lucasrufkahr/Real-ESRGAN
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Re-organize README (#338)

Browse Source 
* update README

* upate readme

* upate readme

* update

* update

* update

* update
This commit is contained in:
Xintao
2022-05-24 20:29:51 +08:00
committed by GitHub
parent 6b15fc6936
commit e2db576020
3 changed files with 148 additions and 155 deletions
Download Patch File Download Diff File Expand all files Collapse all files

298
README.md
View File

@@ -4,6 +4,10 @@
## <div align="center"><b><a href="README.md">English</a> | <a href="README_CN.md">简体中文</a></b></div>
<div align="center">
👀[**Demos**](#-demos-videos) **|** 🚩[**Updates**](#-updates) **|** ⚡[**Usage**](#-quick-inference) **|** 🏰[**Model Zoo**](docs/model_zoo.md) **|** 🔧[Install](#-dependencies-and-installation) **|** 💻[Train](docs/Training.md) **|** ❓[FAQ](docs/FAQ.md) **|** 🎨[Contribution](docs/CONTRIBUTING.md)
[![download](https://img.shields.io/github/downloads/xinntao/Real-ESRGAN/total.svg)](https://github.com/xinntao/Real-ESRGAN/releases)
[![PyPI](https://img.shields.io/pypi/v/realesrgan)](https://pypi.org/project/realesrgan/)
[![Open issue](https://img.shields.io/github/issues/xinntao/Real-ESRGAN)](https://github.com/xinntao/Real-ESRGAN/issues)
@@ -12,34 +16,47 @@
[![python lint](https://github.com/xinntao/Real-ESRGAN/actions/workflows/pylint.yml/badge.svg)](https://github.com/xinntao/Real-ESRGAN/blob/master/.github/workflows/pylint.yml)
[![Publish-pip](https://github.com/xinntao/Real-ESRGAN/actions/workflows/publish-pip.yml/badge.svg)](https://github.com/xinntao/Real-ESRGAN/blob/master/.github/workflows/publish-pip.yml)
:fire: Update the **RealESRGAN AnimeVideo-v3** model **更新动漫视频的小模型**. Please see [[anime video models](docs/anime_video_model.md)] and [[comparisons](docs/anime_comparisons.md)] for more details.
</div>
1. [Colab Demo](https://colab.research.google.com/drive/1k2Zod6kSHEvraybHl50Lys0LerhyTMCo?usp=sharing) for Real-ESRGAN | [Colab Demo](https://colab.research.google.com/drive/1yNl9ORUxxlL4N0keJa2SEPB61imPQd1B?usp=sharing) for Real-ESRGAN (**anime videos**).
2. Portable [Windows](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-windows.zip) / [Linux](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-ubuntu.zip) / [MacOS](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-macos.zip) **executable files for Intel/AMD/Nvidia GPU**. You can find more information [here](#Portable-executable-files). The ncnn implementation is in [Real-ESRGAN-ncnn-vulkan](https://github.com/xinntao/Real-ESRGAN-ncnn-vulkan).
🔥 **AnimeVideo-v3 model (动漫视频小模型)**. Please see [[*anime video models*](docs/anime_video_model.md)] and [[*comparisons*](docs/anime_comparisons.md)]<br>
🔥 **RealESRGAN_x4plus_anime_6B** for anime images **(动漫插图模型)**. Please see [[*anime_model*](docs/anime_model.md)]
1. You can try in our website: [ARC Demo](https://arc.tencent.com/en/ai-demos/imgRestore) (now only support RealESRGAN_x4plus_anime_6B)
1. [Colab Demo](https://colab.research.google.com/drive/1k2Zod6kSHEvraybHl50Lys0LerhyTMCo?usp=sharing) for Real-ESRGAN **|** [Colab Demo](https://colab.research.google.com/drive/1yNl9ORUxxlL4N0keJa2SEPB61imPQd1B?usp=sharing) for Real-ESRGAN (**anime videos**)
1. Portable [Windows](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-windows.zip) / [Linux](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-ubuntu.zip) / [MacOS](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-macos.zip) **executable files for Intel/AMD/Nvidia GPU**. You can find more information [here](#portable-executable-files-ncnn). The ncnn implementation is in [Real-ESRGAN-ncnn-vulkan](https://github.com/xinntao/Real-ESRGAN-ncnn-vulkan)
1. You can watch enhanced animations in [Tencent Video](https://v.qq.com/s/topic/v_child/render/fC4iyCAM.html). 欢迎观看[腾讯视频动漫修复](https://v.qq.com/s/topic/v_child/render/fC4iyCAM.html)
