{-jsY2ddlmZmZmZmZmZddlZddlm Z ddl m Z ddl m Z ddlmZdd lmZmZdd lmZd d lmZd d lmZd dlmZmZmZmZmZmZddl m!Z!ej"GddeZ#e ddGddeZ$dS))AnyDictListOptionalUnionN)logging)pipeline_requires_extra)ImageBatchSampler) ReadImage) HPIConfigPaddlePredictorOption) benchmark)(AutoParallelImageSimpleInferencePipeline) BasePipeline) CropByPolys SortPolyBoxes SortQuadBoxescal_ocr_word_boxconvert_points_to_boxes rotate_image) OCRResultceZdZdZddddddddedeedeedeeeefd eed e d ee eeefe fd dffd Z de ejde ed e ejfdZded e fdZdee dee dee d efdZ d"deedeedeedeedeedeed efdZ d#de ee eeje ejfdee dee dee deedeedeedeedeedeedeed ee d efd!ZxZS)$ _OCRPipelinez OCR PipelineNFdeviceengine engine_config pp_optionuse_hpip hpi_configconfigrr r!r"r#r$returnc tjd5||||||d||dd|_|jrF|didddi} || |_|dd|_|jrF|d id d d i} || |_|d id d di} |d|_ |j dkr| dd|_ | dd|_ | dd|_ | dd|_ | dd|_| dd|_| dd|_t#|_t'd |_n|j d!kr| dd"|_ | dd#|_ | dd|_ | dd$|_ | dd|_| dd%|_| dd|_t+|_t'd& |_n't-d'|j || |j |j |j |j |j|j|j(|_|d id)d d*i} | d+d,|_| d-d.|_| dd|_|| |j/|_t9|d0d12|_t=d34|_dS)6aInitializes the OCR pipeline. Args: config (Dict): Configuration dictionary containing various settings. 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`. ruse_doc_preprocessorT SubPipelinesDocPreprocessorpipeline_config_errorz+config error for doc_preprocessor_pipeline!use_textline_orientation SubModulesTextLineOrientationmodel_config_errorz,config error for textline_orientation_model! TextDetectionz config error for text_det_model! text_typegenerallimit_side_leni limit_typemaxmax_side_limitithreshg333333? box_threshg333333? input_shapeN unclip_ratiog@quad) det_box_typesealiming?g?polyzUnsupported text type {})r3r4r6r7r8r:r9TextRecognitionz config error for text_rec_model! score_threshrreturn_word_boxF)r9 batch_sizer)rCBGR)format) super__init__getr(create_pipelinedoc_preprocessor_pipeliner, create_modeltextline_orientation_modelr1text_det_limit_side_lentext_det_limit_typetext_det_max_side_limittext_det_threshtext_det_box_threshr9text_det_unclip_ratior _sort_boxesr_crop_by_polysr ValueErrorrEtext_det_modeltext_rec_score_threshrBtext_rec_modelr batch_samplerr img_reader)selfr%rr r!r"r#r$kwargsdoc_preprocessor_configtextline_orientation_configtext_det_configtext_rec_config __class__s h/var/www/html/banglarbhumi/venv/lib/python3.11/site-packages/paddlex/inference/pipelines/ocr/pipeline.pyrHz_OCRPipeline.__init__*sc2  '!      %+JJ/Et$L$L!  $ &,jj&D&D&H&H!+-Z'' # .2-A-A'..D *)/ 3Mt(T(T%  ( *0**\2*F*F*J*J%%'UV++ '/3.?.?+//D +!**\266:: 24VW   , >Y & &+:+>+>?OQT+U+UD ('6':':<'O'OD $+:+>+>?OQU+V+VD (#2#6#6x#E#ED '6':':<'M'MD $.22=$GGD )8)<)<^S)Q)QD &,D "-6"B"B"BD   ^v % %+:+>+>?OQT+U+UD ('6':':<'O'OD $+:+>+>?OQU+V+VD (#2#6#6x#E#ED '6':':<'M'MD $)8)<)<^S)Q)QD &.22=$GGD ,D "-6"B"B"BD  7>>t~NNOO O"// 7/7'/3(0   !**\266::  !#E F  &5%8%8%K%K".223DeLL*..}dCC"// )90  /&**\ST:U:UVVV#5111image_array_listrotate_angle_listcLt|t|ks+Jdt|dt|d|D]}|dvs Jd|g}t||D]/\}}|dz}t||}||0|S)a Rotate the given image arrays by their corresponding angles. 0 corresponds to 0 degrees, 1 corresponds to 180 degrees. Args: image_array_list (List[np.ndarray]): A list of input image arrays to be rotated. rotate_angle_list (List[int]): A list of rotation indicators (0 or 1). 