{"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\/ro\/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>Publicat <strong><a rel=\"nofollow\" href=\"https:\/\/github.com\/opencv\/opencv\">OpenCV 5.0.0<\/a><\/strong> \u2014 o mare versiune a bibliotecii deschise pentru viziune computerizat\u0103 \u0219i procesarea imaginilor. Lansarea a avut loc <strong>6 iunie 2026<\/strong> \u0219i este deja marcat\u0103 ca relevant\u0103 \u00een repository-ul proiectului de pe GitHub. OpenCV este distribuit sub licen\u021ba <strong>Apache-2.0<\/strong>.<\/p>\n<p><\/noindex><\/noindex><\/p>\n<p>Scopul lans\u0103rii este tranzi\u021bia OpenCV de la \u201ebiblioteca clasic\u0103 de viziune computerizat\u0103\u201d la o platform\u0103 mai modern\u0103 pentru sarcini CV\/AI: proiectul a cur\u0103\u021bat API-ul vechi, a reproiectat modulul de inferen\u021b\u0103 a re\u021belelor neuronale, a extins suportul pentru ONNX, a ad\u0103ugat suport pentru scenarii VLM\/LLM \u0219i a actualizat stiva de 3D\/calibrare. Dezvoltatorii descriu OpenCV 5.0 ca o ramur\u0103, care este acum considerat\u0103 stabil\u0103, iar noua func\u021bionalitate va fi ad\u0103ugat\u0103 preponderent acolo.<\/p>\n<h3>Principalele modific\u0103ri<\/h3>\n<ul>\n<li>\n<p><strong>Un nou motor de inferen\u021b\u0103 DNN.<\/strong><br \/>\n\u00cen modulul dnn a ap\u0103rut un nou motor, care coexist\u0103 cu cel vechi. Acesta func\u021bioneaz\u0103 mai bine cu formele dinamice de tensori, subgrafuri \u0219i posibilit\u0103\u021bile moderne ale ONNX. Se declar\u0103 o acoperire de peste <strong>80% din specifica\u021bia ONNX<\/strong>, \u00een timp ce \u00een OpenCV 4.x era acoperit\u0103 mai pu\u021bin de 23%.<br \/>\nAceasta este, probabil, cea mai important\u0103 schimbare a lans\u0103rii: OpenCV \u00eencearc\u0103 s\u0103 devin\u0103 nu doar un wrapper pentru modele, ci un motor de inferen\u021b\u0103 integrat complet pentru re\u021bele neuronale moderne.<\/p>\n<\/li>\n<li>\n<p><strong>Alegerea motorului la \u00eenc\u0103rcarea modelului.<\/strong><br \/>\n\u00cen cv::dnn::readNet() \u0219i func\u021biile similare a ap\u0103rut parametrul ENGINE_AUTO. Implicit, OpenCV \u00eencearc\u0103 mai \u00eent\u00e2i noul motor, iar \u00een caz de e\u0219ec revine la cel clasic. Comportamentul poate fi, de asemenea, setat prin variabila de mediu OPENCV_FORCE_DNN_ENGINE: utilizarea motorului vechi, nou, mod automat sau ONNX Runtime. Proiectele vechi nu sunt obligate s\u0103 treac\u0103 complet pe noul motor imediat, dar noile modele pot fi treptat adaptate la acesta.<\/p>\n<\/li>\n<li>\n<p><strong>Integrarea cu ONNX Runtime.<\/strong><br \/>\nOpenCV poate fi acum compilat cu ONNX Runtime conectat. \u00cen acest caz, OpenCV folose\u0219te propriul s\u0103u parser ONNX pentru construirea graficului ORT, astfel \u00eenc\u00e2t nu necesit\u0103 \u00eentregul pachet ONNX. Pentru compilare, sunt prev\u0103zute parametrii CMake -DWITH_ONNXRUNTIME=ON \u0219i -DDOWNLOAD_ONNXRUNTIME=ON; pentru GPU NVIDIA \u2014 -DDOWNLOAD_ONNXRUNTIME_GPU=ON. Aceast\u0103 func\u021bie va fi util\u0103 pentru cei care au nevoie de inferen\u021b\u0103 GPU imediat, deoarece noul motor DNN OpenCV func\u021bioneaz\u0103 deocamdat\u0103 doar pe CPU.<\/p>\n<\/li>\n<li>\n<p><strong>Suport pentru modele de viziune-limbaj.