the pixel in the original image was predicted to belong to. Nrr) __name__ __module__ __qualname____doc__rrr image_moduleImage__annotations__rs/var/www/html/nettyfy-visnx/env/lib/python3.11/site-packages/mediapipe/tasks/python/vision/interactive_segmenter.pyrr<sT:>HT,"456===04-,,-44444r(rc`eZdZUdZeed<dZeed<dZeed<e j de fdZ d S) InteractiveSegmenterOptionszOptions for the interactive segmenter task. Attributes: base_options: Base options for the interactive segmenter task. output_confidence_masks: Whether to output confidence masks. output_category_mask: Whether to output category mask. r Toutput_confidence_masksFoutput_category_maskreturnc|j}d|_t}t ||S)z8Generates an ImageSegmenterGraphOptions protobuf object.F)r segmenter_options)r to_pb2use_stream_mode_SegmenterOptionsProto _ImageSegmenterGraphOptionsProto)selfbase_options_protosegmenter_options_protos r)r1z"InteractiveSegmenterOptions.to_pb2YsK*1133).&466 +'1   r(N) r r!r"r# _BaseOptionsr&r,boolr-rdo_not_generate_docsr4r1r'r(r)r+r+Ksz"&4&&&$$$$$6%$r(r+cheZdZUdZGddejZeed<dZe e j ed<dS)RegionOfInterestz.The Region-Of-Interest (ROI) to interact with.ceZdZdZdZdS)RegionOfInterest.FormatrN)r r!r" UNSPECIFIEDKEYPOINTr'r(r)Formatr>isKHHHr(rBformatNr ) r r!r"r#enumEnumrBr&r rkeypoint_moduleNormalizedKeypointr'r(r)r<r<esg66ty ...;?(H_7 8?????r(r<roir.ct}||jtjjkrt d|jtjjkr^|jW|j }d|j _ |j }d|_ |jj|_|jj|_|Snt dt d)z1Converts region of interest to render data proto.Nz&RegionOfInterest format not specified.Tz7Please specify the Region-of-interest for segmentation.zUnrecognized format.)_RenderDataProtorCr<rBr@ ValueErrorrAr render_annotationsaddcolorrpoint normalizedxy)rHresult annotationrQs r)_convert_roi_to_render_datarWqs   &_ z%,888 ? @ @@ '.7 7 7  !.2244   ,.,. N O OO)***r(c eZdZdZededdfdZededdfdZ d de j d e d e e defd ZdS) InteractiveSegmenteraKClass that performs interactive segmentation on images. Users can represent user interaction through `RegionOfInterest`, which gives a hint to InteractiveSegmenter to perform segmentation focusing on the given region of interest. The API expects a TFLite model with mandatory TFLite Model Metadata. Input tensor: (kTfLiteUInt8/kTfLiteFloat32) - image input of size `[batch x height x width x channels]`. - batch inference is not supported (`batch` is required to be 1). - RGB and greyscale inputs are supported (`channels` is required to be 1 or 3). - if type is kTfLiteFloat32, NormalizationOptions are required to be attached to the metadata for input normalization. Output tensors: (kTfLiteUInt8/kTfLiteFloat32) - list of segmented masks. - if `output_type` is CATEGORY_MASK, uint8 Image, Image vector of size 1. - if `output_type` is CONFIDENCE_MASK, float32 Image list of size `channels`. - batch is always 1 An example of such model can be found at: https://tfhub.dev/tensorflow/lite-model/deeplabv3/1/metadata/2 model_pathr.clt|}t|}||S)aCreates an `InteractiveSegmenter` object from a TensorFlow Lite model and the default `InteractiveSegmenterOptions`. Note that the created `InteractiveSegmenter` instance is in image mode, for performing image segmentation on single image inputs. Args: model_path: Path to the model. Returns: `InteractiveSegmenter` object that's created from the model file and the default `InteractiveSegmenterOptions`. Raises: ValueError: If failed to create `InteractiveSegmenter` object from the provided file such as invalid file path. RuntimeError: If other types of error occurred. )model_asset_pathr )r8r+create_from_options)clsrZr optionss r)create_from_model_pathz+InteractiveSegmenter.create_from_model_paths8& << > &   I 3''U'CC   r(NrrHrc |||d}t|}|tt j|t t j|tt j| i}t}t|vr$tj |t|_t|vr$tj|t|_|S)aPerforms the actual segmentation task on the provided MediaPipe Image. The image can be of any size with format RGB. Args: image: MediaPipe Image. roi: Optional user-specified region of interest for segmentation. image_processing_options: Options for image processing. Returns: If the output_type is CATEGORY_MASK, the returned vector of images is per-category segmented image mask. If the output_type is CONFIDENCE_MASK, the returned vector of images contains only one confidence image mask. A segmentation result object that contains a list of segmentation masks as images. Raises: ValueError: If any of the input arguments is invalid. RuntimeError: If image segmentation failed to run. F) roi_allowed)convert_to_normalized_rectrW_process_image_datarrr create_imagert create_protorvr1rrmrget_image_listrro get_imager)r5rrHrnormalized_rectrender_data_protooutput_packetssegmentation_results r)segmentzInteractiveSegmenter.segments455 %U6O4C88--~:5AA.56GHH ;  " " $ $! ! /N566$66-:-I 6 7..*"^33*7*A 3 4++' r()N)r r!r"r# classmethodstrr`r+r]r$r%r<r_ImageProcessingOptionsrrr'r(r)rYrYs8,c,6L,,,;,,-/----;-fEI 11  1 1!))@ A 1 " 111111r(rY)Ar# dataclassesrDtypingrrmediapipe.pythonrr$mediapipe.python._framework_bindingsrr$/mediapipe.tasks.cc.vision.image_segmenter.protorr ,mediapipe.tasks.python.components.containersr rFmediapipe.tasks.python.corer base_options_moduler task_info_module1mediapipe.tasks.python.core.optional_dependenciesr"mediapipe.tasks.python.vision.corerrimage_processing_options_modulermediapipe.utilr BaseOptionsr8 RenderDatarKSegmenterOptionsr3ImageSegmenterGraphOptionsr4VisionTaskRunningModerxImageProcessingOptionsrTaskInforprmrlrornrrrjrtrsrvrurirq dataclassrr+r<rWBaseVisionTaskApirYr'r(r)rs,+ !!!!!!!!++++++******FFFFFF]]]]]]QQQQQQTTTTTTKKKKKKEEEEEEJJJJJJCCCCCCjjjjjjGGGGGG******". 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