{"id":181944,"date":"2026-06-08T02:48:45","date_gmt":"2026-06-08T00:48:46","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/opencv-5-0-0"},"modified":"2026-06-08T02:48:45","modified_gmt":"2026-06-08T00:48:46","slug":"opencv-5-0-0","status":"publish","type":"post","link":"https:\/\/prohoster.info\/lv\/blog\/news\/opencv-5-0-0","title":{"rendered":"OpenCV 5.0.0","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p><img decoding=\"async\" src=\"\/wp-content\/uploads\/2026\/06\/0827c35d7663a25a36859f66c23893bc.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><noindex>      <noindex><\/p>\n<p>Public\u0113ts <strong><a rel=\"nofollow\" href=\"https:\/\/github.com\/opencv\/opencv\">OpenCV 5.0.0<\/a><\/strong> \u2014 liels izlaidums atv\u0113rt\u0101s datorredzes un att\u0113lu apstr\u0101des bibliot\u0113kas. Izlai\u0161ana notika <strong>6. gada 2026. j\u016bnij\u0101<\/strong> un jau tika atz\u012bm\u0113ta k\u0101 aktu\u0101la projekta kr\u0101jum\u0101 GitHub. OpenCV tiek izplat\u012bts saska\u0146\u0101 ar licenci <strong>Apache-2.0<\/strong>.<\/p>\n<p><\/noindex><\/noindex><\/p>\n<p>Izlai\u0161anas b\u016bt\u012bba ir OpenCV p\u0101reja no \"klasisk\u0101s datorredzes bibliot\u0113kas\" uz m\u016bsdien\u012bg\u0101ku platformu CV\/AI uzdevumiem: projekts att\u012bra veco API, p\u0101rstr\u0101d\u0101 neironu t\u012bklu inferences moduli, papla\u0161ina ONNX atbalstu, pievieno b\u0101zi VLM\/LLM scen\u0101rijiem un atjaunina 3D\/kalibr\u0101cijas steku. Izstr\u0101d\u0101t\u0101ji raksturo OpenCV 5.0 k\u0101 zaru, kas tagad tiek uzskat\u012bts par stabilu, un jaun\u0101 funkcionalit\u0101te galvenok\u0101rt tiks iek\u013cauta tur.<\/p>\n<h3>Galven\u0101s izmai\u0146as<\/h3>\n<ul>\n<li>\n<p><strong>Jauns DNN inferences dzin\u0113js.<\/strong><br \/>\nDNN modul\u012b par\u0101d\u012bj\u0101s jauns dzin\u0113js, kas l\u012bdz\u0101s vecajam. Tas lab\u0101k darbojas ar dinamisk\u0101m tensora form\u0101m, apak\u0161grafiem un m\u016bsdien\u012bg\u0101m ONNX iesp\u0113j\u0101m. Tiek apgalvots, ka tas aptver vair\u0101k nek\u0101 <strong>80% ONNX specifik\u0101cijas<\/strong>, savuk\u0101rt OpenCV 4.x aptv\u0113ra maz\u0101k par 23%.<br \/>\nTas, iesp\u0113jams, ir galvenais izmai\u0146u punkts izlaidum\u0101: OpenCV cen\u0161as k\u013c\u016bt nevis tikai par apvalku ap mode\u013ciem, bet par pilnties\u012bgu ieb\u016bv\u0113tu inferences dzin\u0113ju m\u016bsdienu neironu t\u012bklos.<\/p>\n<\/li>\n<li>\n<p><strong>Dzin\u0113ja izv\u0113le mode\u013ca iel\u0101dei.<\/strong><br \/>\ncv::dnn::readNet() un saist\u012btaj\u0101s funkcij\u0101s par\u0101d\u012bj\u0101s parametrs ENGINE_AUTO. P\u0113c noklus\u0113juma OpenCV vispirms izm\u0113\u0123ina jauno dzin\u0113ju, bet, ja tas neizdodas, atgrie\u017eas pie klasisk\u0101. Uzved\u012bbu var nor\u0101d\u012bt ar\u012b caur vides main\u012bgo OPENCV_FORCE_DNN_ENGINE: izmantot veco dzin\u0113ju, jauno, autom\u0101tisko re\u017e\u012bmu vai ONNX Runtime. Vecajiem projektiem nav nepiecie\u0161ams nekav\u0113joties piln\u012bb\u0101 p\u0101riet uz jauno dzin\u0113ju, bet jaunajiem mode\u013ciem to var pak\u0101peniski ieviest.<\/p>\n<\/li>\n<li>\n<p><strong>Integr\u0101cija ar ONNX Runtime.