{"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\/da\/blog\/news\/novaya-sistema-opticheskogo-raspoznavaniya-teksta-easyocr","title":{"rendered":"Det nye system til optisk tekstgenkendelse EasyOCR","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Projektet <noindex><a rel=\"nofollow\" href=\"https:\/\/jaided.ai\/read\">EasyOCR<\/a><\/noindex> en ny optisk tegngenkendelsessystem er under udvikling, som underst\u00f8tter over 40 sprog, herunder engelsk, tysk, fransk, japansk, kinesisk, koreansk, usbekisk, azerbajdsjansk og litauisk. Sprog baseret p\u00e5 kyrillisk skriftsystem underst\u00f8ttes endnu ikke, men deres tilf\u00f8jelse er planlagt. Koden er skrevet i Python ved hj\u00e6lp af en ramme. <noindex><a rel=\"nofollow\" href=\"https:\/\/pytorch.org\">PyTorch<\/a><\/noindex> og <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/JaidedAI\/EasyOCR\">distribueres<\/a><\/noindex> under Apache 2.0-licens. For at hente <noindex><a rel=\"nofollow\" href=\"https:\/\/jaided.ai\/read_download\">SLTS<\/a><\/noindex> f\u00e6rdige modeller til sprog baseret p\u00e5 det latinske alfabet og tegns\u00e6t.<\/p>\n<p>Maskinl\u00e6ringsmetoder anvendes til at bestemme og genkende tekst p\u00e5 billeder. Til tekstdetektering anvendes en maskinl\u00e6ringsalgoritme. <noindex><a rel=\"nofollow\" href=\"https:\/\/arxiv.org\/pdf\/1904.01941.pdf\">CRAFT<\/a><\/noindex> (Character-Region Awareness For Text) i <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/clovaai\/CRAFT-pytorch\">implementering<\/a><\/noindex> til PyTorch, der er i stand til at fremh\u00e6ve tekst p\u00e5 vilk\u00e5rlige objekter, herunder etiketter, informationsskilte og vejskilte. Til genkendelse af tegnsekvenser anvendes en konvolutionelt-rekurrent neural netv\u00e6rk. <noindex><a rel=\"nofollow\" href=\"https:\/\/arxiv.org\/pdf\/1507.05717\">CRNN<\/a><\/noindex> (Convolutional Recurrent Neural Network, en kombination af DCNN og RNN) og algoritmen <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/githubharald\/CTCDecoder\">CTC BeamSearch<\/a><\/noindex> CTC BeamSearch (Connectionist Temporal Classification) til dekodning af netv\u00e6rkets output til tekstrepr\u00e6sentation. <\/p>\n<p><noindex><a rel=\"nofollow\" name=\"link\"><\/a><\/noindex><\/p>\n<p>Kilde: <a \ncontent=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=53314\">opennet.ru<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u041f\u0440\u043e\u0435\u043a\u0442\u043e\u043c EasyOCR \u0440\u0430\u0437\u0432\u0438\u0432\u0430\u0435\u0442\u0441\u044f \u043d\u043e\u0432\u0430\u044f \u0441\u0438\u0441\u0442\u0435\u043c\u0430 \u043e\u043f\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0433\u043e \u0440\u0430\u0441\u043f\u043e\u0437\u043d\u0430\u0432\u0430\u043d\u0438\u044f \u0442\u0435\u043a\u0441\u0442\u0430, \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u0438\u0432\u0430\u044e\u0449\u0430\u044f \u0431\u043e\u043b\u0435\u0435 40 \u044f\u0437\u044b\u043a\u043e\u0432, \u0432\u043a\u043b\u044e\u0447\u0430\u044f \u0430\u043d\u0433\u043b\u0438\u0439\u0441\u043a\u0438\u0439, \u043d\u0435\u043c\u0435\u0446\u043a\u0438\u0439, \u0444\u0440\u0430\u043d\u0446\u0443\u0437\u0441\u043a\u0438\u0439, \u044f\u043f\u043e\u043d\u0441\u043a\u0438\u0439, \u043a\u0438\u0442\u0430\u0439\u0441\u043a\u0438\u0439, \u043a\u043e\u0440\u0435\u0439\u0441\u043a\u0438\u0439, \u0443\u0437\u0431\u0435\u043a\u0441\u043a\u0438\u0439, \u0430\u0437\u0435\u0440\u0431\u0430\u0439\u0434\u0436\u0430\u043d\u0441\u043a\u0438\u0439 \u0438 \u043b\u0438\u0442\u043e\u0432\u0441\u043a\u0438\u0439. \u042f\u0437\u044b\u043a\u0438 \u043d\u0430 \u043e\u0441\u043d\u043e\u0432\u0435 \u043a\u0438\u0440\u0438\u043b\u043b\u0438\u0446\u044b \u043f\u043e\u043a\u0430 \u043d\u0435 \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u0438\u0432\u0430\u044e\u0442\u0441\u044f, \u043d\u043e \u0438\u0445 \u0434\u043e\u0431\u0430\u0432\u043b\u0435\u043d\u0438\u0435 \u0432 \u0441\u043f\u0438\u0441\u043a\u0435 \u043f\u043b\u0430\u043d\u043e\u0432. \u041a\u043e\u0434 \u043d\u0430\u043f\u0438\u0441\u0430\u043d \u043d\u0430 \u044f\u0437\u044b\u043a\u0435 Python c \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c \u0444\u0440\u0435\u0439\u043c\u0432\u043e\u0440\u043a\u0430 PyTorch \u0438 \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u044f\u0435\u0442\u0441\u044f \u043f\u043e\u0434 \u043b\u0438\u0446\u0435\u043d\u0437\u0438\u0435\u0439 Apache 2.0. \u0414\u043b\u044f \u0437\u0430\u0433\u0440\u0443\u0437\u043a\u0438 \u043f\u0440\u0435\u0434\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u044e\u0442\u0441\u044f \u0433\u043e\u0442\u043e\u0432\u044b\u0435 [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-87777","post","type-post","status-publish","format-standard","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.3 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u041f\u0440\u043e\u0435\u043a\u0442\u043e\u043c EasyOCR \u0440\u0430\u0437\u0432\u0438\u0432\u0430\u0435\u0442\u0441\u044f \u043d\u043e\u0432\u0430\u044f \u0441\u0438\u0441\u0442\u0435\u043c\u0430 \u043e\u043f\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0433\u043e \u0440\u0430\u0441\u043f\u043e\u0437\u043d\u0430\u0432\u0430\u043d\u0438\u044f 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