{"id":54815,"date":"2020-01-05T00:00:00","date_gmt":"2020-01-04T21:00:00","guid":{"rendered":"https:\/\/prohoster.info\/blog\/blog_prohoster\/vypusk-biblioteki-kompyuternogo-zreniya-opencv-4-2"},"modified":"2020-02-18T14:02:52","modified_gmt":"2020-02-18T11:02:52","slug":"vypusk-biblioteki-kompyuternogo-zreniya-opencv-4-2","status":"publish","type":"post","link":"https:\/\/prohoster.info\/cs\/blog\/news\/vypusk-biblioteki-kompyuternogo-zreniya-opencv-4-2","title":{"rendered":"Vyd\u00e1n\u00ed knihovny po\u010d\u00edta\u010dov\u00e9ho vid\u011bn\u00ed OpenCV 4.2","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p><noindex><a rel=\"nofollow\" href=\"https:\/\/opencv.org\/opencv-4-2-0\/\">Prob\u011bhlo<\/a><\/noindex> vyd\u00e1n\u00ed svobodn\u00e9 knihovny <noindex><a rel=\"nofollow\" href=\"http:\/\/opencv.org\/\">OpenCV 4.2<\/a><\/noindex> (Open Source Computer Vision Library), kter\u00e1 poskytuje prost\u0159edky pro zpracov\u00e1n\u00ed a anal\u00fdzu obsahu obraz\u016f. OpenCV nab\u00edz\u00ed v\u00edce ne\u017e 2500 algoritm\u016f, jak klasick\u00fdch, tak reflektuj\u00edc\u00edch nejnov\u011bj\u0161\u00ed pokroky v oblasti po\u010d\u00edta\u010dov\u00e9ho vid\u011bn\u00ed a syst\u00e9m\u016f strojov\u00e9ho u\u010den\u00ed. K\u00f3d knihovny je naps\u00e1n v jazyce C++ a <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/opencv\/opencv\/\">distribuov\u00e1no<\/a><\/noindex> je pod licenc\u00ed BSD. Byl p\u0159ipraven binding pro r\u016fzn\u00e9 programovac\u00ed jazyky, v\u010detn\u011b Pythonu, MATLABu a Javy.<\/p>\n<p>Knihovna m\u016f\u017ee b\u00fdt pou\u017eita pro rozpozn\u00e1v\u00e1n\u00ed objekt\u016f na fotografi\u00edch a vide\u00edch (nap\u0159\u00edklad rozpozn\u00e1v\u00e1n\u00ed obli\u010dej\u016f a postav lid\u00ed, textu atd.), sledov\u00e1n\u00ed pohybu objekt\u016f a kamery, klasifikaci akc\u00ed na videu, konverzi obraz\u016f, extrakci 3D model\u016f, vytv\u00e1\u0159en\u00ed 3D prostoru z obrazu z stereokamer, vytv\u00e1\u0159en\u00ed vysoce kvalitn\u00edch obraz\u016f spojov\u00e1n\u00edm obraz\u016f ni\u017e\u0161\u00ed kvality, vyhled\u00e1v\u00e1n\u00ed na obr\u00e1zku objekt\u016f podobn\u00fdch zadan\u00e9mu souboru prvk\u016f, pou\u017eit\u00ed metod strojov\u00e9ho u\u010den\u00ed, umis\u0165ov\u00e1n\u00ed marker\u016f, identifikaci spole\u010dn\u00fdch prvk\u016f na r\u016fzn\u00fdch obrazech, automatick\u00e9 odstra\u0148ov\u00e1n\u00ed defekt\u016f, jako je efekt \u010derven\u00fdch o\u010d\u00ed.<\/p>\n<p>V <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/opencv\/opencv\/wiki\/ChangeLog#version420\">nov\u00e9m<\/a><\/noindex> <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/opencv\/opencv\/releases\/tag\/4.2.0\">vyd\u00e1n\u00ed<\/a><\/noindex>:<\/p>\n<ul>\n<li class=\"l\"> Do modulu DNN (Deep Neural Network) s implementac\u00ed algoritm\u016f strojov\u00e9ho u\u010den\u00ed na b\u00e1zi neuronov\u00fdch s\u00edt\u00ed byl p\u0159id\u00e1n backend pro pou\u017eit\u00ed CUDA a byla implementov\u00e1na experiment\u00e1ln\u00ed podpora API <noindex><a rel=\"nofollow\" href=\"http:\/\/docs.openvinotoolkit.org\/\">nGraph OpenVINO<\/a><\/noindex>;\n<li class=\"l\"> S vyu\u017eit\u00edm instrukc\u00ed SIMD byla optimalizov\u00e1na v\u00fdkonnost k\u00f3du pro stereov\u00fdstup (StereoBM\/StereoSGBM), zm\u011bnu velikosti, aplikaci masky, rotaci, v\u00fdpo\u010det chyb\u011bj\u00edc\u00edch komponent\u016f barvy a dal\u0161\u00ed operace;\n<li class=\"l\"> Byla p\u0159id\u00e1na v\u00edcetr otvorov\u00e1 implementace funkce <noindex><a rel=\"nofollow\" href=\"https:\/\/docs.opencv.org\/3.4\/d4\/d86\/group__imgproc__filter.html#gaf9bba239dfca11654cb7f50f889fc2ff\">pyrDown<\/a><\/noindex>;\n<li class=\"l\"> Byla p\u0159id\u00e1na mo\u017enost z\u00edsk\u00e1v\u00e1n\u00ed video stream\u016f z medi\u00e1lnich kontejner\u016f (demuxing) pomoc\u00ed backendu videoio zalo\u017een\u00e9ho na FFmpeg;\n<li class=\"l\"> Byl p\u0159id\u00e1n algoritmus pro rychlou frekven\u010dn\u011b selektivn\u00ed rekonstrukci po\u0161kozen\u00fdch obraz\u016f <noindex><a rel=\"nofollow\" href=\"https:\/\/docs.opencv.org\/4.2.0\/dc\/d2f\/tutorial_xphoto_inpainting.html\">FSR<\/a><\/noindex> (Frekven\u010dn\u011b