{"id":53128,"date":"2019-11-24T00:00:00","date_gmt":"2019-11-23T21:00:00","guid":{"rendered":"https:\/\/prohoster.info\/blog\/blog_prohoster\/google-vypustil-distributiv-mendel-linux-4-0-dlya-plat-coral"},"modified":"2020-02-18T14:00:59","modified_gmt":"2020-02-18T11:00:59","slug":"google-vypustil-distributiv-mendel-linux-4-0-dlya-plat-coral","status":"publish","type":"post","link":"https:\/\/prohoster.info\/pl\/blog\/news\/google-vypustil-distributiv-mendel-linux-4-0-dlya-plat-coral","title":{"rendered":"Google wyda\u0142 dystrybucj\u0119 Mendel Linux 4.0 dla p\u0142yt Coral","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Firma Google <noindex><a rel=\"nofollow\" href=\"https:\/\/developers.googleblog.com\/2019\/11\/updates-from-coral-mendel-linux-4.html\">przedstawi\u0142a<\/a><\/noindex> aktualizacja dystrybucji <noindex><a rel=\"nofollow\" href=\"https:\/\/coral.ai\/software\/#mendel-linux\">Mendel Linux<\/a><\/noindex>, zaprojektowanego do u\u017cycia na p\u0142ytach <noindex><a rel=\"nofollow\" href=\"https:\/\/coral.ai\/\">Coral<\/a><\/noindex>, takich jak <noindex><a rel=\"nofollow\" href=\"https:\/\/coral.ai\/products\/dev-board\/\">Dev Board<\/a><\/noindex> i <noindex><a rel=\"nofollow\" href=\"https:\/\/coral.ai\/products\/som\/\">SoM<\/a><\/noindex>. P\u0142yta Dev Board stanowi platform\u0119 do szybkiego prototypowania system\u00f3w sprz\u0119towych opartych na <noindex><a rel=\"nofollow\" href=\"https:\/\/ru.wikipedia.org\/wiki\/%D0%A2%D0%B5%D0%BD%D0%B7%D0%BE%D1%80%D0%BD%D1%8B%D0%B9_%D0%BF%D1%80%D0%BE%D1%86%D0%B5%D1%81%D1%81%D0%BE%D1%80_Google\">Google Edge TPU<\/a><\/noindex> (Tensor Processing Unit) w celu przyspieszenia operacji zwi\u0105zanych z uczeniem maszynowym i sieciami neuronowymi. SoM (System-on-Module) jest jednym z gotowych rozwi\u0105za\u0144 do wykonywania aplikacji zwi\u0105zanych z uczeniem maszynowym.<\/p>\n<p>Distro Mendel Linux <noindex><a rel=\"nofollow\" href=\"https:\/\/coral.googlesource.com\/docs\/+\/refs\/heads\/master\/ReadMe.md\">za\u0142o\u017cony<\/a><\/noindex> oparte na pakietach Debian i w pe\u0142ni zgodne z repozytoriami tego projektu (wykorzystywane s\u0105 niezmienione pakiety binarne i aktualizacje z g\u0142\u00f3wnych repozytori\u00f3w Debiana). Zmiany sprowadzaj\u0105 si\u0119 do budowy obrazu, kt\u00f3ry jest \u0142adowany z kart eMMC, oraz do w\u0142\u0105czenia komponent\u00f3w wspieraj\u0105cych sprz\u0119t platformy Coral. Specyficzne dla Coral komponenty <noindex><a rel=\"nofollow\" href=\"https:\/\/coral.googlesource.com\/\">s\u0105 rozpowszechniane<\/a><\/noindex> na licencji Apache 2.0. <\/p>\n<p>Mendel Linux 4.0 <noindex><a rel=\"nofollow\" href=\"https:\/\/coral.googlesource.com\/docs\/+\/refs\/heads\/master\/Releases.md\">zacz\u0105\u0142<\/a><\/noindex> pierwsza wersja, zaktualizowana do Debian 10 (&#171;buster&#187;). Kompilacja jest zoptymalizowana pod k\u0105tem system\u00f3w wbudowanych i nie zawiera zb\u0119dnych element\u00f3w, w tym nowo\u015bci Debian 10 zwi\u0105zanych z obs\u0142ug\u0105 SecureBoot i AppArmor. Spo\u015br\u00f3d nowo\u015bci wyr\u00f3\u017cnia si\u0119 wsparcie dla OpenCV i OpenCL, wykorzystanie nak\u0142adek Device Tree, a tak\u017ce aktualizacja GStreamer, Pythona 3.7, j\u0105dra Linux 4.14 oraz bootloadera U-Boot w wersji 2017.03.3. <\/p>\n<p>W\u015br\u00f3d specyficznych nowinek wymienia si\u0119 mo\u017cliwo\u015b\u0107 wykorzystania GPU (Vivante GC7000) montowanego na p\u0142ytach Coral do przyspieszenia konwersji danych pikselowych z modelu kolor\u00f3w YUV na RGB z wydajno\u015bci\u0105 do 130 klatek na sekund\u0119 dla wideo w rozdzielczo\u015bci 1080p, co mo\u017ce by\u0107 przydatne w przypadku u\u017cywania p\u0142yt do przetwarzania wideo z kamer generuj\u0105cych strumie\u0144 w formacie YUV. Do zastosowa\u0144 uczenia maszynowego w przetwarzaniu strumieniowego wideo i d\u017awi\u0119ku w czasie rzeczywistym sugeruje si\u0119 u\u017cycie otwartego frameworka <noindex><a rel=\"nofollow\" href=\"https:\/\/mediapipe.dev\/\">MediaPipe<\/a><\/noindex>. Na jego podstawie mo\u017cna <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/google\/mediapipe\/tree\/master\/mediapipe\/examples\/coral\">wdro\u017cenie<\/a><\/noindex> stworzy\u0107 system rozpoznawania i \u015bledzenia obiekt\u00f3w lub twarzy w wideo przesy\u0142anym z kamery monitoruj\u0105cej.