{"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\/es\/blog\/news\/poyavilas-utilita-dlya-udaleniya-dvizhushhihsya-obektov-s-video","title":{"rendered":"Ha aparecido una herramienta para eliminar objetos en movimiento de videos","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Hoy en d\u00eda, eliminar un elemento molesto de una foto ya no es un problema para muchos. Las habilidades b\u00e1sicas en Photoshop o las redes neuronales de moda pueden resolver el problema. Sin embargo, en el caso del video, la situaci\u00f3n se complica, ya que es necesario procesar al menos 24 fotogramas por segundo de video.<\/p>\n

\"Ha<\/p>\n

Y aqu\u00ed en Github se ha a\u00f1adido<\/a><\/noindex> una herramienta que automatiza estas acciones, permitiendo eliminar cualquier objeto en movimiento del video. Basta con marcar el objeto no deseado con el cursor, y el sistema har\u00e1 el resto. La herramienta se llama de manera sencilla \u2014 video-object-removal. Sin embargo, en su base reposan tecnolog\u00edas avanzadas.<\/p>\n

El sistema utiliza una red neuronal que procesa el video fotograma a fotograma, reemplazando el objeto o persona no deseada con el fondo. El programa puede cambiar hasta 55 fotogramas por segundo, reconstruyendo el fondo en funci\u00f3n de la imagen circundante. Aunque al examinarlo de cerca se hace evidente que el m\u00e9todo de eliminaci\u00f3n de objetos no es perfecto, los resultados son impresionantes.<\/p>\n

<\/center><\/p>\n

En algunos fotogramas se puede ver que en el lugar de la persona \u00abeliminada\u00bb queda una huella fantasma transparente o semitransparente. Esto se debe a que el sistema solo analiza el fondo disponible y, por el momento, no siempre puede recrearlo de manera adecuada. Esto depende de la complejidad del fondo \u2014 cuanto m\u00e1s simple y homog\u00e9neo sea, mejor ser\u00e1 el resultado final.<\/p>\n

Para las pruebas se utiliz\u00f3 el sistema operativo Ubuntu 16.04, Python 3.5, Pytorch 0.4.0, CUDA 8.0, y el procesamiento se realiz\u00f3 en una tarjeta gr\u00e1fica NVIDIA GeForce GTX 1080 Ti. Los propios c\u00f3digos fuente son abiertos y pueden ser utilizados por todos. Sin embargo, cabe destacar que esta tecnolog\u00eda tambi\u00e9n puede ser utilizada para fines malintencionados. Por ejemplo, para \u00abocultar\u00bb infracciones de tr\u00e1fico u otros delitos capturados por las c\u00e1maras.<\/p>\n

<\/p>\n

<\/center><\/p>\n

\t\t\t\t


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

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