selektivn\u00ed rekonstrukce);\n<li class=\"l\"> Byla p\u0159id\u00e1na metoda <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/opencv\/opencv_contrib\/pull\/2367\">RIC<\/a><\/noindex> pro interpolaci typick\u00fdch nezapln\u011bn\u00fdch oblast\u00ed;\n<li class=\"l\"> Byla p\u0159id\u00e1na metoda normalizace odchylek <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/short-circuitt\/LOGOS\">LOGOS<\/a><\/noindex>;\n<li class=\"l\"> V modulu G-API (opencv_gapi), kter\u00fd slou\u017e\u00ed jako engine pro efektivn\u00ed zpracov\u00e1n\u00ed obr\u00e1zk\u016f pomoc\u00ed grafov\u00fdch algoritm\u016f, byla implementov\u00e1na podpora slo\u017eit\u011bj\u0161\u00edch hybridn\u00edch algoritm\u016f po\u010d\u00edta\u010dov\u00e9ho vid\u011bn\u00ed a hlubok\u00e9ho strojov\u00e9ho u\u010den\u00ed. Byla zaji\u0161t\u011bna podpora backendu Intel Inference Engine. Do modelu prov\u00e1d\u011bn\u00ed byla p\u0159id\u00e1na podpora zpracov\u00e1n\u00ed video stream\u016f;\n<li class=\"l\"> Opraveny <noindex><a rel=\"nofollow\" href=\"https:\/\/blog.talosintelligence.com\/2020\/01\/opencv-buffer-overflow-jan-2020.html\">zranitelnosti<\/a><\/noindex>  (<noindex><a rel=\"nofollow\" href=\"https:\/\/www.talosintelligence.com\/vulnerability_reports\/TALOS-2019-0852\">CVE-2019-5063<\/a><\/noindex>, <noindex><a rel=\"nofollow\" href=\"https:\/\/www.talosintelligence.com\/vulnerability_reports\/TALOS-2019-0853\">CVE-2019-5064<\/a><\/noindex>), kter\u00e9 mohou potenci\u00e1ln\u011b v\u00e9st k vykon\u00e1n\u00ed k\u00f3du \u00fato\u010dn\u00edka p\u0159i zpracov\u00e1n\u00ed neov\u011b\u0159en\u00fdch dat ve form\u00e1tech XML, YAML a JSON. Pokud se b\u011bhem anal\u00fdzy JSON objev\u00ed znak s nulov\u00fdm k\u00f3dem, hodnota se kompletn\u011b zkop\u00edruje do bufferu, av\u0161ak bez pat\u0159i\u010dn\u00e9 kontroly p\u0159ete\u010den\u00ed pam\u011bti.\n<\/ul>\n<p><noindex><a rel=\"nofollow\" name=\"link\"><\/a><\/noindex><\/p>\n<p>Zdroj: <a \ncontent=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=52134\">opennet.ru<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u0421\u043e\u0441\u0442\u043e\u044f\u043b\u0441\u044f \u0440\u0435\u043b\u0438\u0437 \u0441\u0432\u043e\u0431\u043e\u0434\u043d\u043e\u0439 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 OpenCV 4.2 (Open Source Computer Vision Library), \u043f\u0440\u0435\u0434\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u044e\u0449\u0435\u0439 \u0441\u0440\u0435\u0434\u0441\u0442\u0432\u0430 \u0434\u043b\u044f \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u0438 \u0430\u043d\u0430\u043b\u0438\u0437\u0430 \u0441\u043e\u0434\u0435\u0440\u0436\u0438\u043c\u043e\u0433\u043e \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0439. OpenCV \u043f\u0440\u0435\u0434\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 \u0431\u043e\u043b\u0435\u0435 2500 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u043e\u0432, \u043a\u0430\u043a \u043a\u043b\u0430\u0441\u0441\u0438\u0447\u0435\u0441\u043a\u0438\u0445, \u0442\u0430\u043a \u0438 \u043e\u0442\u0440\u0430\u0436\u0430\u044e\u0449\u0438\u0445 \u043f\u043e\u0441\u043b\u0435\u0434\u043d\u0438\u0435 \u0434\u043e\u0441\u0442\u0438\u0436\u0435\u043d\u0438\u044f \u0432 \u043e\u0431\u043b\u0430\u0441\u0442\u0438 \u043a\u043e\u043c\u043f\u044c\u044e\u0442\u0435\u0440\u043d\u043e\u0433\u043e \u0437\u0440\u0435\u043d\u0438\u044f \u0438 \u0441\u0438\u0441\u0442\u0435\u043c \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f. \u041a\u043e\u0434 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 \u043d\u0430\u043f\u0438\u0441\u0430\u043d \u043d\u0430 \u044f\u0437\u044b\u043a\u0435 \u0421++ \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 BSD. \u0411\u0438\u043d\u0434\u0438\u043d\u0433\u0438 \u043f\u043e\u0434\u0433\u043e\u0442\u043e\u0432\u043b\u0435\u043d\u044b \u0434\u043b\u044f \u0440\u0430\u0437\u043b\u0438\u0447\u043d\u044b\u0445 \u044f\u0437\u044b\u043a\u043e\u0432 [&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-54815","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=\"\u0421\u043e\u0441\u0442\u043e\u044f\u043b\u0441\u044f \u0440\u0435\u043b\u0438\u0437 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