<\/strong><br \/>\nOpenCV tagad var tikt salikts ar piesaist\u012btu ONNX Runtime. \u0160aj\u0101 gad\u012bjum\u0101 OpenCV izmanto savu ONNX parseri, lai uzb\u016bv\u0113tu ORT grafu, t\u0101p\u0113c tas neprasa pilnu ONNX pakotni. Sav\u0101k\u0161anai paredz\u0113ti CMake parametri -DWITH_ONNXRUNTIME=ON un -DDOWNLOAD_ONNXRUNTIME=ON; NVIDIA GPU gad\u012bjum\u0101 \u2014 -DDOWNLOAD_ONNXRUNTIME_GPU=ON. Funkcija b\u016bs noder\u012bga tiem, kam nepiecie\u0161ama GPU inferences jau tagad, jo jaunais OpenCV DNN dzin\u0113js pagaid\u0101m darbojas tikai uz CPU.<\/p>\n<\/li>\n<li>\n<p><strong>Atbalsts redzes-valodas mode\u013ciem.<\/strong><br \/>\nJaunais DNN dzin\u0113js ietver tokenizatorus, uzman\u012bbas sl\u0101\u0146us, dekod\u0113\u0161anas blokos, p\u0113capstr\u0101di un KV ke\u0161u, kas nepiecie\u0161ami VLM mode\u013cu palai\u0161anai \"no kastes\u017e. Bibliot\u0113ka v\u0113sturiski ir bijusi saist\u012bta ar att\u0113lu apstr\u0101di, bet tagad iek\u013c\u016bst jom\u0101, kur mode\u013ci str\u0101d\u0101 ar att\u0113liem un tekstu vienlaikus.<\/p>\n<\/li>\n<li>\n<p><strong>Jaun\u0101 DNN dzin\u0113ja GPU atbalsts v\u0113l nav gatavs.<\/strong><br \/>\nJaunais dzin\u0113js OpenCV 5.0 str\u0101d\u0101 tikai uz CPU. Viet\u0113j\u0101 GPU atbalsta pievieno\u0161ana tiek sol\u012bta n\u0101kamajos laidienos; pagaid\u0101m GPU ieteicams izmantot klasisko dzin\u0113ju vai komplekt\u0101ciju ar ONNX Runtime un NVIDIA izpildes sniedz\u0113jiem. OpenCV 5.0 v\u0113l nesp\u0113j aizst\u0101t specializ\u0113tos darb\u012bbas vidus serveru vai galddatoru CUDA inferenc\u0113.<\/p>\n<\/li>\n<li>\n<p><strong>Tika iz\u0146emti vecie Darknet un Caffe analizatori.<\/strong><br \/>\nIzstr\u0101d\u0101t\u0101ji ir iz\u0146\u0113mu\u0161i Darknet un Caffe analizatorus, jo liel\u0101k\u0101 da\u013ca mode\u013cu jau ir p\u0101rv\u0113rsta ONNX. TFLite pagaid\u0101m paliek caur klasisko dzin\u0113ju, un p\u0101rvieto\u0161an\u0101s uz jauno dzin\u0113ju ir pl\u0101nota v\u0113l\u0101k. OpenCV atteicas no vecajiem form\u0101tiem un koncentr\u0113jas uz ONNX k\u0101 galveno mode\u013cu apmai\u0146as form\u0101tu.<\/p>\n<\/li>\n<li>\n<p><strong>Liela att\u012br\u012b\u0161ana no novecoju\u0161\u0101 API.<\/strong><br \/>\nIz\u0146emta OpenCV 1.x C API: t\u0101das funkcijas k\u0101 cvCreateMat() un vec\u0101s strukt\u016bras, piem\u0113ram, CvMat, vairs nav da\u013ca no galven\u0101 API. T\u0101pat tika iz\u0146emta OpenVX atbalsts, G-API modulis tika p\u0101rvietots uz opencv_contrib, tur tika nos\u016bt\u012bta ar\u012b klasisk\u0101 ML modulis. Lomu izmai\u0146as vecajiem projektiem, ta\u010du tas jau sen bija nepiecie\u0161ams: bibliot\u0113ka atbr\u012bvojas no tehnisk\u0101 par\u0101da, kas uzkr\u0101ts gadu desmitiem.<\/p>\n<\/li>\n<li>\n<p><strong>Features2D tika p\u0101rd\u0113v\u0113ts par Features.<\/strong><br \/>\nModulis ir papla\u0161in\u0101ts, lai iek\u013cautu m\u016bsdienu iez\u012bmju vektorus no neironu t\u012bklu. Galvenaj\u0101 repozitorij\u0101 atst\u0101ti SIFT, ORB, FAST, GoodFeaturesToTrack un MSER, bet novecoju\u0161i detektori un iez\u012bmju aprakst\u012bt\u0101ji tika p\u0101rvietoti uz opencv_contrib. Pievienoti ALIKED, DISK un LightGlue maatchers. OpenCV skaidri piel\u0101gojas m\u016bsdienu pl\u016bsm\u0101m, kuru iez\u012bmes bie\u017e\u0101k tiek ieg\u016btas no neironu t\u012bklu, nevis klasiskajiem algoritmiem.