Video2X Lossless Video Enlarger

Official Discussion Group (Telegram): https://t.me/video2x

Prerequisites

Component names that are bolded are mandatory.

Component names that are italicized can be automatically downloaded and configured with the video2x_setup.py script.

1. Operating System: Windows
2. AMD GPU / Nvidia GPU
3. AMD GPU driver / Nvidia GPU driver / Nvidia CUDNN
4. FFMPEG
5. waifu2x-caffe / waifu2x-converter-cpp

Recent Changes

2.6.2 (March 19, 2019)

• Removed --model_dir verification due to the rapidly evolving number of models added.
• Fixed model specifying bug. Users should now specify model using --model_dir [path to folder containing model JSON files].
• Enhanced command execution method.

2.6.1 (March 12, 2019)

• Added -b, --batch option which selects applies all default values for questions automatically.
• This new version will now require avalon_framework>=1.6.3. Please run pip install -U avalon_framework to update the existing framework.

2.6.0 (March 9, 2019)

• Complete redesign of configuration file format. The configuration file is now much more flexible and easy to look at.
• Various modifications done to the rest of the program to adapt to the changes made in the configuration file. This eliminated some problems existed in the previous version.

Description

Video2X is an automation software based on waifu2x image enlarging engine. It extracts frames from a video, enlarge it by a number of times without losing any details or quality, keeping lines smooth and edges sharp.

For short: Video2X enlarges your video without losing details

Watch for the sharper edges in this screenshot around the shadows:

You can also watch the YouTube video Demo: https://www.youtube.com/watch?v=PG94iPoeoZk

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.

Screenshot

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Documentations

Video2X Wiki

You can find all detailed user-facing and developer-facing documentations in the 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.

Step-By-Step Tutorial (Nvidia GPUs)

For those who want a detailed walk-through of how to use Video2X, you can head to the Step-By-Step Tutorial wiki page. It includes almost every step you need to perform in order to enlarge your first video. This tutorial currently only includes instructions for Nvidia GPUs, since AMD GPUs (OpenCL) requires installation of waifu2x-converter-cpp which cannot be installed automatically with Python at the moment due to its 7z compression format.

Waifu2X Drivers

Go to the Waifu2X Drivers wiki page if you want to see a detailed description on the different types of waifu2x 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.

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Quick Start

Prerequisites

• Python 3
  Download: https://www.python.org/downloads/windows/
• FFMPEG Windows Build
  Download: https://ffmpeg.org/download.html
• waifu2x-caffe (for Nvidia CUDA/CUDNN)
  Download: https://github.com/lltcggie/waifu2x-caffe/releases
• waifu2x-converter-cpp (required for AMD, OpenCL and OpenGL processing)
  Download: https://github.com/DeadSix27/waifu2x-converter-cpp/releases

Installing Dependencies

First, clone the video2x repository.

$ git clone https://github.com/K4YT3X/video2x.git
$ cd video2x/bin

Then you may run the video2x_setup.py script to install and configure the depencies automatically. This script is designed and tested on Windows 10.

This script will install ffmpeg, waifu2x-caffe to %LOCALAPPDATA%\\video2x and all python libraries.

waifu2x-converter-cpp cannot be installed automatically with this script. Please follow the waifu2x-converter-cpp installation instructions to install it.

$ python video2x_setup.py

Alternatively, you can also install the dependencies manually. Please refer to the prerequisites section to see what's needed.

Then you'll need to install python dependencies before start using video2x. Install simply by executing the following command.

$ pip install -r requirements.txt

Note that all command line arguments/options overwrite configuration file settings.

Sample Videos

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.

• Sample Video Original (240P) 1.7MB
• Sample Video Upscaled (1080P) 4.8MB

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.

Nvidia CUDA (waifu2x-caffe)

Enlarge the video to 1920x1080 using CUDA. You may also use the -r/--ratio option.

$ python video2x.py -i sample_input.mp4 -o sample_output.mp4 -m gpu --width=1920 --height=1080

Nvidia CNDNN

Enlarge the video to 1920x1080 using CUDNN. You may also use the -r/--ratio option.

$ python video2x.py -i sample_input.mp4 -o sample_output.mp4 -m cudnn --width=1920 --height=1080

AMD or Nvidia (waifu2x-converter-cpp OpenCL)

Enlarge the video by 2 times using OpenCL. Note that waifu2x-converter-cpp doesn't support width and height. You'll also have to explicitly specify that the driver to be used is waifu2x_converter.

$ python video2x.py -i sample_input.mp4 -o sample_output.mp4 -m gpu -r 2 -d waifu2x_converter

Corresponding sample configuration is shown below. Note that the waifu2x_path is different from the configuration for waifu2x-caffe. Instead of the binary path, folder containing extracted waifu2x-converter-cpp.exe should be specified.

CPU

Enlarge the video to 1920x1080 using the CPU. You may also use the -r/--ratio option. This is potentially much slower than using a GPU. The configuration file for this method is similar to the previous methods.

$ python video2x.py -i sample_input.mp4 -o sample_output.mp4 -m cpu --width=1920 --height=1080

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Full Usage

General Options

-h, --help

show this help message and exit

File Options

-i INPUT, --input INPUT

Source video file/directory (default: None)

-o OUTPUT, --output OUTPUT

Output video file/directory (default: None)

Upscaling Options

-m {cpu,gpu,cudnn}, --method {cpu,gpu,cudnn}

Upscaling method (default: gpu)

-d {waifu2x_caffe,waifu2x_converter}, --driver {waifu2x_caffe,waifu2x_converter}

Waifu2x driver (default: waifu2x_caffe)

-y MODEL_DIR, --model_dir MODEL_DIR

Folder containing model JSON files (default: None)

-t THREADS, --threads THREADS

Number of threads to use for upscaling (default: 5)

-c CONFIG, --config CONFIG

Video2X config file location (default: video2x\bin\video2x.json)

-b, --batch

Enable batch mode (select all default values to questions) (default: False)

Scaling Options

--width WIDTH

Output video width (default: False)

--height HEIGHT

Output video height (default: False)

-r RATIO, --ratio RATIO

Scaling ratio (default: False)

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License

Licensed under the GNU General Public License Version 3 (GNU GPL v3) https://www.gnu.org/licenses/gpl-3.0.txt

(C) 2018-2019 K4YT3X

Credits

This project relies on the following software and projects.

• FFMPEG
• waifu2x-caffe
• waifu2x-converter-cpp

Related Resources

• Dandere2x: Dandere2x is a lossy video upscaler also built around waifu2x, but with video compression techniques to shorten the time needed to process a video.