{"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\/fr\/blog\/news\/vypusk-biblioteki-kompyuternogo-zreniya-opencv-4-2","title":{"rendered":"Publication de la biblioth\u00e8que de vision par ordinateur 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\/\">A eu lieu<\/a><\/noindex> sortie de la biblioth\u00e8que libre <noindex><a rel=\"nofollow\" href=\"http:\/\/opencv.org\/\">OpenCV 4.2<\/a><\/noindex> (Biblioth\u00e8que de Vision par Ordinateur Open Source), fournissant des outils pour le traitement et l'analyse du contenu des images. OpenCV offre plus de 2500 algorithmes, \u00e0 la fois classiques et refl\u00e9tant les derni\u00e8res avanc\u00e9es dans le domaine de la vision par ordinateur et des syst\u00e8mes d'apprentissage automatique. Le code de la biblioth\u00e8que est \u00e9crit en C++ et <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/opencv\/opencv\/\">est distribu\u00e9<\/a><\/noindex> sous licence BSD. Des liaisons ont \u00e9t\u00e9 pr\u00e9par\u00e9es pour divers langages de programmation, y compris Python, MATLAB et Java.<\/p>\n<p>La biblioth\u00e8que peut \u00eatre utilis\u00e9e pour la reconnaissance d'objets sur des photographies et des vid\u00e9os (par exemple, la reconnaissance faciale et des silhouettes humaines, du texte, etc.), le suivi du mouvement des objets et de la cam\u00e9ra, la classification des actions sur vid\u00e9o, la transformation d'images, l'extraction de mod\u00e8les 3D, la cr\u00e9ation d'espaces 3D \u00e0 partir d'images de cam\u00e9ras st\u00e9r\u00e9o, la construction d'images de haute qualit\u00e9 \u00e0 partir d'images de plus basse qualit\u00e9, la recherche d'objets sur une image similaires \u00e0 un ensemble donn\u00e9, l'application de m\u00e9thodes d'apprentissage automatique, le placement de marqueurs, la d\u00e9tection d'\u00e9l\u00e9ments communs sur diff\u00e9rentes images, et l'\u00e9limination automatique des d\u00e9fauts comme l'effet des yeux rouges.<\/p>\n<p>Dans <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/opencv\/opencv\/wiki\/ChangeLog#version420\">nouvelle<\/a><\/noindex> <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/opencv\/opencv\/releases\/tag\/4.2.0\">version<\/a><\/noindex>:<\/p>\n<ul>\n<li class=\"l\"> Dans le module DNN (R\u00e9seau Neuronal Profond) avec une mise en \u0153uvre d'algorithmes d'apprentissage automatique bas\u00e9s sur des r\u00e9seaux neuronaux, un backend a \u00e9t\u00e9 ajout\u00e9 pour utiliser CUDA et un support exp\u00e9rimental pour l'API <noindex><a rel=\"nofollow\" href=\"http:\/\/docs.openvinotoolkit.org\/\">nGraph OpenVINO<\/a><\/noindex>;\n<li class=\"l\"> Avec l'utilisation des instructions SIMD, la performance du code a \u00e9t\u00e9 optimis\u00e9e pour le rendu st\u00e9r\u00e9oscopique (StereoBM\/StereoSGBM), le changement de taille, l'application de masques, la rotation, le calcul des composants de couleur manquants et de nombreuses autres op\u00e9rations;\n<li class=\"l\"> Une mise en \u0153uvre multithread de la fonction <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\"> La possibilit\u00e9 d'extraire des flux vid\u00e9o \u00e0 partir de conteneurs multim\u00e9dia (d\u00e9multiplexage) a \u00e9t\u00e9 ajout\u00e9e \u00e0 l'aide du backend videoio bas\u00e9 sur FFmpeg;\n<li class=\"l\"> Un algorithme pour la reconstruction rapide \u00e0 s\u00e9lection de fr\u00e9quence d'images endommag\u00e9es a \u00e9t\u00e9 ajout\u00e9 <noindex><a rel=\"nofollow\" href=\"https:\/\/docs.opencv.org\/4.2.0\/dc\/d2f\/tutorial_xphoto_inpainting.html\">FSR<\/a><\/noindex> (Reconstruction S\u00e9lective en Fr\u00e9quence);\n<li class=\"l\"> M\u00e9thode ajout\u00e9e <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/opencv\/opencv_contrib\/pull\/2367\">RIC<\/a><\/noindex> pour l'interpolation des zones typiques non remplies;\n<li class=\"l\"> Une m\u00e9thode de normalisation des \u00e9carts a \u00e9t\u00e9 ajout\u00e9e <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/short-circuitt\/LOGOS\">LOGOS<\/a><\/noindex>;\n<li class=\"l\"> Dans le module G-API (opencv_gapi), qui fonctionne comme un moteur pour un traitement d'images efficace utilisant des algorithmes bas\u00e9s sur des graphes, un support pour des algorithmes hybrides plus complexes de vision par ordinateur et d'apprentissage machine profond a \u00e9t\u00e9 impl\u00e9ment\u00e9. Le support du backend Intel Inference Engine a \u00e9t\u00e9 assur\u00e9. Le mod\u00e8le d'ex\u00e9cution a \u00e9t\u00e9 extens\u00e9 pour traiter des flux vid\u00e9o;\n<li class=\"l\"> R\u00e9solus <noindex><a rel=\"nofollow\" href=\"https:\/\/blog.talosintelligence.com\/2020\/01\/opencv-buffer-overflow-jan-2020.html\">une vuln\u00e9rabilit\u00e9<\/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>), qui peuvent potentiellement conduire \u00e0 l'ex\u00e9cution de code par un attaquant lors du traitement de donn\u00e9es non v\u00e9rifi\u00e9es dans les formats XML, YAML et JSON. Lors de l'analyse de JSON, si un caract\u00e8re avec un code nul est rencontr\u00e9, la valeur est enti\u00e8rement copi\u00e9e dans le tampon, mais sans une v\u00e9rification ad\u00e9quate du d\u00e9passement de la m\u00e9moire allou\u00e9e.\n<\/ul>\n<p><noindex><a rel=\"nofollow\" name=\"link\"><\/a><\/noindex><\/p>\n<p>Source : <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 5.0.2 - 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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