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< div class = "cardback" > < DOCUMENT_FRAGMENT > < div class = "mw-parser-output" > < div class = "thumb tright" > < div class = "thumbinner" style = "width:152px;" > < a class = "image" href = "https://pzwiki.wdka.nl/mw-mediadesign/images/thumb/3/3c/Rereferencing_Open_work_OCR.jpeg/720px-Rereferencing_Open_work_OCR.jpeg" > < img alt = "" class = "thumbimage" decoding = "async" src = "https://pzwiki.wdka.nl/mw-mediadesign/images/thumb/3/3c/Rereferencing_Open_work_OCR.jpeg/320px-Rereferencing_Open_work_OCR.jpeg" > < / a > < div class = "thumbcaption" > < div class = "magnify" > < a class = "internal" href = "File:Rereferencing_Open_work_OCR.jpeg.html" title = "Enlarge" > < / a > < / div > A bootleg copy of The Open Work by Umberto Eco. OCR software has mistaken the page number (page 80) as the word “So”< / div > < / div > < / div >
< h2 > < span class = "mw-headline" id = "Pre-processing_for_OCR" > Pre-processing for OCR< / span > < span class = "mw-editsection" > < span class = "mw-editsection-bracket" > [< / span > < a href = "/mw-mediadesign/index.php?title=User:Simon/self_directed_research/OCR_preprocessing&action=edit&section=T-1" title = "Edit section: " > edit< / a > < span class = "mw-editsection-bracket" > ]< / span > < / span > < / h2 >
< p > This script applies transformations to the image before running OCR, resulting in a clearer result:
< / p >
< div class = "mw-highlight mw-content-ltr" dir = "ltr" > < pre > < span > < / span > < span class = "c1" > # import the necessary packages< / span >
< span class = "c1" > #from PIL < / span >
< span class = "kn" > import< / span > < span class = "nn" > Image< / span >
< span class = "kn" > import< / span > < span class = "nn" > pytesseract< / span >
< span class = "kn" > import< / span > < span class = "nn" > argparse< / span >
< span class = "kn" > import< / span > < span class = "nn" > cv2< / span >
< span class = "kn" > import< / span > < span class = "nn" > os< / span >
< span class = "c1" > # construct the argument parse and parse the arguments< / span >
< span class = "n" > ap< / span > < span class = "o" > =< / span > < span class = "n" > argparse< / span > < span class = "o" > .< / span > < span class = "n" > ArgumentParser< / span > < span class = "p" > ()< / span >
< span class = "n" > ap< / span > < span class = "o" > .< / span > < span class = "n" > add_argument< / span > < span class = "p" > (< / span > < span class = "s2" > "-i"< / span > < span class = "p" > ,< / span > < span class = "s2" > "--image"< / span > < span class = "p" > ,< / span > < span class = "n" > required< / span > < span class = "o" > =< / span > < span class = "bp" > True< / span > < span class = "p" > ,< / span >
< span class = "n" > help< / span > < span class = "o" > =< / span > < span class = "s2" > "path to input image to be OCR'd"< / span > < span class = "p" > )< / span >
< span class = "n" > ap< / span > < span class = "o" > .< / span > < span class = "n" > add_argument< / span > < span class = "p" > (< / span > < span class = "s2" > "-p"< / span > < span class = "p" > ,< / span > < span class = "s2" > "--preprocess"< / span > < span class = "p" > ,< / span > < span class = "nb" > type< / span > < span class = "o" > =< / span > < span class = "nb" > str< / span > < span class = "p" > ,< / span > < span class = "n" > default< / span > < span class = "o" > =< / span > < span class = "s2" > "thresh"< / span > < span class = "p" > ,< / span >
< span class = "n" > help< / span > < span class = "o" > =< / span > < span class = "s2" > "type of preprocessing to be done"< / span > < span class = "p" > )< / span >
< span class = "n" > args< / span > < span class = "o" > =< / span > < span class = "nb" > vars< / span > < span class = "p" > (< / span > < span class = "n" > ap< / span > < span class = "o" > .< / span > < span class = "n" > parse_args< / span > < span class = "p" > ())< / span >
< span class = "c1" > # load the example image and convert it to grayscale< / span >
< span class = "n" > image< / span > < span class = "o" > =< / span > < span class = "n" > cv2< / span > < span class = "o" > .< / span > < span class = "n" > imread< / span > < span class = "p" > (< / span > < span class = "n" > args< / span > < span class = "p" > [< / span > < span class = "s2" > "image"< / span > < span class = "p" > ])< / span >
< span class = "n" > gray< / span > < span class = "o" > =< / span > < span class = "n" > cv2< / span > < span class = "o" > .< / span > < span class = "n" > cvtColor< / span > < span class = "p" > (< / span > < span class = "n" > image< / span > < span class = "p" > ,< / span > < span class = "n" > cv2< / span > < span class = "o" > .< / span > < span class = "n" > COLOR_BGR2GRAY< / span > < span class = "p" > )< / span >
< span class = "c1" > # check to see if we should apply thresholding to preprocess the< / span >
< span class = "c1" > # image< / span >
