{"id":36276,"date":"2019-10-31T22:10:37","date_gmt":"2019-10-31T19:10:37","guid":{"rendered":"https:\/\/prohoster.info\/blog\/poyavilas-utilita-dlya-udaleniya-dvizhushhihsya-obektov-s-video\/"},"modified":"2019-10-31T22:10:37","modified_gmt":"2019-10-31T19:10:37","slug":"poyavilas-utilita-dlya-udaleniya-dvizhushhihsya-obektov-s-video","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sv\/blog\/news\/poyavilas-utilita-dlya-udaleniya-dvizhushhihsya-obektov-s-video","title":{"rendered":"Det har kommit en verktyg f\u00f6r att ta bort r\u00f6rliga objekt fr\u00e5n video","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Idag \u00e4r det inte l\u00e4ngre ett problem f\u00f6r m\u00e5nga att ta bort st\u00f6rande objekt fr\u00e5n foton. Grundl\u00e4ggande kunskaper i Photoshop eller moderna neurala n\u00e4tverk kan l\u00f6sa problemet. Men n\u00e4r det g\u00e4ller video blir situationen mer komplicerad, eftersom minst 24 ramar m\u00e5ste bearbetas per sekund.<\/p>\n

\"Det<\/p>\n

Och p\u00e5 Github har det tillkommit<\/a><\/noindex> ett verktyg som automatiserar dessa \u00e5tg\u00e4rder och m\u00f6jligg\u00f6r borttagning av alla r\u00f6rliga objekt fr\u00e5n videor. Det \u00e4r tillr\u00e4ckligt att enkelt markera det \u00f6verfl\u00f6diga objektet med muspekaren, s\u00e5 g\u00f6r systemet allt annat. Verktyget heter enkelt video-object-removal. Men bakom det ligger avancerad teknologi.<\/p>\n

Systemet anv\u00e4nder ett neuralt n\u00e4tverk som bearbetar videon ram f\u00f6r ram, och ers\u00e4tter det o\u00f6nskade objektet eller personen med bakgrunden. Programmet kan f\u00f6r\u00e4ndra upp till 55 ramar per sekund och rekonstruera bakgrunden baserat p\u00e5 den omgivande bilden. \u00c4ven om det blir tydligt vid n\u00e4rmare granskning att metoden f\u00f6r att ta bort objekt inte \u00e4r perfekt, \u00e4r resultaten imponerande.<\/p>\n

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I vissa bilder syns det att p\u00e5 platsen f\u00f6r den «borttagna» personen l\u00e4mnas ett genomskinligt eller halvgenomskinligt sp\u00f6ksyn. Anledningen \u00e4r att systemet endast analyserar den tillg\u00e4ngliga bakgrunden och \u00e4n s\u00e5 l\u00e4nge inte alltid kan \u00e5terskapa den p\u00e5 ett adekvat s\u00e4tt. Detta beror p\u00e5 bakgrundens komplexitet — ju enklare och mer homogen den \u00e4r, desto b\u00e4ttre blir det slutgiltiga resultatet.<\/p>\n

F\u00f6r testningen anv\u00e4ndes operativsystemet Ubuntu 16.04, Python 3.5, Pytorch 0.4.0, CUDA 8.0, och bearbetning skedde p\u00e5 grafikkortet NVIDIA GeForce GTX 1080 Ti. K\u00e4llkoden \u00e4r \u00f6ppen och kan anv\u00e4ndas av alla. Vi p\u00e5pekar dock att s\u00e5dan teknik ocks\u00e5 kan anv\u00e4ndas i skadliga syften. Till exempel f\u00f6r att «d\u00f6lja» trafikf\u00f6rseelser eller andra brott som f\u00e5ngats av kameror.<\/p>\n

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K\u00e4lla: 3dnews.ru<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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