82 lines
7.4 KiB
Plaintext
82 lines
7.4 KiB
Plaintext
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§—>j4& ã @ sj d Z ddlmZmZmZmZ ddlmZ ddlZ eG dd„ dƒƒZ
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G dd„ dƒZ d d
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„ Z e
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d krfe ƒ dS ) zD
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OCR Pipeline
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Extract all text from images for semantic geolocation
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é )ÚDictÚListÚOptionalÚTuple)Ú dataclassNc @ sN e Zd ZU dZeed< eed< ee ed< dZ e
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e ed< dZ e
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e ed< dS )Ú OCRResultzOCR detection resultÚtextÚ
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confidenceÚbboxNÚlanguageÚ text_type) Ú__name__Ú
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__module__Ú __qualname__Ú__doc__ÚstrÚ__annotations__Úfloatr Úintr r r © r r úF/home/bernt/.openclaw/workspace/iom/visual_geolocation/ocr_pipeline.pyr s
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r c @ s¸ e Zd ZdZd edœdd„Zdd„ Zedœd d
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œdd„ZdS ) Ú OCRPipelineuÙ
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Multi-engine OCR pipeline
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Supports:
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- Tesseract (local) — requires tesseract binary
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- EasyOCR (local) — requires easyocr package
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- Simulated (demo) — for testing without OCR engine
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Úauto©Úenginec C s || _ d| _| ¡ d S )NF)r Ú availableÚ _init_engine)Úselfr r r r Ú__init__ s zOCRPipeline.__init__c C s„ | j dkrD| ¡ r d| _ d| _q€| ¡ r6d| _ d| _q€d| _ d| _n<| j dkrZ| ¡ | _n&| j dkrp| ¡ | _n| j dkr€d| _dS )zInitialize OCR enginer Ú tesseractTÚeasyocrÚ simulatedN)r Ú_check_tesseractr Ú_check_easyocr)r r r r r $ s
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zOCRPipeline._init_engine)Úreturnc C s0 z ddl }| ¡ || _W dS Y dS 0 dS )z Check if Tesseract is availabler NTF)Ú pytesseractZget_tesseract_versionr )r r% r r r r" = s z OCRPipeline._check_tesseractc C s2 z ddl }| g d¢¡| _W dS Y dS 0 dS )z Check if EasyOCR is availabler N)ÚenZsvZthTF)r ÚReaderÚreader)r r r r r r# H s zOCRPipeline._check_easyocr)Ú
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image_pathr$ c C sJ | j s
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g S | jdkr | |¡S | jdkr2| |¡S | jdkrF| |¡S g S )zExtract all text from imager r r! )r r Ú_extract_tesseractÚ_extract_easyocrÚ_extract_simulated)r r) r r r Ú extract_textQ s
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zOCRPipeline.extract_textc C sä ddl m} | |¡}| jj|| jjjd�}g }t|d ƒ}t|ƒD ]š}t |d | ƒ}|dkrD|d |
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|¡ qD|S )z Extract text using Tesseractr ©ÚImage)Ú output_typer Úconfé ÚleftÚtopÚwidthÚheightg Y@N©r r r
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r r )ÚPILr/ Úopenr Ú
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image_to_dataÚOutputÚDICTÚlenÚranger Ústripr Ú_classify_textÚappend)r r) r/ ÚimgÚdataÚresultsÚn_boxesÚir1 r ÚxÚyÚwÚhÚresultr r r r* _ s(
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4û z OCRPipeline._extract_tesseractc C s’ | j |¡}g }|D ]x\}}}t|d d ƒt|d d ƒ }}t|d d ƒt|d d ƒ } }
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gd| |¡d�} | | ¡ q|S )zExtract text using EasyOCRr é é Nr7 )r( Zreadtextr r r@ rA ) r r) rD Z ocr_resultsr
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û z OCRPipeline._extract_easyocrc C s¤ ddl m} ddl}| |¡}|j\}}g d¢}g }|D ]f\} }
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d �}| |¡ q8|S ) z Simulated OCR for demo purposesr r. N))úSukhumvit RoadÚ street_namegq=
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×£pí?)ÚBangkokZ city_nameg)\�Âõ(ì?)Z10110Ú postal_codegffffffî?)Z
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RestaurantÚ
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business_nameg è?)ZMASSAGErT g=
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×£p=ê?é2 éÈ éd é r2 r& r7 ) r8 r/ Úrandomr9 ÚsizeZrandintr= r rA )r r) r/ rY rB r5 r6 Zsimulated_textsrD r r r1 rG rH rI rJ rK r r r r, ‘ s(
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û z OCRPipeline._extract_simulated)r r$ c sÖ | ¡ ‰ g d¢}t‡ fdd„|D ƒƒr*dS g d¢}t‡ fdd„|D ƒƒrLdS t|ƒdkr€td d„ |D ƒƒr€td
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d„ |D ƒƒr€d S | ¡ r˜t|ƒd kr˜d
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S tdd„ |D ƒƒrºt|ƒdkrºdS | ¡ rÒt|ƒdkrÒdS dS )z0Classify text type (street name, business, etc.)) ZstreetÚstZavenueZaveZroadZrdZ boulevardZblvdZlaneZlnZgatanu vägenc 3 s | ]}|ˆ v V qd S ©Nr ©Ú.0Úkw©Ú
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text_lowerr r Ú <genexpr>Á ó z-OCRPipeline._classify_text.<locals>.<genexpr>rQ ) Z
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restaurantZcafeZshopZstoreZhotelZmassageZspaZbarZpubc 3 s | ]}|ˆ v V qd S r\ r r] r` r r rb Ç rc rT é
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c s s | ]}| ¡ V qd S r\ ©Úisdigit©r^ Úcr r r rb Ë rc c s s | ]}| ¡ V qd S r\ )Úisalpharg r r r rb Ë rc Ú
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license_plateé Ú house_numberc s s | ]}| ¡ V qd S r\ re rg r r r rb Ó rc é Ú phone_numberé rS Úunknown)ÚlowerÚanyr= rf )r r Zstreet_keywordsZbusiness_keywordsr r` r r@ º s 0 zOCRPipeline._classify_textc C sä | |¡}g g g g g g g dœ}|D ]¼}|jdkrB|d |j¡ q"|jdkr^|d |j¡ q"|jdkrz|d |j¡ q"|jdkr–|d |j¡ q"|jd
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kr²|d |j¡ q"|jd krÎ|d
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|j¡ q"|d |j¡ q"|S )z'Extract structured data from image text)Ú street_namesÚbusiness_namesÚlicense_platesÚ
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house_numbersÚ
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phone_numbersÚ postal_codesÚ
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other_textrQ rs rT rt rj ru rl rv rn rw rS rx ry )r- r rA r )r r) rD Ú
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