Real-ESRGAN aims at developing **Practical Algorithms for General Image/Video Restoration**.<br>
We extend the powerful ESRGAN to a practical restoration application (namely, Real-ESRGAN), which is trained with pure synthetic data.
:art: Real-ESRGAN needs your contributions. Any contributions are welcome, such as new features/models/typo fixes/suggestions/maintenance, *etc*. See [CONTRIBUTING.md](docs/CONTRIBUTING.md). All contributors are list [here](README.md#hugs-acknowledgement).
:question: Frequently Asked Questions can be found in [FAQ.md](docs/FAQ.md).
:milky_way: Thanks for your valuable feedbacks/suggestions. All the feedbacks are updated in [feedback.md](docs/feedback.md).
🌌 Thanks for your valuable feedbacks/suggestions. All the feedbacks are updated in [feedback.md](docs/feedback.md).
---
If Real-ESRGAN is helpful in your photos/projects, please help to :star: this repo or recommend it to your friends. Thanks:blush: <br>
If Real-ESRGAN is helpful, please help to ⭐ this repo or recommend it to your friends 😊 <br>
Other recommended projects:<br>
:arrow_forward: [GFPGAN](https://github.com/TencentARC/GFPGAN): A practical algorithm for real-world face restoration <br>
:arrow_forward: [BasicSR](https://github.com/xinntao/BasicSR): An open-source image and video restoration toolbox<br>
:arrow_forward: [facexlib](https://github.com/xinntao/facexlib): A collection that provides useful face-relation functions.<br>
:arrow_forward: [HandyView](https://github.com/xinntao/HandyView): A PyQt5-based image viewer that is handy for view and comparison. <br>
▶️ [GFPGAN](https://github.com/TencentARC/GFPGAN): A practical algorithm for real-world face restoration <br>
▶️ [BasicSR](https://github.com/xinntao/BasicSR): An open-source image and video restoration toolbox<br>
▶️ [facexlib](https://github.com/xinntao/facexlib): A collection that provides useful face-relation functions.<br>
▶️ [HandyView](https://github.com/xinntao/HandyView): A PyQt5-based image viewer that is handy for view and comparison <br>
▶️ [HandyFigure](https://github.com/xinntao/HandyFigure): Open source of paper figures <br>
---
### 📖 Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data
> [[Paper](https://arxiv.org/abs/2107.10833)] &emsp; [[YouTube Video](https://www.youtube.com/watch?v=fxHWoDSSvSc)] &emsp; [[B站讲解](https://www.bilibili.com/video/BV1H34y1m7sS/)] &emsp; [[Poster](https://xinntao.github.io/projects/RealESRGAN_src/RealESRGAN_poster.pdf)] &emsp; [[PPT slides](https://docs.google.com/presentation/d/1QtW6Iy8rm8rGLsJ0Ldti6kP-7Qyzy6XL/edit?usp=sharing&ouid=109799856763657548160&rtpof=true&sd=true)]<br>
> [Xintao Wang](https://xinntao.github.io/), Liangbin Xie, [Chao Dong](https://scholar.google.com.hk/citations?user=OSDCB0UAAAAJ), [Ying Shan](https://scholar.google.com/citations?user=4oXBp9UAAAAJ&hl=en) <br>
> [Tencent ARC Lab](https://arc.tencent.com/en/ai-demos/imgRestore); Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences
<p align="center">
<img src="assets/teaser.jpg">
</p>
---
<!---------------------------------- Updates --------------------------->
<details>
<summary>🚩<b>Updates</b></summary>
## 🚩 Updates
- ✅ Update the **RealESRGAN AnimeVideo-v3** model. Please see [anime video models](docs/anime_video_model.md) and [comparisons](docs/anime_comparisons.md) for more details.
- ✅ Add small models for anime videos. More details are in [anime video models](docs/anime_video_model.md).
@@ -52,119 +69,20 @@ Other recommended projects:<br>
- ✅ [The inference code](inference_realesrgan.py) supports: 1) **tile** options; 2) images with **alpha channel**; 3) **gray** images; 4) **16-bit** images.
- ✅ The training codes have been released. A detailed guide can be found in [Training.md](docs/Training.md).
</details>
<!---------------------------------- Projects that use Real-ESRGAN --------------------------->