< span class = "k" > if< / span > < span class = "n" > args< / span > < span class = "p" > [< / span > < span class = "s2" > "preprocess"< / span > < span class = "p" > ]< / span > < span class = "o" > ==< / span > < span class = "s2" > "thresh"< / span > < span class = "p" > :< / span >
< span class = "n" > gray< / span > < span class = "o" > =< / span > < span class = "n" > cv2< / span > < span class = "o" > .< / span > < span class = "n" > threshold< / span > < span class = "p" > (< / span > < span class = "n" > gray< / span > < span class = "p" > ,< / span > < span class = "mi" > 0< / span > < span class = "p" > ,< / span > < span class = "mi" > 255< / span > < span class = "p" > ,< / span >
< span class = "n" > cv2< / span > < span class = "o" > .< / span > < span class = "n" > THRESH_BINARY< / span > < span class = "o" > |< / span > < span class = "n" > cv2< / span > < span class = "o" > .< / span > < span class = "n" > THRESH_OTSU< / span > < span class = "p" > )[< / span > < span class = "mi" > 1< / span > < span class = "p" > ]< / span >
< span class = "c1" > # make a check to see if median blurring should be done to remove< / span >
< span class = "c1" > # noise< / span >
< span class = "k" > elif< / span > < span class = "n" > args< / span > < span class = "p" > [< / span > < span class = "s2" > "preprocess"< / span > < span class = "p" > ]< / span > < span class = "o" > ==< / span > < span class = "s2" > "blur"< / span > < span class = "p" > :< / span >
< span class = "n" > gray< / span > < span class = "o" > =< / span > < span class = "n" > cv2< / span > < span class = "o" > .< / span > < span class = "n" > medianBlur< / span > < span class = "p" > (< / span > < span class = "n" > gray< / span > < span class = "p" > ,< / span > < span class = "mi" > 3< / span > < span class = "p" > )< / span >
< span class = "c1" > # write the grayscale image to disk as a temporary file so we can< / span >
< span class = "c1" > # apply OCR to it< / span >
< span class = "n" > filename< / span > < span class = "o" > =< / span > < span class = "s2" > "{}.png"< / span > < span class = "o" > .< / span > < span class = "n" > format< / span > < span class = "p" > (< / span > < span class = "n" > os< / span > < span class = "o" > .< / span > < span class = "n" > getpid< / span > < span class = "p" > ())< / span >
< span class = "n" > cv2< / span > < span class = "o" > .< / span > < span class = "n" > imwrite< / span > < span class = "p" > (< / span > < span class = "n" > filename< / span > < span class = "p" > ,< / span > < span class = "n" > gray< / span > < span class = "p" > )< / span >
< span class = "c1" > # load the image as a PIL/Pillow image, apply OCR, and then delete< / span >
< span class = "c1" > # the temporary file< / span >
< span class = "n" > text< / span > < span class = "o" > =< / span > < span class = "n" > pytesseract< / span > < span class = "o" > .< / span > < span class = "n" > image_to_string< / span > < span class = "p" > (< / span > < span class = "n" > Image< / span > < span class = "o" > .< / span > < span class = "n" > open< / span > < span class = "p" > (< / span > < span class = "n" > filename< / span > < span class = "p" > ))< / span >
< span class = "n" > os< / span > < span class = "o" > .< / span > < span class = "n" > remove< / span > < span class = "p" > (< / span > < span class = "n" > filename< / span > < span class = "p" > )< / span >
< span class = "k" > print< / span > < span class = "p" > (< / span > < span class = "n" > text< / span > < span class = "p" > )< / span >
< span class = "c1" > # show the output images< / span >
< span class = "n" > cv2< / span > < span class = "o" > .< / span > < span class = "n" > imshow< / span > < span class = "p" > (< / span > < span class = "s2" > "Image"< / span > < span class = "p" > ,< / span > < span class = "n" > image< / span > < span class = "p" > )< / span >
< span class = "n" > cv2< / span > < span class = "o" > .< / span > < span class = "n" > imshow< / span > < span class = "p" > (< / span > < span class = "s2" > "Output"< / span > < span class = "p" > ,< / span > < span class = "n" > gray< / span > < span class = "p" > )< / span >
< span class = "n" > cv2< / span > < span class = "o" > .< / span > < span class = "n" > waitKey< / span > < span class = "p" > (< / span > < span class = "mi" > 0< / span > < span class = "p" > )< / span >
< / pre > < / div >
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Cache expiry: 86400
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CPU time usage: 0.028 seconds
Real time usage: 0.215 seconds
Preprocessor visited node count: 7/1000000
Preprocessor generated node count: 26/1000000
Post‐
Template argument size: 0/2097152 bytes
Highest expansion depth: 2/40
Expensive parser function count: 0/100
Unstrip recursion depth: 0/20
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Transclusion expansion time report (%,ms,calls,template)
100.00% 191.534 1 User:Simon/self_directed_research/OCR_preprocessing
100.00% 191.534 1 -total
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