<\/strong><br \/>\nNoul motor DNN include tokenizatori, straturi de aten\u021bie, blocuri de decodificare, postprocesare \u0219i cache KV necesare pentru a rula modelele VLM \u201edin cutie\u201d. Biblioteca a fost istoric asociat\u0103 cu procesarea imaginilor, iar acum se extinde \u00een domeniul modelor care lucreaz\u0103 simultan cu imaginea \u0219i textul.<\/p>\n<\/li>\n<li>\n<p><strong>Suportul GPU pentru noul motor DNN nu este \u00eenc\u0103 disponibil.<\/strong><br \/>\nNoul motor \u00een OpenCV 5.0 func\u021bioneaz\u0103 doar pe CPU. Suportul nativ pentru GPU se promite a fi ad\u0103ugat \u00een versiunile viitoare; \u00een prezent, pentru GPU se recomand\u0103 utilizarea motorului clasic sau a unei construc\u021bii cu ONNX Runtime \u0219i furnizorii de execu\u021bie NVIDIA. OpenCV 5.0 nu \u00eenlocuie\u0219te de sine st\u0103t\u0103tor runtime-urile specializate pentru inferen\u021ba CUDA pe server sau desktop.<\/p>\n<\/li>\n<li>\n<p><strong>Parserii vechi Darknet \u0219i Caffe au fost elimina\u021bi.<\/strong><br \/>\nDezvoltatorii au eliminat parserii Darknet \u0219i Caffe, deoarece majoritatea modelor au fost deja migrate \u00een ONNX. TFLite r\u0103m\u00e2ne pentru moment prin motorul clasic, iar migrarea c\u0103tre noul motor este planificat\u0103 ulterior. OpenCV abandonaz\u0103 formatele vechi \u0219i se concentreaz\u0103 pe ONNX ca pe principalul format de schimb al modelelor.<\/p>\n<\/li>\n<li>\n<p><strong>O mare cur\u0103\u021bare a API-ului \u00eenvechit.<\/strong><br \/>\nAPI-ul C OpenCV 1.x a fost eliminat: func\u021bii precum cvCreateMat() \u0219i structuri vechi de tip CvMat nu mai fac parte din API-ul principal. Suportul pentru OpenVX a fost de asemenea eliminat, modul G-API a fost mutat \u00een opencv_contrib, iar clasicul modul ML a fost de asemenea trimis acolo. O modificare semnificativ\u0103 pentru proiectele vechi, dar era necesar\u0103: biblioteca \u00ee\u0219i elimin\u0103 datoria tehnic\u0103 acumulat\u0103 de decenii.<\/p>\n<\/li>\n<li>\n<p><strong>Features2D a fost redenumit \u00een Features.<\/strong><br \/>\nModulul a fost extins pentru vectorii moderni de caracteristici din re\u021bele neuronale. \u00cen repository-ul principal au r\u0103mas SIFT, ORB, FAST, GoodFeaturesToTrack \u0219i MSER, \u00een timp ce detectorii \u0219i descriptorii \u00eenvechi\u021bi au fost muta\u021bi \u00een opencv_contrib. Au fost ad\u0103ugate ALIKED, DISK \u0219i asigur\u0103torul LightGlue. OpenCV se adapteaz\u0103 clar la pipeline-urile moderne, unde caracteristicile imaginii sunt tot mai frecvent extrase nu prin algoritmi clasici, ci prin re\u021bele neuronale.<\/p>\n<\/li>\n<li>\n<p><strong>Tipuri noi de date \u00een Core.<\/strong><br \/>\nAu fost ad\u0103ugate CV_16BF \/ cv::bfloat, CV_32U, CV_64U, CV_64S \u0219i CV_Bool. Suportul pentru matricele N-dimensionale, matricele 1D \u0219i scalarii 0D a fost \u00eembun\u0103t\u0103\u021bit. LAPACK este acum \u00eentotdeauna disponibil: dac\u0103 biblioteca extern\u0103 nu este disponibil\u0103, OpenCV compileaz\u0103 un subset minim \u00eencorporat. Modific\u0103rile sunt importante pentru DNN, algoritmi numerici \u0219i compatibilitatea cu formatele de date moderne, unde bfloat16 \u0219i tipurile extinse sunt \u00eent\u00e2lnite tot mai frecvent.<\/p>\n<\/li>\n<li>\n<p><strong>Procesarea imaginilor a fost accelerat\u0103.