{"id":29895,"date":"2019-10-31T21:32:30","date_gmt":"2019-10-31T18:32:30","guid":{"rendered":"https:\/\/prohoster.info\/blog\/nejroset-ot-nvidia-prevrashhaet-prostejshie-nabroski-v-krasivye-pejzazhi\/"},"modified":"2019-10-31T21:32:30","modified_gmt":"2019-10-31T18:32:30","slug":"nejroset-ot-nvidia-prevrashhaet-prostejshie-nabroski-v-krasivye-pejzazhi","status":"publish","type":"post","link":"https:\/\/prohoster.info\/et\/blog\/nejroset-ot-nvidia-prevrashhaet-prostejshie-nabroski-v-krasivye-pejzazhi","title":{"rendered":"Nvidia tehisintellekt muudab lihtsad visandid kauniteks maastikeks.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

\"Nvidia
\nSuitsetaja juga ning terve inimese juga<\/p>\n

Kuidas me k\u00f5ik teame, et \u00f6\u00f6kulli joonistamine on lihtne. Esiteks joonistame ovaali, seej\u00e4rel ringi, ja l\u00f5puks \u2014 saame suurep\u00e4rase \u00f6\u00f6kulli. Loomulikult on see naljaga \u00f6eldud, ajades aegunud, ent Nvidia insenerid on p\u00fc\u00fcdnud muuta fantaasia reaalsuseks. <\/p>\n

Uus arendus<\/a><\/noindex>, mida nimetatakse GauGAN-iks, loob h\u00e4mmastavaid maastikke v\u00e4ga lihtsate jooniste p\u00f5hjal (t\u00f5eliselt lihtsad \u2014 ringid, jooned ja nii edasi). Loomulikult p\u00f5hinevad selle arenduse alused kaasaegsetel tehnoloogiatel \u2014 nimelt genereerivatel vastandv\u00f5rkudel.
\n<\/a><\/noindex>
\nGauGAN v\u00f5imaldab luua v\u00e4rvikaid virtuaalseid monde \u2014 mitte ainult meelelahutuseks, vaid ka t\u00f6\u00f6ks. Nii saavad arhitektid, maastikuarhitektid, m\u00e4ngude arendajad \u2014 k\u00f5ik nad v\u00f5ivad leida kasulikku teavet. Tehisintellekt m\u00f5istab viivitamatult, mida inimene soovib, ja t\u00e4iendab algseid ideid suure hulga detailidega. <\/p>\n

\u201eIdeede genereerimine disaini osas on GauGANi abil palju lihtsam, kuna nutikas pintsel suudab t\u00e4iendada algset joonist, lisades kvaliteetseid pilte,\u201c \u00fctles \u00fcks GauGANi arendajatest.<\/p>\n

Selle t\u00f6\u00f6riista kasutajad saavad muuta algset ideed, kohandades maastikku v\u00f5i muid pilte, lisades taevast, liiva, meri ja nii edasi. K\u00f5ike, mida hing igatseb, ja see lisamine toimub vaid m\u00f5ne sekundi jooksul.<\/p>\n

Neurov\u00f5rku koolitati miljoneid pilte kasutades. T\u00e4nu sellele suudab s\u00fcsteem m\u00f5ista, mida inimene soovib ja kuidas soovitud tulemuseni j\u00f5uda. Samuti ei unusta neurov\u00f5rk v\u00e4iksemaid detaile. Kui n\u00e4iteks joonistada karedalt tiik ja m\u00f5ni puu selle l\u00e4hedal, siis p\u00e4rast maastiku elavdamist kajastuvad k\u00f5ik l\u00e4heduses olevad objektid tiigi veepinnal.<\/p>\n

S\u00fcsteemile on v\u00f5imalik m\u00e4\u00e4rata, milline peaks olema n\u00e4htav pinnas \u2014 see v\u00f5ib olla kaetud rohu, lume, vee v\u00f5i liivaga. K\u00f5ike seda saab sekunditega muuta, nii et lumi muutub liivaks ja asemel lumisest t\u00fchermaast saab kunstnik k\u00f5rbemaastik. <\/p>\n

\u00abSee see see sees like a coloring book, which tells where to place the tree, where \u2014 the sun, and where \u2014 the sky. Then, after the initial task, the neural network brings the picture to life, adds necessary details and textures, and draws reflections. All this is based on real images,\u00bb says one of the developers. <\/p>\n

\r\n \"M\u00e4ngi\r\n
<\/div>\r\n <\/div><\/center>
\nDespite the system lacking a 'understanding' of the real world, it creates impressive landscapes. This is because it uses two neural networks, a generator and a discriminator. The generator creates an image and shows it to the discriminator. Based on millions of previously seen images, the discriminator chooses the most realistic options. <\/p>\n

That\u2019s why the generator 'knows' where reflections should be. It is worth noting that the tool is quite flexible and equipped with a large number of settings. Thus, it can create paintings, adjusting to the style of a specific artist or just to play with the quick addition of a sunrise or sunset. <\/p>\n

The developers claim that the system does not simply take images from somewhere, put them together and get a result. No, all the 'pictures' are generated. That is, the neural network 'creates' like a real artist (or even better).<\/p>\n

Currently, the program is not available for public access, but it will soon be possible to try it in action. This can be done at the GPU Technology Conference 2019, which is currently taking place in California. Lucky ones who managed to visit the exhibition can already test GauGAN.<\/p>\n

Neural networks have long been taught to take part in the creative process. For example, last year, some of them could create 3D models<\/a><\/noindex>. In addition, developers from DeepMind trained the neural network to restore three-dimensional spaces and objects from drawings, photographs, and sketches. To recreate a simple figure, the neural network needs just one picture; to create more complex objects, five pictures are required for 'training'.<\/p>\n

As for GauGAN, this tool will surely find worthy commercial application \u2014 many areas of business and science have a need for such services.<\/p>\n

Allikas: habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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(\u0434\u0435\u0439\u0441\u0442\u0432\u0438\u0442\u0435\u043b\u044c\u043d\u043e […]<\/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":[],"tags":[],"class_list":["post-29895","post","type-post","status-publish","format-standard","hentry"],"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\udd47Nvidia tehisintellekt muudab lihtsad visandid kauniteks maastikeks | ProHoster","description":"Smoker's waterfall 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