- **`Full`**: full package comes pre-configured with **all** dependencies like `FFmpeg` and `waifu2x-caffe`.
- **`Light`**: ligt package comes with only Video2X binaries and a template configuration file. The user will either have to run the setup script or install and configure dependencies themselves.
In case you're unable to download the releases directly from GitHub, you can try downloading from the mirror site hosted by the author. Only releases will be updated in this directory, not nightly builds.
Nightly builds are built automatically every time a new commit is pushed to the master branch. The lates nightly build is always up-to-date with the latest version of the code, but is less stable and may contain bugs. Nightly builds are handled by GitHub's integrated CI/CD tool, GitHub Actions.
To download the latest nightly build, go to the [GitHub Actions](https://github.com/k4yt3x/video2x/actions) tab, enter the last run of workflow "Video2X Nightly Build, and download the artifacts generated from the run.
Video2X Docker images are available on Docker Hub for easy and rapid Video2X deployment on Linux and macOS. If you already have Docker installed, then only one command is needed to start upscaling a video. For more information on how to use Video2X's Docker image, please refer to the [documentations](https://github.com/K4YT3X/video2x/wiki/Docker).
You can use Video2X on [Google Colab](https://colab.research.google.com/) for free. Colab allows you too use a GPU on Google's Servers (Tesla K80, T4, P4, P100). Please bare in mind that Colab can only be provided for free if all users know that they shouldn't abuse it. A single free-tier tier session can last up to 12 hours. Please do not abuse the platform by creating sessions back-to-back and running upscaling 24/7. This might result in you getting banned.
Here is an exmaple Notebook written by [@Felixkruemel](https://github.com/Felixkruemel): [Video2X_on_Colab.ipynb](https://colab.research.google.com/drive/1xqeZvoJXaBBPP6UyVwErnhwrnth0br0u). This file can be used in combination of the following modified configuration file: [@Felixkruemel's Video2X configuration for Google Colab](https://gist.githubusercontent.com/Felixkruemel/71e62de4bb38965ead2e0f4bae7ef4ee/raw/video2x.yaml).
Video2X is a video/GIF/image upscaling software based on Waifu2X, Anime4K, SRMD and RealSR written in Python 3. It upscales videos, GIFs and images, restoring details from low-resolution inputs. Video2X also accepts GIF input to video output and video input to GIF output.
Clip is from trailer of animated movie "千と千尋の神隠し". Copyright belongs to "株式会社スタジオジブリ (STUDIO GHIBLI INC.)". Will delete immediately if use of clip is in violation of copyright.
This original input GIF is 160x120 in size. This image is downsized and accelerated to 20 FPS from its [original image](https://gfycat.com/craftyeasygoingankole-capoo-bug-cat).
[Original image](https://72915.tumblr.com/post/173793265673) from [nananicu@twitter](https://twitter.com/nananicu/status/994546266968281088), edited by K4YT3X.
If you can't find a video clip to begin with, or if you want to see a before-after comparison, we have prepared some sample clips for you. The quick start guide down below will also be based on the name of the sample clips.
Clip is from anime "さくら荘のペットな彼女". Copyright belongs to "株式会社アニプレックス (Aniplex Inc.)". Will delete immediately if use of clip is in violation of copyright.
Tweak the settings if you want to, then hit the start button at the bottom and the upscale will start. Now you'll just have to wait for it to complete.
If you would like to tweak engine-specific settings, either specify the corresponding argument after `--`, or edit the corresponding field in the configuration file `video2x.yaml`. **Command line arguments will overwrite default values in the config file.**
This example below adds enables TTA for `waifu2x-caffe`.
To see a help page for driver-specific settings, use `-d` to select the driver and append `-- --help` as demonstrated below. This will print all driver-specific settings and descriptions.
Video2X can be deployed via Docker. The following command upscales the video `sample_input.mp4` two times with Waifu2X NCNN Vulkan and outputs the upscaled video to `sample_output.mp4`. For more details on Video2X Docker image usages, please refer to the [documentations](https://github.com/K4YT3X/video2x/wiki/Docker).
You can find all detailed user-facing and developer-facing documentations in the [Video2X Wiki](https://github.com/k4yt3x/video2x/wiki). It covers everything from step-by-step instructions for beginners, to the code structure of this program for advanced users and developers. If this README page doesn't answer all your questions, the wiki page is where you should head to.
For those who want a detailed walk-through of how to use Video2X, you can head to the [Step-By-Step Tutorial](https://github.com/k4yt3x/video2x/wiki/Step-By-Step-Tutorial) wiki page. It includes almost every step you need to perform in order to enlarge your first video.
Go to the [Drivers](https://github.com/k4yt3x/video2x/wiki/Drivers) wiki page if you want to see a detailed description on the different types of drivers implemented by Video2X. This wiki page contains detailed difference between different drivers, and how to download and set each of them up for Video2X.
If you have any questions, first try visiting our [Q&A](https://github.com/k4yt3x/video2x/wiki/Q&A) page to see if your question is answered there. If not, open an issue and we will respond to your questions ASAP. Alternatively, you can also join our [Telegram discussion group](https://t.me/video2x) and ask your questions there.
Are you interested in how the idea of Video2X was born? Do you want to know the stories and histories behind Video2X's development? Come into this page.
- [Dandere2x](https://github.com/CardinalPanda/dandere2x): A lossy video upscaler also built around `waifu2x`, but with video compression techniques to shorten the time needed to process a video.
- [Waifu2x-Extension-GUI](https://github.com/AaronFeng753/Waifu2x-Extension-GUI): A similar project that focuses more and only on building a better graphical user interface. It is built using C++ and Qt5, and currently only supports the Windows platform.