<details>
<summary>🧩<b>Projects that use Real-ESRGAN</b></summary>
&nbsp;&nbsp;&nbsp;&nbsp;👋 If you develop/use Real-ESRGAN in your projects, welcome to let me know.
- NCNN-Android: [RealSR-NCNN-Android](https://github.com/tumuyan/RealSR-NCNN-Android) by [tumuyan](https://github.com/tumuyan)
- VapourSynth: [vs-realesrgan](https://github.com/HolyWu/vs-realesrgan) by [HolyWu](https://github.com/HolyWu)
- NCNN: [Real-ESRGAN-ncnn-vulkan](https://github.com/xinntao/Real-ESRGAN-ncnn-vulkan)
&nbsp;&nbsp;&nbsp;&nbsp;**GUI**
- [Waifu2x-Extension-GUI](https://github.com/AaronFeng753/Waifu2x-Extension-GUI) by [AaronFeng753](https://github.com/AaronFeng753)
- [Squirrel-RIFE](https://github.com/Justin62628/Squirrel-RIFE) by [Justin62628](https://github.com/Justin62628)
- [Real-GUI](https://github.com/scifx/Real-GUI) by [scifx](https://github.com/scifx)
- [Real-ESRGAN_GUI](https://github.com/net2cn/Real-ESRGAN_GUI) by [net2cn](https://github.com/net2cn)
- [Real-ESRGAN-EGUI](https://github.com/WGzeyu/Real-ESRGAN-EGUI) by [WGzeyu](https://github.com/WGzeyu)
- [anime_upscaler](https://github.com/shangar21/anime_upscaler) by [shangar21](https://github.com/shangar21)
- [RealESRGAN-GUI](https://github.com/Baiyuetribe/paper2gui/blob/main/Video%20Super%20Resolution/RealESRGAN-GUI.md) by [Baiyuetribe](https://github.com/Baiyuetribe)
</details>
---
<!---------------------------------- Demo videos --------------------------->
<details open>
<summary>👀<b>Demo videos</b></summary>
## 👀 Demos Videos
#### Bilibili
- [大闹天宫片段](https://www.bilibili.com/video/BV1ja41117zb)
- [Anime dance cut 动漫魔性舞蹈](https://www.bilibili.com/video/BV1wY4y1L7hT/)
- [海贼王片段](https://www.bilibili.com/video/BV1i3411L7Gy/)
</details>
#### YouTube
### :book: Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data
> [[Paper](https://arxiv.org/abs/2107.10833)] &emsp; [Project Page] &emsp; [[YouTube Video](https://www.youtube.com/watch?v=fxHWoDSSvSc)] &emsp; [[B站讲解](https://www.bilibili.com/video/BV1H34y1m7sS/)] &emsp; [[Poster](https://xinntao.github.io/projects/RealESRGAN_src/RealESRGAN_poster.pdf)] &emsp; [[PPT slides](https://docs.google.com/presentation/d/1QtW6Iy8rm8rGLsJ0Ldti6kP-7Qyzy6XL/edit?usp=sharing&ouid=109799856763657548160&rtpof=true&sd=true)]<br>
> [Xintao Wang](https://xinntao.github.io/), Liangbin Xie, [Chao Dong](https://scholar.google.com.hk/citations?user=OSDCB0UAAAAJ), [Ying Shan](https://scholar.google.com/citations?user=4oXBp9UAAAAJ&hl=en) <br>
> Tencent ARC Lab; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences
<p align="center">
<img src="assets/teaser.jpg">
</p>
---
We have provided a pretrained model (*RealESRGAN_x4plus.pth*) with upsampling X4.<br>
**Note that RealESRGAN may still fail in some cases as the real-world degradations are really too complex.**<br>
Moreover, it **may not** perform well on **human faces, text**, *etc*, which will be optimized later.
<br>
Real-ESRGAN will be a long-term supported project (in my current plan :smiley:). It will be continuously updated
in my spare time.
Here is a TODO list in the near future:
- [ ] optimize for human faces
- [ ] optimize for texts
- [x] optimize for anime images
- [ ] support more scales
- [ ] support controllable restoration strength
If you have any good ideas or demands, please open an issue/discussion to let me know. <br>
If you have some images that Real-ESRGAN could not well restored, please also open an issue/discussion. I will record it (but I cannot guarantee to resolve it:stuck_out_tongue:). If necessary, I will open a page to specially record these real-world cases that need to be solved, but the current technology is difficult to handle well.
---
