{"id":102454,"date":"2021-12-03T15:36:38","date_gmt":"2021-12-03T13:36:42","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/hyperstyle-adaptacziya-sistemy-mashinnogo-obucheniya-stylegan-dlya-redaktirovaniya-izobrazhenij"},"modified":"2021-12-03T15:36:38","modified_gmt":"2021-12-03T13:36:42","slug":"hyperstyle-adaptacziya-sistemy-mashinnogo-obucheniya-stylegan-dlya-redaktirovaniya-izobrazhenij","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sl\/blog\/news\/hyperstyle-adaptacziya-sistemy-mashinnogo-obucheniya-stylegan-dlya-redaktirovaniya-izobrazhenij","title":{"rendered":"HyperStyle \u2014 prilagoditev sistema strojnega u\u010denja StyleGAN za urejanje slik.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Skupina raziskovalcev s Telavivske univerze je predstavila HyperStyle, obrnjen razli\u010dica sistema strojnega u\u010denja StyleGAN2, razvitega s strani podjetja NVIDIA, ki je bila predelana za obnovo manjkajo\u010dih delov pri urejanju resni\u010dnih slik. Koda je napisana v programskem jeziku Python s pomo\u010djo ogrodja PyTorch in se distribuira pod MIT licenco. <\/p>\n

Medtem ko StyleGAN omogo\u010da sintezo realno vidnih novih obrazov ljudi z dolo\u010ditvijo tak\u0161nih parametrov kot so starost, spol, dol\u017eina las, zna\u010daj nasmeha, oblika nosu, barva ko\u017ee, o\u010dala in kot fotografije, HyperStyle omogo\u010da spreminjanje podobnih parametrov na obstoje\u010dih fotografijah, ne da bi spremenil njihove zna\u010dilne zna\u010dilnosti in ohranil prepoznavnost izvirnega obraza. Na primer, s pomo\u010djo HyperStyle lahko simulirate spremembo starosti osebe na fotografiji, spremenite frizuro, dodate o\u010dala, brado ali brke, naredite sliko videti kot lik iz risanke ali slikane slike, ter izraz obraza spremenite v tu\u017enega ali veseljega. Sistem lahko usposobite ne le za spreminjanje \u010dlove\u0161kih obrazov, temve\u010d tudi za vse vrste predmetov, na primer za urejanje slik avtomobilov.

\"HyperStyle<\/center> <\/p>\n

Obravnavana metoda je usmerjena v re\u0161evanje problema rekonstrukcije manjkajo\u010dih delov slike pri urejanju. V prej predlaganih metodah je bila izbira med rekonstrukcijo in urejanjem re\u0161ena z natan\u010dnim nastavljanjem generatorja slik za vlo\u017eitev delov ciljne slike pri obnovi prvotno manjkajo\u010dih urejenih podro\u010dij. Pomanjkljivost podobnih pristopov je potreba po dolgotrajnem ciljnem usposabljanju nevronske mre\u017ee za vsako sliko. <\/p>\n

Metoda, ki temelji na algoritmu StyleGAN, omogo\u010da uporabo standardnega modela, vnaprej usposobljenega na splo\u0161nih zbirkah slik, za generiranje elementov, zna\u010dilnih za izvirno sliko, z ravnjo verodostojnosti, primerljivo z algoritmi, ki zahtevajo individualno usposabljanje modela za vsako sliko. Med prednostmi nove metode se izpostavlja tudi mo\u017enost spreminjanja slik z zmogljivostjo, blizu realnemu \u010dasu.

\"HyperStyle<\/center> <\/p>\n

Modeli i trenirani modeli su pripremljeni za lica ljudi, automobila i \u017eivotinja na osnovu kolekcija Flickr-Faces-HQ (FFHQ, 70.000 visokokvalitetnih PNG slika ljudskih lica), Stanford Cars (16.000 slika automobila) i AFHQ (fotografije \u017eivotinja). Dodatno je obezbe\u0111en alat za obuku vlastitih modela, kao i gotovi trenirani modeli generi\u010dkih enkodera i generatora koje je mogu\u0107e koristiti. Na primer, dostupni su generatori za kreiranje slika u stilu Toonify, Pixar likova, formiranje skica i \u010dak stilizovanje kao princeze iz Disneyevih crta\u0107a.

\"HyperStyle<\/center>
\"HyperStyle<\/center>
\"HyperStyle<\/center>
\"HyperStyle<\/center>
\n
Izvor: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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[…]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":102455,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-102454","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\n","aioseo_head_json":{"title":"\ud83e\udd47HyperStyle \u2014 adaptacija sistema ma\u0161inskog u\u010denja StyleGAN za ure\u0111ivanje slika | ProHoster","description":"Grupa istra\u017eiva\u010da sa Tel Aviv Univerziteta predstavila je HyperStyle, invertovanu verziju sistema ma\u0161inskog u\u010denja StyleGAN2 koji razvija kompanija NVIDIA, koja je prerada kako bi se rekonstruisale nedostaju\u0107e 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