0 means rotate by 0 degrees 1 means rotate by 180 degrees Returns: List[np.ndarray]: A list of rotated image arrays. Raises: AssertionError: If any rotate_angle is not 0 or 1. AssertionError: If the lengths of input lists don't match. zLength of image_array_list (z*) must match length of rotate_angle_list ())rrz&rotate_angle must be 0 or 1, now it's )lenziprappend) r\rerfanglerotated_images image_arrayrotate_indicator rotate_angle rotated_images rcrz_OCRPipeline.rotate_images(#$$ ) )     E#.>*?*? E EknpAlBlB E E E   ' U UEF???$TU$T$T????-01ACT-U-U 1 1 )K)+c1L(lCCM  ! !- 0 0 0 0rdmodel_settingsc|dr|jstjddS|dr|jstjddSdS)a8 Check if the input parameters are valid based on the initialized models. Args: model_info_params(Dict): A dictionary containing input parameters. Returns: bool: True if all required models are initialized according to input parameters, False otherwise. r(zRSet use_doc_preprocessor, but the models for doc preprocessor are not initialized.Fr,z^Set use_textline_orientation, but the models for use_textline_orientation are not initialized.T)r(r errorr,)r\rss rccheck_model_settings_validz'_OCRPipeline.check_model_settings_validsz 0 1 $:S  Md   5 5 6 1  Mp   5trduse_doc_orientation_classifyuse_doc_unwarpingr,ch| ||j}n |dus|durd}nd}||j}t||S)a Get the model settings based on the provided parameters or default values. Args: use_doc_orientation_classify (Optional[bool]): Whether to use document orientation classification. use_doc_unwarping (Optional[bool]): Whether to use document unwarping. use_textline_orientation (Optional[bool]): Whether to use textline orientation. Returns: dict: A dictionary containing the model settings. NTF)r(r,)r(r,dict)r\rwrxr,r(s rcget_model_settingsz_OCRPipeline.get_model_settingssm" ( /4E4M#'#< +t337HD7P7P'+$$',$ # +'+'D $!5%=    rdrNrOrPrQrRrSc||j}||j}||j}||j}||j}||j}t ||||||S)a  Get text detection parameters. If a parameter is None, its default value from the instance will be used. Args: text_det_limit_side_len (Optional[int]): The maximum side length of the text box. text_det_limit_type (Optional[str]): The type of limit to apply to the text box. text_det_max_side_limit (Optional[int]): The maximum side length of the text box. text_det_thresh (Optional[float]): The threshold for text detection. text_det_box_thresh (Optional[float]): The threshold for the bounding box. text_det_unclip_ratio (Optional[float]): The ratio for unclipping the text box. Returns: dict: A dictionary containing the text detection parameters. N)r3r4r7r6r8r:)rNrOrPrQrRrSrz)r\rNrOrPrQrRrSs rcget_text_det_paramsz _OCRPipeline.get_text_det_paramss2 # *&*&B #  &"&":  " *&*&B #  ""2O  &"&":  ($($> !2*"2*.     rdinputrXrBc #D )*+,K|||++sddiV||||| | , j j t |D]\} }|j}+dr&t |||}n d|D}d|D}tj |fi,}d|D*fd *D*+ , fd t|j |j|*D} r|D] }g|d <g|d < ttt!|}*fd |D}|rg}dg}|D]}t||*|)g}g}t)*|D]\\}}|jdkrL|jddkr;|jddkr*||||]|*|<|||d<||||dt!|z+dr6d|D}||}ndgt!|z}t |D])\}}||}|||||dz|d<*t |D]\}}|||||dz)||}*|}dt )D} t1| d}!)fd|!D}"t |" D]\}}#|!|d}$|#| |$d<tt!