<\/p>\n<\/li>\n<li>\n<p><strong>Jauni datu tipi Core.<\/strong><br \/>\nPievienoti CV_16BF \/ cv::bfloat, CV_32U, CV_64U, CV_64S un CV_Bool. T\u0101pat uzlabots N-dimension\u0101lo mas\u012bvu, 1D mas\u012bvu un 0D skalaru atbalsts. LAPACK tagad vienm\u0113r ir pieejams: ja nav \u0101r\u0113j\u0101s bibliot\u0113kas, OpenCV izveido ieb\u016bv\u0113tu minim\u0101lo apak\u0161kopu. Izmai\u0146as ir svar\u012bgas DNN, numeriskajiem algoritmiem un sader\u012bbai ar m\u016bsdienu datu form\u0101tiem, kur bfloat16 un papla\u0161in\u0101tie tipi sastopami arvien bie\u017e\u0101k.<\/p>\n<\/li>\n<li>\n<p><strong>Tika pa\u0101trin\u0101ta att\u0113lu apstr\u0101de.<\/strong><br \/>\nImgproc ir p\u0101rstr\u0101d\u0101jusi warpAffine, warpPerspective un remap. Veiktsp\u0113jas uzlabojumi tiek apgalvoti no 10% l\u012bdz vair\u0101k nek\u0101 300% atkar\u012bb\u0101 no platformas, att\u0113la lieluma, datu veida un oper\u0101cijas karodzi\u0146iem.<br \/>\nTas vairs nav par AI modu \u2014 \u0161\u0101das optimiz\u0101cijas ir tie\u0161i svar\u012bgas klasiskaj\u0101m uzdevumiem: video straum\u0113m, stabiliz\u0101cijai, projekcijas transform\u0101cij\u0101m un datu sagatavo\u0161anai pirms inferences.<\/p>\n<\/li>\n<li>\n<p><strong>Teksta izvad\u012b\u0161ana ir uzlabota.<\/strong><br \/>\nVecais teksta render\u0113\u0161anas meh\u0101nisms ir aizst\u0101ts ar STB balst\u012btu TrueType dzin\u0113ju ar ieb\u016bv\u0113tu variat\u012bvo fontu Rubik. Ir iesp\u0113jams pievienot lietot\u0101ja fontus, un pla\u0161i tiek atbalst\u012bts Unicode. Tom\u0113r sare\u017e\u0123\u012btas rakst\u012bbas, piem\u0113ram, ar\u0101bu un devanagari, joproj\u0101m tiek att\u0113lotas nepareizi bez Harfbuzz, savuk\u0101rt kr\u0101sainie emoji netiek atbalst\u012bti. OpenCV k\u013c\u016bst \u0113rt\u0101ks anot\u0101ciju \u0123ener\u0113\u0161anai, atk\u013c\u016bdo\u0161anas att\u0113liem un vizualiz\u0101cij\u0101m bez \u0101r\u0113j\u0101m bibliot\u0113k\u0101m.<\/p>\n<\/li>\n<li>\n<p><strong>Atjaunin\u0101ta 3D un kameru kalibr\u0101cija.<\/strong><br \/>\nCalib3d ir sadal\u012bts geometrij\u0101, kalib, stereo un ptcloud. USAC ir k\u013cuvis par standarta aizmuguri stabilai homogr\u0101fijas, b\u016btisk\u0101s\/fundament\u0101l\u0101s matricas, PnP un citu uzdevumu v\u0113rt\u0113\u0161anai. Pievienota vair\u0101ku kameru kalibr\u0113\u0161anas caurule, s\u0101kotn\u0113jais atbalsts t\u012bklu un punktu m\u0101ko\u0146u apstr\u0101dei, tostarp TSDF, ICP, import\u0113\u0161anai un eksport\u0113\u0161anai .ply un .obj form\u0101t\u0101. Tas ir noz\u012bm\u012bgs solis robotik\u0101, SLAM, AR\/VR un vair\u0101ku kameru sist\u0113m\u0101s, kur viens 2D apstr\u0101de vairs nav pietiekama.<\/p>\n<\/li>\n<li>\n<p><strong>P\u0101rstr\u0101d\u0101ti piem\u0113ri un dokument\u0101cija.