### Portable executable files
You can download [Windows](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-windows.zip) / [Linux](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-ubuntu.zip) / [MacOS](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-macos.zip) **executable files for Intel/AMD/Nvidia GPU**.
This executable file is **portable** and includes all the binaries and models required. No CUDA or PyTorch environment is needed.<br>
You can simply run the following command (the Windows example, more information is in the README.md of each executable files):
```bash
./realesrgan-ncnn-vulkan.exe -i input.jpg -o output.png -n model_name
```
We have provided five models:
1. realesrgan-x4plus (default)
2. realesrnet-x4plus
3. realesrgan-x4plus-anime (optimized for anime images, small model size)
4. realesr-animevideov3 (animation video)
You can use the `-n` argument for other models, for example, `./realesrgan-ncnn-vulkan.exe -i input.jpg -o output.png -n realesrnet-x4plus`
### Usage of executable files
1. Please refer to [Real-ESRGAN-ncnn-vulkan](https://github.com/xinntao/Real-ESRGAN-ncnn-vulkan#computer-usages) for more details.
1. Note that it does not support all the functions (such as `outscale`) as the python script `inference_realesrgan.py`.
```console
Usage: realesrgan-ncnn-vulkan.exe -i infile -o outfile [options]...
-h show this help
-i input-path input image path (jpg/png/webp) or directory
-o output-path output image path (jpg/png/webp) or directory
-s scale upscale ratio (can be 2, 3, 4. default=4)
-t tile-size tile size (>=32/0=auto, default=0) can be 0,0,0 for multi-gpu
-m model-path folder path to the pre-trained models. default=models
-n model-name model name (default=realesr-animevideov3, can be realesr-animevideov3 | realesrgan-x4plus | realesrgan-x4plus-anime | realesrnet-x4plus)
-g gpu-id gpu device to use (default=auto) can be 0,1,2 for multi-gpu
-j load:proc:save thread count for load/proc/save (default=1:2:2) can be 1:2,2,2:2 for multi-gpu
-x enable tta mode"
-f format output image format (jpg/png/webp, default=ext/png)
-v verbose output
```
Note that it may introduce block inconsistency (and also generate slightly different results from the PyTorch implementation), because this executable file first crops the input image into several tiles, and then processes them separately, finally stitches together.
---
## :wrench: Dependencies and Installation
## 🔧 Dependencies and Installation
- Python >= 3.7 (Recommend to use [Anaconda](https://www.anaconda.com/download/#linux) or [Miniconda](https://docs.conda.io/en/latest/miniconda.html))
- [PyTorch >= 1.7](https://pytorch.org/)
@@ -191,43 +109,69 @@ Note that it may introduce block inconsistency (and also generate slightly diffe
python setup.py develop
```
## :zap: Quick Inference
---
### Inference general images
## ⚡ Quick Inference
Download pre-trained models: [RealESRGAN_x4plus.pth](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth)
There are usually three ways to inference Real-ESRGAN.
1. [Online inference](#online-inference)
1. [Portable executable files (NCNN)](#portable-executable-files-ncnn)
1. [Python script](#python-script)
### Online inference
1. You can try in our website: [ARC Demo](https://arc.tencent.com/en/ai-demos/imgRestore) (now only support RealESRGAN_x4plus_anime_6B)
1. [Colab Demo](https://colab.research.google.com/drive/1k2Zod6kSHEvraybHl50Lys0LerhyTMCo?usp=sharing) for Real-ESRGAN **|** [Colab Demo](https://colab.research.google.com/drive/1yNl9ORUxxlL4N0keJa2SEPB61imPQd1B?usp=sharing) for Real-ESRGAN (**anime videos**).
### Portable executable files (NCNN)
You can download [Windows](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-windows.zip) / [Linux](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-ubuntu.zip) / [MacOS](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-macos.zip) **executable files for Intel/AMD/Nvidia GPU**.
This executable file is **portable** and includes all the binaries and models required. No CUDA or PyTorch environment is needed.<br>
