jWUddlmZddlmZddlmZddlmZddlm Z ddl m Z d gZ e eed <gd Zdd edededede f dZ dd ededededededede fdZdS))Any)_CompiledModule) detection)reparameterize) PreProcessor)DetectionPredictordetection_predictorARCHS) db_resnet34 db_resnet50db_mobilenet_v3_largelinknet_resnet18linknet_resnet34linknet_resnet50 fast_tiny fast_small fast_baseTarch pretrainedassume_straight_pageskwargsreturnc \t|trw|tvrtd|dt j|||dd|}t|tjrt|}nztj tj tjtg}t|t|stdt||}||_||j_|dd|d|jd|d<|d|jd|d<|d d |d <t%t'|jd d dfi||}|S) Nzunknown architecture ''pretrained_backboneT)rrrzunknown architecture: meanstd batch_sizer input_shaper ) isinstancestrr ValueErrorr__dict__getFASTrDBNetLinkNetrtupletyper postprocessorpopcfgr r)rrrr_model allowed_archs predictors ]/var/www/html/Carbon-Document/venv/lib/python3.11/site-packages/doctr/models/detection/zoo.py _predictorr3 s$K u  =d===>> >#D)! & +@$ G G"7    fin - - ,#F++F#)*;Y^_] $m 4 455 DBd4jjBBCC C'<$5J2 JJ$d+++ZZ 6(:;;F6NJJufj&788F5M!::lA66F<"VZ .qrr2==f==I rFpreserve_aspect_ratio symmetric_padr c (td||||||d|S)aText detection architecture. >>> import numpy as np >>> from doctr.models import detection_predictor >>> model = detection_predictor(arch='db_resnet50', pretrained=True) >>> input_page = (255 * np.random.rand(600, 800, 3)).astype(np.uint8) >>> out = model([input_page]) Args: arch: name of the architecture or model itself to use (e.g. 'db_resnet50') pretrained: If True, returns a model pre-trained on our text detection dataset assume_straight_pages: If True, fit straight boxes to the page preserve_aspect_ratio: If True, pad the input document image to preserve the aspect ratio before running the detection model on it symmetric_pad: if True, pad the image symmetrically instead of padding at the bottom-right batch_size: number of samples the model processes in parallel **kwargs: optional keyword arguments passed to the architecture Returns: Detection predictor )rrrr5r6r )r3)rrrr5r6r rs r2r r Ds<<   33#      r4N)T)rFTTTr)typingrdoctr.models.utilsrrdetection.fastr preprocessorrr1r __all__listr#__annotations__r boolr3intr r8r4r2rCsa ......++++++'''''')))))) ! Cy   !!S!d!4!Z]!bt!!!!J"&"& && && & &  &  &&&&&&&&r4