<\/strong><br \/>\nNovecojus\u012b piem\u0113ri ir iz\u0146emti, bet atliku\u0161ie ir atjaunin\u0101ti. DNN piem\u0113riem tiek izmantota kop\u012bga mode\u013cu kolekcija, ko var lejupiel\u0101d\u0113t ar skriptu download_models.py. Pievienoti eksperiment\u0101lie piem\u0113ri VLM un LDM, un dokument\u0101cija ir ieguvusi m\u016bsdien\u012bgu t\u0113mu, \u0101tru mekl\u0113\u0161anu, gai\u0161o\/tum\u0161o re\u017e\u012bmu un uzlabotu navig\u0101ciju. \u0160\u0101dai lielai bibliot\u0113kai tas nav kosm\u0113tisks uzlabojums: norm\u0101la dokument\u0101cija un str\u0101d\u0101jo\u0161i piem\u0113ri tie\u0161i ietekm\u0113 to, vai izstr\u0101d\u0101t\u0101ji var\u0113s p\u0101riet uz OpenCV 5.x.<\/p>\n<\/li>\n<\/ul>\n<p>Kopum\u0101 OpenCV 5.0 nav tikai v\u0113l viens rel\u012bze ar optimiz\u0101cij\u0101m, bet noz\u012bm\u012bgs visp\u0101r\u0113js atjaunin\u0101jums: maz\u0101k mantojuma no OpenCV 1.x \u0113ras un vair\u0101k nor\u0101des uz ONNX, neironu t\u012bklu inferenci, m\u016bsdien\u012bg\u0101m iez\u012bm\u0113m, 3D apstr\u0101di un heterog\u0113nu pa\u0101trin\u0101jumu. Tom\u0113r p\u0101reja vecajiem projektiem var pras\u012bt izmai\u0146as, jo tiek iz\u0146emts C API un da\u013ca modu\u013cu tiek p\u0101rnesta uz opencv_contrib.<\/p>\n<p>Avots: <a \ncontent=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.linux.org.ru\/news\/development\/18313193\">linux.org.ru<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u041e\u043f\u0443\u0431\u043b\u0438\u043a\u043e\u0432\u0430\u043d OpenCV 5.0.0 \u2014 \u043a\u0440\u0443\u043f\u043d\u044b\u0439 \u0432\u044b\u043f\u0443\u0441\u043a \u043e\u0442\u043a\u0440\u044b\u0442\u043e\u0439 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 \u043a\u043e\u043c\u043f\u044c\u044e\u0442\u0435\u0440\u043d\u043e\u0433\u043e \u0437\u0440\u0435\u043d\u0438\u044f \u0438 \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0439. \u0420\u0435\u043b\u0438\u0437 \u0441\u043e\u0441\u0442\u043e\u044f\u043b\u0441\u044f 6 \u0438\u044e\u043d\u044f 2026 \u0433\u043e\u0434\u0430 \u0438 \u0443\u0436\u0435 \u043e\u0442\u043c\u0435\u0447\u0435\u043d \u043a\u0430\u043a \u0430\u043a\u0442\u0443\u0430\u043b\u044c\u043d\u044b\u0439 \u0432 \u0440\u0435\u043f\u043e\u0437\u0438\u0442\u043e\u0440\u0438\u0438 \u043f\u0440\u043e\u0435\u043a\u0442\u0430 \u043d\u0430 GitHub. OpenCV \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. \u0421\u0443\u0442\u044c \u0440\u0435\u043b\u0438\u0437\u0430 \u2014 \u043f\u0435\u0440\u0435\u0445\u043e\u0434 OpenCV \u043e\u0442 \u00ab\u043a\u043b\u0430\u0441\u0441\u0438\u0447\u0435\u0441\u043a\u043e\u0439 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 \u043a\u043e\u043c\u043f\u044c\u044e\u0442\u0435\u0440\u043d\u043e\u0433\u043e \u0437\u0440\u0435\u043d\u0438\u044f\u00bb \u043a \u0431\u043e\u043b\u0435\u0435 \u0441\u043e\u0432\u0440\u0435\u043c\u0435\u043d\u043d\u043e\u0439 \u043f\u043b\u0430\u0442\u0444\u043e\u0440\u043c\u0435 \u0434\u043b\u044f CV\/AI-\u0437\u0430\u0434\u0430\u0447: \u043f\u0440\u043e\u0435\u043a\u0442 \u0432\u044b\u0447\u0438\u0441\u0442\u0438\u043b \u0441\u0442\u0430\u0440\u043e\u0435 API, \u043f\u0435\u0440\u0435\u0440\u0430\u0431\u043e\u0442\u0430\u043b [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":8,"featured_media":181945,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-181944","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.5 - 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