<\/strong><br \/>\n\u00cen imgproc au fost reworkate warpAffine, warpPerspective \u0219i remap. \u00cembun\u0103t\u0103\u021birile de performan\u021b\u0103 sunt anun\u021bate \u00een intervalul de la 10% la peste 300%, \u00een func\u021bie de platform\u0103, dimensiunea imaginii, tipul de date \u0219i flagurile de opera\u021bie.<br \/>\nAcesta nu mai este despre modul AI \u2014 aceste optimiz\u0103ri sunt direct importante pentru sarcinile clasice: fluxuri video, stabilizare, transform\u0103ri de proiec\u021bie \u0219i preg\u0103tirea datelor \u00eenainte de inferen\u021b\u0103.<\/p>\n<\/li>\n<li>\n<p><strong>A fost \u00eembun\u0103t\u0103\u021bit\u0103 redarea textului.<\/strong><br \/>\nVechea mecanism de redare a textului a fost \u00eenlocuit de motorul bazat pe STB pentru TrueType, cu fontul variabil Rubik \u00eencorporat. Pot fi ata\u0219ate fonturi personalizate, iar suportul Unicode a fost extins. Cu toate acestea, scrierile complexe, cum ar fi araba \u0219i devanagari, sunt \u00eenc\u0103 afi\u0219ate incorect f\u0103r\u0103 Harfbuzz, iar emoji-urile colorate nu sunt suportate. OpenCV devine mai u\u0219or de utilizat pentru generarea de adnot\u0103ri, imagini de depanare \u0219i vizualiz\u0103ri f\u0103r\u0103 biblioteci externe.<\/p>\n<\/li>\n<li>\n<p><strong>Au fost actualizate 3D \u0219i calibrarea camerelor.<\/strong><br \/>\ncalib3d a fost \u00eemp\u0103r\u021bit \u00een geometry, calib, stereo \u0219i ptcloud. USAC a devenit backend standard pentru estimarea robust\u0103 a omografiei, matricea esen\u021bial\u0103\/fundamental\u0103, PnP \u0219i alte sarcini. A fost ad\u0103ugat un pipeline pentru calibrarea multi-camerelor, suport ini\u021bial pentru procesarea re\u021belelor \u0219i a norilor de puncte, inclusiv TSDF, ICP, import \u0219i export .ply \u0219i .obj. Acesta este un pas important pentru robotic\u0103, SLAM, AR\/VR \u0219i sisteme multi-camer\u0103, unde o procesare 2D nu mai este suficient\u0103.<\/p>\n<\/li>\n<li>\n<p><strong>Au fost revizuite exemplele \u0219i documenta\u021bia.<\/strong><br \/>\nExemplele \u00eenvechite au fost eliminate, iar cele r\u0103mase au fost actualizate. Pentru exemplele DNN se folose\u0219te o colec\u021bie comun\u0103 de modele, care poate fi desc\u0103rcat\u0103 prin scriptul download_models.py. Au fost ad\u0103ugate exemple experimentale pentru VLM \u0219i LDM, iar documenta\u021bia a primit un design modern, c\u0103utare rapid\u0103, mod deschis\/\u00eentunecat \u0219i navigare \u00eembun\u0103t\u0103\u021bit\u0103. Pentru o bibliotec\u0103 at\u00e2t de mare, aceasta nu este o simpl\u0103 schimbare cosmetic\u0103: o documenta\u021bie normal\u0103 \u0219i exemple func\u021bionale influen\u021beaz\u0103 direct dac\u0103 dezvoltatorii pot trece efectiv la OpenCV 5.x.<\/p>\n<\/li>\n<\/ul>\n<p>\u00cen final, OpenCV 5.0 nu este doar o alt\u0103 lansare cu optimiz\u0103ri, ci o actualizare semnificativ\u0103 a tot: mai pu\u021bin mo\u0219tenire din epoca OpenCV 1.x \u0219i mai multe orient\u0103ri c\u0103tre ONNX, inferen\u021b\u0103 de re\u021bea neural\u0103, caracteristici moderne, procesare 3D \u0219i accelerare heterogen\u0103. Cu toate acestea, trecerea pentru proiectele vechi poate necesita modific\u0103ri din cauza elimin\u0103rii API-ului C \u0219i mut\u0103rii unei p\u0103r\u021bi din module \u00een opencv_contrib.<\/p>\n<p>Sursa: <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 5.0.2.1 - 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