{"repo":"sniklaus/3d-ken-burns","free":true,"listed":false,"github":"https://github.com/sniklaus/3d-ken-burns","clone":"git clone https://github.com/sniklaus/3d-ken-burns.git","description":"an implementation of 3D Ken Burns Effect from a Single Image using PyTorch","language":"Python","stars":1569,"topics":["pytorch","python","cuda","deep-learning","cupy"],"license":null,"category":"machine-learning","readme_excerpt":"3d-ken-burns This is a reference implementation of 3D Ken Burns Effect from a Single Image [1] using PyTorch. Given a single input image, it animates this still image with a virtual camera scan and zoom subject to motion parallax. Should you be making use of our work, please cite our paper [1]. For some interesting related work, please see: https://github.com/pierlj/ken-burns-effect For some interesting discussions, please see: https://news.ycombinator.com/item?id=20978055 setup Several functions are implemented in CUDA using CuPy, which is why CuPy is a required dependency. It can be installed using pip install cupy or alternatively using one of the provided binary packages as outlined in the CuPy repository. Please also make sure to have the CUDA HOME environment variable configured. In order to generate the video results, please also make sure to have pip install moviepy installed. usage To run it on an image and generate the 3D Ken Burns effect fully automatically, use the following command. To start the interface that allows you to manually adjust the camera path, use the following command. You can then navigate to http://localhost:8080/ and load an image using the button on the bottom right corner. Please be patient when loading an image and saving the result, there is a bit of background processing going on. To run the depth estimation to obtain the raw depth estimate, use the following command. Please note that this script does not perform the depth adjustment, see #2","default_branch":null,"files":null,"tree":[],"storefront":"/r/sniklaus","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/sniklaus/3d-ken-burns/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}