<\/p>\n<p>Gotowe i ju\u017c wytr trenowane typowe modele uczenia maszynowego, skompilowane dla procesor\u00f3w Edge TPU u\u017cywanych na p\u0142ytach Coral, s\u0105 nadal dostarczane na <noindex><a rel=\"nofollow\" href=\"https:\/\/coral.ai\/models\/\">stronie projektu<\/a><\/noindex>, ale stopniowo przenoszone s\u0105 r\u00f3wnie\u017c do og\u00f3lnego katalogu publicznych modeli <noindex><a rel=\"nofollow\" href=\"https:\/\/tfhub.dev\/\">TensorFlow Hub<\/a><\/noindex>. Aby u\u0142atwi\u0107 rozw\u00f3j w\u0142asnych rozwi\u0105za\u0144 opartych na p\u0142ytach Coral i Mendel Linux, przygotowano <noindex><a rel=\"nofollow\" href=\"https:\/\/coral.ai\/projects\/teachable-sorter\/\">przewodnik<\/a><\/noindex>, pokazuj\u0105ce jak z materia\u0142\u00f3w dost\u0119pnych w domu zbudowa\u0107 inteligentny sorter, kt\u00f3ry rozdziela kolorowe i bia\u0142e kulki do r\u00f3\u017cnych koszy, wykorzystuj\u0105c Raspberry Pi i Coral USB Accelerator.<\/p>\n<p><center><div class=\"youtube-placeholder\" data-id=\"ydzJPeeMiMI\" onclick=\"loadVideo(this)\">\r\n        <img decoding=\"async\" src=\"https:\/\/img.youtube.com\/vi\/ydzJPeeMiMI\/hqdefault.jpg\" alt=\"Odtwarzaj wideo\" loading=\"lazy\" width=\"480\" height=\"360\" style=\"width:100%;height:auto;\">\r\n        <div class=\"play-button\"><\/div>\r\n    <\/div><\/center><\/p>\n<p><noindex><a rel=\"nofollow\" name=\"link\"><\/a><\/noindex><\/p>\n<p>\u0179r\u00f3d\u0142o: <a \ncontent=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=51924\">opennet.ru<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u041a\u043e\u043c\u043f\u0430\u043d\u0438\u044f Google \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u0438\u043b\u0430 \u043e\u0431\u043d\u043e\u0432\u043b\u0435\u043d\u0438\u0435 \u0434\u0438\u0441\u0442\u0440\u0438\u0431\u0443\u0442\u0438\u0432\u0430 Mendel Linux, \u043f\u0440\u0435\u0434\u043d\u0430\u0437\u043d\u0430\u0447\u0435\u043d\u043d\u043e\u0433\u043e \u0434\u043b\u044f \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u043d\u0430 \u043f\u043b\u0430\u0442\u0430\u0445 Coral, \u0442\u0430\u043a\u0438\u0445 \u043a\u0430\u043a Dev Board \u0438 SoM. \u041f\u043b\u0430\u0442\u0430 Dev Board \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 \u0441\u043e\u0431\u043e\u0439 \u043f\u043b\u0430\u0442\u0444\u043e\u0440\u043c\u0443 \u0434\u043b\u044f \u0431\u044b\u0441\u0442\u0440\u043e\u0439 \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u043f\u0440\u043e\u0442\u043e\u0442\u0438\u043f\u043e\u0432 \u0430\u043f\u043f\u0430\u0440\u0430\u0442\u043d\u044b\u0445 \u0441\u0438\u0441\u0442\u0435\u043c \u043d\u0430 \u0431\u0430\u0437\u0435 Google Edge TPU (Tensor Processing Unit) \u0434\u043b\u044f \u0443\u0441\u043a\u043e\u0440\u0435\u043d\u0438\u044f \u043e\u043f\u0435\u0440\u0430\u0446\u0438\u0439, \u0441\u0432\u044f\u0437\u0430\u043d\u043d\u044b\u0445 \u0441 \u043c\u0430\u0448\u0438\u043d\u043d\u044b\u043c \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u0435\u043c \u0438 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u043c\u0438 \u0441\u0435\u0442\u044f\u043c\u0438. SoM (System-on-Module) \u044f\u0432\u043b\u044f\u0435\u0442\u0441\u044f \u043e\u0434\u043d\u0438\u043c \u0438\u0437 \u0433\u043e\u0442\u043e\u0432\u044b\u0445 [&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-53128","post","type-post","status-publish","format-standard","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.1.1 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u041a\u043e\u043c\u043f\u0430\u043d\u0438\u044f Google \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u0438\u043b\u0430 \u043e\u0431\u043d\u043e\u0432\u043b\u0435\u043d\u0438\u0435 \u0434\u0438\u0441\u0442\u0440\u0438\u0431\u0443\u0442\u0438\u0432\u0430\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta 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