{"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\/pt\/blog\/news\/vypusk-biblioteki-kompyuternogo-zreniya-opencv-4-2","title":{"rendered":"Lan\u00e7amento da biblioteca de vis\u00e3o computacional 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\/\">Aconteceu<\/a><\/noindex> lan\u00e7amento da biblioteca livre <noindex><a rel=\"nofollow\" href=\"http:\/\/opencv.org\/\">OpenCV 4.2<\/a><\/noindex> (Open Source Computer Vision Library), que fornece ferramentas para processamento e an\u00e1lise de conte\u00fado de imagens. O OpenCV oferece mais de 2500 algoritmos, tanto cl\u00e1ssicos quanto refletindo os mais recentes avan\u00e7os em vis\u00e3o computacional e sistemas de aprendizado de m\u00e1quina. O c\u00f3digo da biblioteca \u00e9 escrito em C++ e <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/opencv\/opencv\/\">\u00e9 distribu\u00eddo<\/a><\/noindex> sob licen\u00e7a BSD. As liga\u00e7\u00f5es est\u00e3o preparadas para v\u00e1rias linguagens de programa\u00e7\u00e3o, incluindo Python, MATLAB e Java.<\/p>\n<p>A biblioteca pode ser usada para reconhecimento de objetos em fotografias e v\u00eddeos (por exemplo, reconhecimento de rostos e figuras humanas, texto, etc.), rastreamento de movimento de objetos e c\u00e2meras, classifica\u00e7\u00e3o de a\u00e7\u00f5es em v\u00eddeos, transforma\u00e7\u00e3o de imagens, extra\u00e7\u00e3o de modelos 3D, forma\u00e7\u00e3o de espa\u00e7o 3D a partir de imagens de c\u00e2meras est\u00e9reo, cria\u00e7\u00e3o de imagens de alta qualidade atrav\u00e9s da combina\u00e7\u00e3o de imagens de menor qualidade, busca em imagens por objetos semelhantes a um conjunto apresentado, aplica\u00e7\u00e3o de m\u00e9todos de aprendizado de m\u00e1quina, posicionamento de marcadores, identifica\u00e7\u00e3o de elementos comuns em diferentes imagens, corre\u00e7\u00e3o autom\u00e1tica de defeitos, como o efeito dos olhos vermelhos.<\/p>\n<p>Em <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/opencv\/opencv\/wiki\/ChangeLog#version420\">novo<\/a><\/noindex> <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/opencv\/opencv\/releases\/tag\/4.2.0\">lan\u00e7amento<\/a><\/noindex>:<\/p>\n<ul>\n<li class=\"l\"> No m\u00f3dulo DNN (Deep Neural Network) com a implementa\u00e7\u00e3o de algoritmos de aprendizado de m\u00e1quina baseados em redes neurais, foi adicionado um backend para uso do CUDA e foi implementado suporte experimental para API <noindex><a rel=\"nofollow\" href=\"http:\/\/docs.openvinotoolkit.org\/\">nGraph OpenVINO<\/a><\/noindex>;\n<li class=\"l\"> Usando instru\u00e7\u00f5es SIMD, houve uma otimiza\u00e7\u00e3o de desempenho do c\u00f3digo para estereovis\u00e3o (StereoBM\/StereoSGBM), redimensionamento, sobreposi\u00e7\u00e3o de m\u00e1scara, rota\u00e7\u00e3o, c\u00e1lculo de componentes de cor ausentes e muitas outras opera\u00e7\u00f5es;\n<li class=\"l\"> Foi adicionada uma implementa\u00e7\u00e3o multithread da fun\u00e7\u00e3o <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\"> Foi adicionada a capacidade de extrair fluxos de v\u00eddeo de cont\u00eaineres de m\u00eddia (demuxing) usando o backend videoio baseado em FFmpeg;\n<li class=\"l\"> Foi adicionado um algoritmo para r\u00e1pida reconstru\u00e7\u00e3o seletiva de frequ\u00eancia de imagens danificadas <noindex><a rel=\"nofollow\" href=\"https:\/\/docs.opencv.org\/4.2.0\/dc\/d2f\/tutorial_xphoto_inpainting.html\">FSR<\/a><\/noindex> (Reconstru\u00e7\u00e3o Seletiva de Frequ\u00eancia);\n<li class=\"l\"> M\u00e9todo adicionado <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/opencv\/opencv_contrib\/pull\/2367\">RIC<\/a><\/noindex> para interpola\u00e7\u00e3o de \u00e1reas vazias t\u00edpicas;\n<li class=\"l\"> Foi adicionado um m\u00e9todo de normaliza\u00e7\u00e3o de desvios <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/short-circuitt\/LOGOS\">LOGOS<\/a><\/noindex>;\n<li class=\"l\"> No m\u00f3dulo G-API (opencv_gapi), que desempenha fun\u00e7\u00f5es de mecanismo para o processamento eficiente de imagens usando algoritmos baseados em grafos, foi implementado suporte a algoritmos h\u00edbridos mais complexos de vis\u00e3o computacional e aprendizado de m\u00e1quina profundo. H\u00e1 suporte para o backend Intel Inference Engine. A modelo de execu\u00e7\u00e3o agora inclui suporte ao processamento de fluxos de v\u00eddeo;\n<li class=\"l\"> Corrigidos <noindex><a rel=\"nofollow\" href=\"https:\/\/blog.talosintelligence.com\/2020\/01\/opencv-buffer-overflow-jan-2020.html\">no aplicativo para Windows, que permitia ao usu\u00e1rio elevar seus privil\u00e9gios no sistema para administrador (a vulnerabilidade foi causada pela intera\u00e7\u00e3o inadequada entre o cliente GUI sem privil\u00e9gios e o servi\u00e7o de sistema).<\/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>), que potencialmente podem levar \u00e0 execu\u00e7\u00e3o de c\u00f3digo do atacante ao processar dados n\u00e3o verificados nos formatos XML, YAML e JSON. Se, durante a an\u00e1lise do JSON, um caractere com c\u00f3digo nulo for encontrado, o valor inteiro \u00e9 copiado para o buffer, mas sem a devida verifica\u00e7\u00e3o de estouro da \u00e1rea de mem\u00f3ria alocada.\n<\/ul>\n<p><noindex><a rel=\"nofollow\" name=\"link\"><\/a><\/noindex><\/p>\n<p>Fonte: <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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