mirror of
https://github.com/k4yt3x/video2x.git
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229 lines
8.6 KiB
Markdown
229 lines
8.6 KiB
Markdown
# Video2X Lossless Video Enlarger
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### Official Discussion Group (Telegram): https://t.me/video2x
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## Prerequisites
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Component names that are **bolded** are mandatory.
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Component names that are *italicized* can be automatically downloaded and configured with the `video2x_setup.py` script.
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1. Operating System: Windows
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1. AMD GPU / Nvidia GPU
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1. AMD GPU driver / Nvidia GPU driver / Nvidia CUDNN
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1. [***FFMPEG***](https://ffmpeg.zeranoe.com/builds/)
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1. [***waifu2x-caffe***](https://github.com/lltcggie/waifu2x-caffe/releases) / [***waifu2x-converter-cpp***](https://github.com/DeadSix27/waifu2x-converter-cpp/releases)
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## Recent Changes
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### Setup Script 1.2.0 (March 26, 2019)
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- `video2x_setup.py` script can now automatically download and configure `waifu2x-converter-cpp`.
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- replaced old progress indicator with progress bar.
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### 2.6.3 (March 24, 2019)
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- Added image cleaner by @BrianPetkovsek which removes upscaled frames.
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- Fixed some PEP8 issues.
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- Exceptions in waifu2x are now caught, and script will now stop on waifu2x error instead of keep going on to FFMPEG.
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### 2.6.2 (March 19, 2019)
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- Removed `--model_dir` verification due to the rapidly evolving number of models added.
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- Fixed model specifying bug. Users should now specify model using `--model_dir [path to folder containing model JSON files]`.
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- Enhanced command execution method.
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### 2.6.1 (March 12, 2019)
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- Added `-b, --batch` option which selects applies all default values for questions automatically.
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- **This new version will now require `avalon_framework>=1.6.3`**. Please run `pip install -U avalon_framework` to update the existing framework.
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## Description
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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.
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For short: **Video2X enlarges your video without losing details**
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Watch for the sharper edges in this screenshot around the shadows:
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**You can also watch the YouTube video Demo: https://www.youtube.com/watch?v=PG94iPoeoZk**
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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.
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## Screenshot
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---
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## Documentations
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### [Video2X Wiki](https://github.com/K4YT3X/video2x/wiki)
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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.
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### [Step-By-Step Tutorial](https://github.com/K4YT3X/video2x/wiki/Step-By-Step-Tutorial) (Nvidia GPUs)
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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.
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### [Waifu2X Drivers](https://github.com/K4YT3X/video2x/wiki/Waifu2X-Drivers)
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Go to the [Waifu2X Drivers](https://github.com/K4YT3X/video2x/wiki/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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---
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## Quick Start
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### Prerequisites
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- **Python 3**
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Download: https://www.python.org/downloads/windows/
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- **FFMPEG Windows Build**
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Download: https://ffmpeg.org/download.html
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- **waifu2x-caffe** (for Nvidia CUDA/CUDNN)
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Download: https://github.com/lltcggie/waifu2x-caffe/releases
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- **waifu2x-converter-cpp** (required for AMD, OpenCL and OpenGL processing)
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Download: https://github.com/DeadSix27/waifu2x-converter-cpp/releases
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### Installing Dependencies
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First, clone the video2x repository.
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```shell
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git clone https://github.com/K4YT3X/video2x.git
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cd video2x/bin
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```
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Then you may run the `video2x_setup.py` script to install and configure the dependencies automatically. This script is designed and tested on Windows 10.
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This script will install the newest version of `ffmpeg`, either or both of `waifu2x-caffe` and `waifu2x-converter-cpp` to `%LOCALAPPDATA%\\video2x` and all required python libraries.
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```shell
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python video2x_setup.py
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```
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Alternatively, you can also install the dependencies manually. Please refer to the prerequisites section to see what's needed.
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Then you'll need to install python dependencies before start using video2x. Install simply by executing the following command.
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```shell
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pip install -r requirements.txt
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```
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**Note that all command line arguments/options overwrite configuration file settings.**
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### Sample Videos
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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.
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- [Sample Video Original (240P) 1.7MB](https://files.flexio.org/Resources/Videos/sample_input.mp4)
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- [Sample Video Upscaled (1080P) 4.8MB](https://files.flexio.org/Resources/Videos/sample_output.mp4)
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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.
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### Nvidia CUDA (waifu2x-caffe)
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Enlarge the video to 1920x1080 using CUDA. You may also use the `-r/--ratio` option.
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```shell
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python video2x.py -i sample_input.mp4 -o sample_output.mp4 -m gpu --width=1920 --height=1080
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```
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### Nvidia CNDNN
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Enlarge the video to 1920x1080 using CUDNN. You may also use the `-r/--ratio` option.
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```shell
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python video2x.py -i sample_input.mp4 -o sample_output.mp4 -m cudnn --width=1920 --height=1080
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```
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### AMD or Nvidia (waifu2x-converter-cpp OpenCL)
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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`.
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```shell
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python video2x.py -i sample_input.mp4 -o sample_output.mp4 -m gpu -r 2 -d waifu2x_converter
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```
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### CPU
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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.
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```shell
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python video2x.py -i sample_input.mp4 -o sample_output.mp4 -m cpu --width=1920 --height=1080
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```
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---
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# Full Usage
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## General Options
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### -h, --help
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show this help message and exit
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## File Options
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### -i INPUT, --input INPUT
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Source video file/directory (default: None)
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### -o OUTPUT, --output OUTPUT
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Output video file/directory (default: None)
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## Upscaling Options
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### -m {cpu,gpu,cudnn}, --method {cpu,gpu,cudnn}
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Upscaling method (default: gpu)
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### -d {waifu2x_caffe,waifu2x_converter}, --driver {waifu2x_caffe,waifu2x_converter}
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Waifu2x driver (default: waifu2x_caffe)
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### -y MODEL_DIR, --model_dir MODEL_DIR
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Folder containing model JSON files
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### -t THREADS, --threads THREADS
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Number of threads to use for upscaling (default: 5)
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### -c CONFIG, --config CONFIG
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Video2X config file location (default: video2x\bin\video2x.json)
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### -b, --batch
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Enable batch mode (select all default values to questions)
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## Scaling Options
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### --width WIDTH
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Output video width
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### --height HEIGHT
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Output video height
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### -r RATIO, --ratio RATIO
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Scaling ratio
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---
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## License
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Licensed under the GNU General Public License Version 3 (GNU GPL v3)
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https://www.gnu.org/licenses/gpl-3.0.txt
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(C) 2018-2019 K4YT3X
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## Credits
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This project relies on the following software and projects.
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- [FFMPEG]('https://www.ffmpeg.org/')
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- [waifu2x-caffe](https://github.com/lltcggie/waifu2x-caffe)
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- [waifu2x-converter-cpp](https://github.com/DeadSix27/waifu2x-converter-cpp)
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## Related Resources
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- [Dandere2x](https://github.com/CardinalPanda/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. |