{"id":106297,"date":"2022-12-29T21:37:00","date_gmt":"2022-12-29T19:37:00","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/vypusk-biblioteki-kompyuternogo-zreniya-opencv-4-7"},"modified":"2022-12-29T21:37:00","modified_gmt":"2022-12-29T19:37:00","slug":"vypusk-biblioteki-kompyuternogo-zreniya-opencv-4-7","status":"publish","type":"post","link":"https:\/\/prohoster.info\/pt\/blog\/news\/vypusk-biblioteki-kompyuternogo-zreniya-opencv-4-7","title":{"rendered":"Lan\u00e7amento da biblioteca de vis\u00e3o computacional OpenCV 4.7","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Foi lan\u00e7ado a biblioteca livre OpenCV 4.7 (Biblioteca de Vis\u00e3o Computacional de C\u00f3digo Aberto), que fornece ferramentas para o processamento e an\u00e1lise de conte\u00fados de imagens. OpenCV oferece mais de 2500 algoritmos, tanto cl\u00e1ssicos quanto que refletem os \u00faltimos avan\u00e7os em vis\u00e3o computacional e sistemas de aprendizado de m\u00e1quina. O c\u00f3digo da biblioteca \u00e9 escrito em C++ e distribu\u00eddo sob a licen\u00e7a BSD. V\u00ednculos foram preparados 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>Entre as mudan\u00e7as na nova vers\u00e3o:  <\/p>\n<ul>\n<li class=\"l\"> Foi realizada uma otimiza\u00e7\u00e3o significativa no desempenho das convolu\u00e7\u00f5es no m\u00f3dulo DNN (Rede Neural Profunda) com a implementa\u00e7\u00e3o de algoritmos de aprendizado de m\u00e1quina baseados em redes neurais. O algoritmo r\u00e1pido de convolu\u00e7\u00f5es de Vinograd foi implementado. Novas camadas ONNX (Open Neural Network Exchange) foram adicionadas: Scatter, ScatterND, Tile, ReduceL1 e ReduceMin. O suporte para o framework OpenVino 2022.1 e o backend CANN foi adicionado.\n<li class=\"l\"> A qualidade de detec\u00e7\u00e3o e decodifica\u00e7\u00e3o de QR codes foi aprimorada.\n<li class=\"l\"> Adicionado suporte para marcadores visuais ArUco e AprilTag.\n<li class=\"l\"> Adicionado o rastreador Nanotrack v2 baseado em redes neurais.\n<li class=\"l\"> Implementado o algoritmo de desfoque Stackblur.\n<li class=\"l\"> Adicionado suporte para FFmpeg 5.x e CUDA 12.0.\n<li class=\"l\"> Uma nova API para manipula\u00e7\u00e3o de formatos de imagem multip\u00e1gina foi proposta.\n<li class=\"l\"> Adicionado suporte para a biblioteca libSPNG para o formato PNG.\n<li class=\"l\"> No libJPEG-Turbo, foram utilizados acelera\u00e7\u00f5es por meio de instru\u00e7\u00f5es SIMD.\n<li class=\"l\"> Suporte para H264\/H265 foi implementado na plataforma Android.\n<li class=\"l\"> Todas as APIs b\u00e1sicas para a linguagem Python foram disponibilizadas.\n<li class=\"l\"> Adicionado um novo backend universal para instru\u00e7\u00f5es vetoriais.  <\/ul>\n<p>Fonte: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=58405\">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 4.7 (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-106297","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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