{"id":87777,"date":"2020-07-10T01:42:13","date_gmt":"2020-07-09T23:42:13","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/novaya-sistema-opticheskogo-raspoznavaniya-teksta-easyocr"},"modified":"2020-07-10T01:42:13","modified_gmt":"2020-07-09T23:42:13","slug":"novaya-sistema-opticheskogo-raspoznavaniya-teksta-easyocr","status":"publish","type":"post","link":"https:\/\/prohoster.info\/nl\/blog\/news\/novaya-sistema-opticheskogo-raspoznavaniya-teksta-easyocr","title":{"rendered":"Het nieuwe systeem voor optische tekenherkenning EasyOCR","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Project EasyOCR<\/a><\/noindex> er wordt een nieuw optisch tekstherkenningssysteem ontwikkeld dat meer dan 40 talen ondersteunt, waaronder Engels, Duits, Frans, Japans, Chinees, Koreaans, Oezbeeks, Azerbeidzjaans en Litouws. Talen op basis van het Cyrillisch worden voorlopig niet ondersteund, maar hun toevoeging staat op de planning. De code is geschreven in Python met behulp van het framework PyTorch<\/a><\/noindex> en wordt verspreid<\/a><\/noindex> onder Apache 2.0-licentie. Voor download ontwerpen voor 3D-printen van de behuizing van een USB-sleutelhanger op basis van de populaire chip<\/a><\/noindex> beschikbare modellen voor talen op basis van het Latijnse alfabet en hi\u00ebroglyphen.<\/p>\n

Om tekst op afbeeldingen te identificeren en te herkennen, worden methoden voor machine learning toegepast. Voor het identificeren van tekst wordt een machine learning-algoritme gebruikt CRAFT<\/a><\/noindex> (Character-Region Awareness For Text) in implementatie<\/a><\/noindex> voor PyTorch, dat in staat is om tekst te detecteren op willekeurige objecten, waaronderLabels, informatietabellen en verkeersborden. Voor het herkennen van tekenreeks wordt een convolutioneel-recurrent neuraal netwerk toegepast CRNN<\/a><\/noindex> (Convolutional Recurrent Neural Network, een combinatie van DCNN en RNN) en het algoritme CTC BeamSearch<\/a><\/noindex> CTC BeamSearch (Connectionist Temporal Classification) voor het decoderen van de uitvoer van het neuraal netwerk in tekstuele vorm. <\/p>\n

<\/a><\/noindex><\/p>\n

Bron: opennet.ru<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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