| D]4}%| |%d}#|#d kr rt5|#dd||%|#dd\}&}'|d |&|d |'|d|#ddn!|d|#d|d|#d|d |#d!|d"||%6|D]g}jd#kr2t9|d"}(|(|d$< rd%|d D|d&<nt;jg|d$<t?|VhdS)'aQ Predict OCR results based on input images or arrays with optional preprocessing steps. Args: input (Union[str, list[str], np.ndarray, list[np.ndarray]]): Input image of pdf path(s) or numpy array(s). use_doc_orientation_classify (Optional[bool]): Whether to use document orientation classification. use_doc_unwarping (Optional[bool]): Whether to use document unwarping. use_textline_orientation (Optional[bool]): Whether to use textline orientation prediction. text_det_limit_side_len (Optional[int]): Maximum side length for text detection. text_det_limit_type (Optional[str]): Type of limit to apply for text detection. text_det_max_side_limit (Optional[int]): Maximum side length for text detection. text_det_thresh (Optional[float]): Threshold for text detection. text_det_box_thresh (Optional[float]): Threshold for text detection boxes. text_det_unclip_ratio (Optional[float]): Ratio for unclipping text detection boxes. text_rec_score_thresh (Optional[float]): Score threshold for text recognition. return_word_box (Optional[bool]): Whether to return word boxes along with recognized texts. Returns: OCRResult: Generator yielding OCR results for each input image. ruz0the input params for model settings are invalid!Nr()rwrxcg|]}d|iS output_imgrF).0arrs rc z(_OCRPipeline.predict..hs+X+X+XC\3,?+X+X+Xrdcg|] }|d SrrFritems rcrz(_OCRPipeline.predict..js*''''+\"'''rdcg|] }|d S)dt_polysrFrs rcrz(_OCRPipeline.predict..rsFFF$T*-FFFrdc:g|]}|SrF)rT)rrr\s rcrz(_OCRPipeline.predict..ts'NNNT--d33NNNrdcDg|]\}}}}||||j ggggd S)) input_path page_indexdoc_preprocessor_resrrstext_det_paramsr1rXrB rec_texts rec_scores rec_polys vis_fonts)r1) rrrrrrsrBr\rrXs rcrz(_OCRPipeline.predict..vse KJ ,@(#-",,@ (&4'6!%-B'6!#"$!#!#rd text_wordtext_word_regioncFg|]}t|dk|S)r)rj)ridx dt_polys_lists rcrz(_OCRPipeline.predict..s0MMMs]35G1H1H11L1Ls1L1L1Lrdrrrr,cg|]M}ttj|dtjdNS) class_ids)dtyper)intnpasarrayint64ravel)rtextline_angle_infos rcrz(_OCRPipeline.predict..sd    0 J 3K @#egga)   rdtextline_orientation_anglescjg|]0\}}||jdt|jdz d1S)rr) sub_img_id sub_img_ratio)shapefloat)rimg_idsub_imgs rcrz(_OCRPipeline.predict..sW))) ,FG+1-4]1-=gmTUFV@W@W-W)))rdc|dS)NrrF)xs rcz&_OCRPipeline.predict..s ?9Krd)keyc,g|]}|dS)rrF)rrall_subs_of_imgs rcrz(_OCRPipeline.predict..s/***=>,8***rd)rBrrec_res rec_scorerec_textrrrvis_fontrr2 rec_boxesc,g|]}t|SrF)r)rlines rcrz(_OCRPipeline.predict..s0222 $4D99222rdtext_word_boxes) r{rvr}rXrB enumeraterZr[ instanceslistrKrWrk input_paths page_indexesrangerjrUsizerrlextendrMrsortedrYrr1rrarrayr)-r\r~rwrxr,rNrOrPrQrRrSrXrB_ batch_data image_arraysdoc_preprocessor_resultsdoc_preprocessor_images det_resultsresultsresindicesall_subs_of_imgs chunk_indicesr filtered_subsfiltered_polysrr?anglesirsub_img_info_listsorted_subs_infosorted_subs_of_imgrrsnoword_box_content_list word_box_listrrrrsrs-` `` @@@@rcpredictz_OCRPipeline.predict$sF00 (*;=U  ..~>> PNO O O O22 #  #   !    ! 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