{"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\/pl\/blog\/news\/hyperstyle-adaptacziya-sistemy-mashinnogo-obucheniya-stylegan-dlya-redaktirovaniya-izobrazhenij","title":{"rendered":"HyperStyle \u2014 adaptacja systemu uczenia maszynowego StyleGAN do edycji obraz\u00f3w","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Zesp\u00f3\u0142 badaczy z Uniwersytetu Telawiwskiego zaprezentowa\u0142 HyperStyle, odwr\u00f3con\u0105 wersj\u0119 systemu uczenia maszynowego StyleGAN2 opracowywanego przez firm\u0119 NVIDIA, przekszta\u0142con\u0105 do rekonstrukcji brakuj\u0105cych cz\u0119\u015bci podczas edytowania rzeczywistych obraz\u00f3w. Kod napisano w j\u0119zyku Python z wykorzystaniem frameworka PyTorch i jest udost\u0119pniany na licencji MIT. <\/p>\n

Podczas gdy StyleGAN pozwala na syntetyzowanie realistycznie wygl\u0105daj\u0105cych nowych twarzy, okre\u015blaj\u0105c takie parametry, jak wiek, p\u0142e\u0107, d\u0142ugo\u015b\u0107 w\u0142os\u00f3w, kszta\u0142t u\u015bmiechu, kszta\u0142t nosa, kolor sk\u00f3ry, okulary oraz k\u0105t zdj\u0119cia, HyperStyle umo\u017cliwia zmian\u0119 podobnych parametr\u00f3w na ju\u017c istniej\u0105cych fotografiach, nie zmieniaj\u0105c ich cech charakterystycznych i zachowuj\u0105c rozpoznawalno\u015b\u0107 oryginalnej twarzy. Na przyk\u0142ad, za pomoc\u0105 HyperStyle mo\u017cna symulowa\u0107 zmian\u0119 wieku osoby na zdj\u0119ciu, zmieni\u0107 fryzur\u0119, doda\u0107 okulary, brod\u0119 lub w\u0105sy, nada\u0107 obrazowi wygl\u0105d postaci z kresk\u00f3wki lub malowanej ilustracji, sprawi\u0107, \u017ce wyraz twarzy b\u0119dzie smutny lub weso\u0142y. System mo\u017ce by\u0107 r\u00f3wnie\u017c trenowany nie tylko do zmiany twarzy, ale i dowolnych obiekt\u00f3w, na przyk\u0142ad do edytowania obraz\u00f3w samochod\u00f3w.

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

Proponowana metoda ma na celu rozwi\u0105zanie problemu rekonstrukcji brakuj\u0105cych cz\u0119\u015bci obrazu podczas edytowania. W wcze\u015bniej proponowanych metodach kompromis mi\u0119dzy rekonstrukcj\u0105 a edytowalno\u015bci\u0105 by\u0142 osi\u0105gany poprzez drobne dostosowanie generatora obraz\u00f3w do wstawiania cz\u0119\u015bci docelowego obrazu podczas rekonstrukcji pierwotnie brakuj\u0105cych edytowalnych obszar\u00f3w. Wad\u0105 takich podej\u015b\u0107 jest konieczno\u015b\u0107 przeprowadzenia d\u0142ugotrwa\u0142ego treningu sieci neuronowej dla ka\u017cdego obrazu. <\/p>\n

Metoda oparta na algorytmie StyleGAN umo\u017cliwia wykorzystanie typowego modelu, wcze\u015bniej wytrenowanego na og\u00f3lnych zbiorach obraz\u00f3w, do generowania element\u00f3w charakterystycznych dla oryginalnego obrazu z poziomem wiarygodno\u015bci por\u00f3wnywalnym z algorytmami wymagaj\u0105cymi indywidualnego treningu modelu dla ka\u017cdego obrazu. Zalet\u0105 nowej metody jest r\u00f3wnie\u017c mo\u017cliwo\u015b\u0107 modyfikowania obraz\u00f3w z wydajno\u015bci\u0105 zbli\u017con\u0105 do trybu rzeczywistego.

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

Gotowe, wytrenowane modele s\u0105 dost\u0119pne dla ludzkich twarzy, samochod\u00f3w i zwierz\u0105t na podstawie zbior\u00f3w Flickr-Faces-HQ (FFHQ, 70 tysi\u0119cy wysokiej jako\u015bci obraz\u00f3w PNG ludzi), Stanford Cars (16 tysi\u0119cy zdj\u0119\u0107 samochod\u00f3w) i AFHQ (zdj\u0119cia zwierz\u0105t). Dodatkowo dost\u0119pne s\u0105 narz\u0119dzia do trenowania w\u0142asnych modeli, a tak\u017ce gotowe, wytrenowane modele typowych kodownik\u00f3w i generator\u00f3w, kt\u00f3re mo\u017cna z nimi wykorzysta\u0107. Na przyk\u0142ad dost\u0119pne s\u0105 generatory do tworzenia obrazk\u00f3w w stylu Toonify, postaci Pixara, szkic\u00f3w oraz do stylizacji na ksi\u0119\u017cniczki z film\u00f3w Disneya.

\"HyperStyle<\/center>
\"HyperStyle<\/center>
\"HyperStyle<\/center>
\"HyperStyle<\/center>
\n
\u0179r\u00f3d\u0142o: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

\u0413\u0440\u0443\u043f\u043f\u0430 \u0438\u0441\u0441\u043b\u0435\u0434\u043e\u0432\u0430\u0442\u0435\u043b\u0435\u0439 \u0438\u0437 \u0422\u0435\u043b\u044c-\u0410\u0432\u0438\u0432\u0441\u043a\u043e\u0433\u043e \u0443\u043d\u0438\u0432\u0435\u0440\u0441\u0438\u0442\u0435\u0442\u0430 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u0438\u043b\u0430 HyperStyle, \u0438\u043d\u0432\u0435\u0440\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0439 \u0432\u0430\u0440\u0438\u0430\u043d\u0442 \u0440\u0430\u0437\u0432\u0438\u0432\u0430\u0435\u043c\u043e\u0439 \u043a\u043e\u043c\u043f\u0430\u043d\u0438\u0435\u0439 NVIDIA \u0441\u0438\u0441\u0442\u0435\u043c\u044b \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f StyleGAN2, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u043f\u0435\u0440\u0435\u0440\u0430\u0431\u043e\u0442\u0430\u043d \u0434\u043b\u044f \u0432\u043e\u0441\u0441\u043e\u0437\u0434\u0430\u043d\u0438\u044f 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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\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 adaptacja systemu uczenia maszynowego StyleGAN do edytowania obraz\u00f3w | ProHoster","description":"Zesp\u00f3\u0142 badaczy z Uniwersytetu w Tel Awiwie zaprezentowa\u0142 HyperStyle, odwr\u00f3con\u0105 wersj\u0119 opracowywanego przez firm\u0119 NVIDIA systemu uczenia maszynowego StyleGAN2, kt\u00f3ry zosta\u0142 przekszta\u0142cony w celu rekonstrukcji brakuj\u0105cych 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