dj/ dZddlZddlZddlZddlmZmZddlmZ ddlm Z ddl m Z ddl mZddl mZdd l mZdd l mZdd l mZdd lmZdd lmZddlmZddlmZddlmZej@Z!ejDZ#ejHZ%e jLZ'GddejPZ)GddejPZ*ejVdejXe*ejXejZfejVdejZejZejXe)ejXej\ejXej^fejHdejXej^gdejVdejZffZ0ejbGddZ2ejbGddZ3ejbGddZ4Gdd Z5y)!z%MediaPipe interactive segmenter task.N)ListOptional)keypoint) keypoint_c)async_result_dispatcher base_options)base_options_c)mediapipe_c_bindings)mediapipe_c_utils)serial_dispatcher) doc_controls)image_segmenter)image)image_processing_options)image_processing_options_cceZdZdZGddej Zdejfdeje jfdeje jfdejfgZ y) RegionOfInterestC.The Region-Of-Interest (ROI) to interact with.ceZdZdZdZdZy)RegionOfInterestC.FormatrN)__name__ __module__ __qualname__ UNSPECIFIEDKEYPOINTSCRIBBLEv/root/repos/pocs/video-evals/.venv/lib/python3.12/site-packages/mediapipe/tasks/python/vision/interactive_segmenter.pyFormatr,sKHHr!r#formatrscribblescribble_countN)rrr__doc__enumIntEnumr#ctypesc_intPOINTERkeypoint_c_moduleNormalizedKeypointCc_uint32_fields_r r!r"rr)sj6t|| >6>>"3"G"GHI>6>>"3"G"GHI) (r!rcbeZdZdZdej fdejfdejfgZy)InteractiveSegmenterOptionsCz>The MediaPipe Tasks InteractiveSegmenterOptions CTypes struct.r output_confidence_masksoutput_category_maskN) rrrr'base_options_c_module BaseOptionsCr*c_boolr0r r!r"r2r29s5F,99: &--0v}}-(r!r2MpInteractiveSegmenterCreate"MpInteractiveSegmenterSegmentImage!MpInteractiveSegmenterCloseResultMpInteractiveSegmenterCloseceZdZUdZdZeeeje d<dZ eeje d<e e jdejddfdZy)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. Nconfidence_masks category_maskc_resultreturnc|tjj|}||j|jS)zIConverts a C ImageSegmenterResult to a Python InteractiveSegmenterResult.)r>r?)rImageSegmenterResult from_ctypesr>r?)clsr@ base_results r"rDz&InteractiveSegmenterResult.from_ctypesqs9 "66BB8LK $55!// r!)rrrr'r>rr image_moduleImage__annotations__r? classmethodrdo_not_generate_docsrImageSegmenterResultCrDr r!r"r=r=cso:>HT,"4"456=04-,,,-4$$$::#%r!r=cbeZdZUdZeed<dZeed<dZeed<e jde fdZ y ) InteractiveSegmenterOptionsaOptions for the interactive segmenter task. Attributes: base_options: Base options for the interactive segmenter task. running_mode: The running mode of the task. output_confidence_masks: Whether to output confidence masks. output_category_mask: Whether to output category mask. result_callback: The callback function that is invoked synchronously when the current thread is idle. r Tr3Fr4rAcvt|jj|j|jS)z8Generates an InteractiveSegmenterOptionsC ctypes struct.)r r3r4)r2r to_ctypesr3r4selfs r"rPz%InteractiveSegmenterOptions.to_ctypess5 (&&002 $ < <!66 r!N) rrrr' _BaseOptionsrIr3boolr4rrKr2rPr r!r"rNrN~sE "&4&$$$$5%r!rNceZdZUdZGddej Zeed<dZe e jed<e jdefdZy) RegionOfInterestrceZdZdZdZy)RegionOfInterest.FormatrrN)rrrrrr r!r"r#rXs KHr!r#r$NrrAc|j|jtjjk(r t d|jtjj k(r{t|jj}tj|jj|jj}tj||_|St dt d)zeZdZUdZej ed<ejed<e jed<dej dejde jfdZ e d e d dfd Ze d ed dfd Z ddej$dedeed efdZdZdZdZdZy)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 _lib_handle _dispatcherlibhandle dispatcherc.||_||_||_y)z.Initializes the `InteractiveSegmenter` object.N)rfrgrh)rRrirjrks r"__init__zInteractiveSegmenter.__init__sDIDL!Dr! model_pathrAcTt|}t|}|j|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)rSrNcreate_from_options)rErnr optionss r"create_from_model_pathz+InteractiveSegmenter.create_from_model_paths)& z:InteractiveSegmenter.create_from_options..sAr!) converter) r load_shared_library_CTYPES_SIGNATURES_AsyncResultDispatcherrPr*c_void_pr8byref)rErrrirkctypes_optionssegmenter_handles r"rqz(InteractiveSegmenter.create_from_optionssr"  2 23E FC'+>J&&(N($$ ^$fll3C&D s$j 11r!Nrroirc |j}|j}tj}|r#t j |jnd}|j j|j|t j ||t j |tj|}|j jt j ||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. N) _image_ptrrPrrLr*r}rfr9rgr=rDr:) rRrrrc_imager_r@ options_c py_results r"segmentzInteractiveSegmenter.segments4G MMOE446H $  -779:   II00  U X +66x@III// X0FG r!c|jsy|jj|jd|_|jj |jj y)z Closes the InteractiveSegmenter.N)rgrfr;rhcloserQs r"rzInteractiveSegmenter.closeEsI << II))$,,7DLIIOOr!c|S)z1Returns `self` upon entering the runtime context.r rQs r" __enter__zInteractiveSegmenter.__enter__Ns Kr!c*~~~|jy)zFShuts down the MediaPipe task instance on exit of the context manager.Nr)rRexc_type exc_value tracebacks r"__exit__zInteractiveSegmenter.__exit__Rs)YJJLr!c$|jyrvrrQs r"__del__zInteractiveSegmenter.__del__Ws JJLr!rv)rrrr'r SerialDispatcherrIr*r|rAsyncResultDispatcherrmrJstrrsrNrqrGrHrVr_ImageProcessingOptionsr=rrrrrr r!r"reres8 *** ??&<<< "  - - "oo "*?? ",c,6L,,,2/222<EI ,   , ,!))@ A , " ,\ r!re)6r'r* dataclassesr(typingrr,mediapipe.tasks.python.components.containersrrbrr-mediapipe.tasks.python.corerr base_options_moduler r5r r r 1mediapipe.tasks.python.core.optional_dependenciesrmediapipe.tasks.python.visionr"mediapipe.tasks.python.vision.corerrGrimage_processing_options_moduler!image_processing_options_c_module BaseOptionsrSImageProcessingOptionsr CFunction _CFunctionrr{ Structurerr2CStatusFunctionr,r|ImageProcessingOptionsCrLrz dataclassr=rNrVrer r!r"rs,  !TX?KO<99J9Djn".. 9PP  ( ( 0FF ((  6#3#3&%%& FNN7 8 FNN6?? + &%%, OO OO FNN, - FNN1II  FNN?@@ A   + == >?  &%%% 3@ 4 4 --->__r!