You can simply run the following command (the Windows example, more information is in the README.md of each executable files):
```bash
wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth -P experiments/pretrained_models
./realesrgan-ncnn-vulkan.exe -i input.jpg -o output.png -n model_name
```
Inference!
We have provided five models:
```bash
python inference_realesrgan.py -n RealESRGAN_x4plus -i inputs --face_enhance
1. realesrgan-x4plus (default)
2. realesrnet-x4plus
3. realesrgan-x4plus-anime (optimized for anime images, small model size)
4. realesr-animevideov3 (animation video)
You can use the `-n` argument for other models, for example, `./realesrgan-ncnn-vulkan.exe -i input.jpg -o output.png -n realesrnet-x4plus`
#### Usage of portable executable files
1. Please refer to [Real-ESRGAN-ncnn-vulkan](https://github.com/xinntao/Real-ESRGAN-ncnn-vulkan#computer-usages) for more details.
1. Note that it does not support all the functions (such as `outscale`) as the python script `inference_realesrgan.py`.
```console
Usage: realesrgan-ncnn-vulkan.exe -i infile -o outfile [options]...
-h show this help
-i input-path input image path (jpg/png/webp) or directory
-o output-path output image path (jpg/png/webp) or directory
-s scale upscale ratio (can be 2, 3, 4. default=4)
-t tile-size tile size (>=32/0=auto, default=0) can be 0,0,0 for multi-gpu
-m model-path folder path to the pre-trained models. default=models
-n model-name model name (default=realesr-animevideov3, can be realesr-animevideov3 | realesrgan-x4plus | realesrgan-x4plus-anime | realesrnet-x4plus)
-g gpu-id gpu device to use (default=auto) can be 0,1,2 for multi-gpu
-j load:proc:save thread count for load/proc/save (default=1:2:2) can be 1:2,2,2:2 for multi-gpu
-x enable tta mode"
-f format output image format (jpg/png/webp, default=ext/png)
-v verbose output
```
Results are in the `results` folder
Note that it may introduce block inconsistency (and also generate slightly different results from the PyTorch implementation), because this executable file first crops the input image into several tiles, and then processes them separately, finally stitches together.
### Inference anime images
### Python script
<p align="center">
<img src="https://raw.githubusercontent.com/xinntao/public-figures/master/Real-ESRGAN/cmp_realesrgan_anime_1.png">
</p>
Pre-trained models: [RealESRGAN_x4plus_anime_6B](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth)<br>
More details and comparisons with [waifu2x](https://github.com/nihui/waifu2x-ncnn-vulkan) are in [**anime_model.md**](docs/anime_model.md)
```bash
# download model
wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth -P experiments/pretrained_models
# inference
python inference_realesrgan.py -n RealESRGAN_x4plus_anime_6B -i inputs
```
Results are in the `results` folder
### Usage of python script
#### Usage of python script
1. You can use X4 model for **arbitrary output size** with the argument `outscale`. The program will further perform cheap resize operation after the Real-ESRGAN output.
@@ -248,13 +192,41 @@ A common command: python inference_realesrgan.py -n RealESRGAN_x4plus -i infile
--ext Image extension. Options: auto | jpg | png, auto means using the same extension as inputs. Default: auto
```
## :european_castle: Model Zoo
#### Inference general images
Please see [docs/model_zoo.md](docs/model_zoo.md)
Download pre-trained models: [RealESRGAN_x4plus.pth](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth)
## :computer: Training and Finetuning on your own dataset
```bash
wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth -P experiments/pretrained_models
```
A detailed guide can be found in [Training.md](docs/Training.md).
Inference!
```bash
python inference_realesrgan.py -n RealESRGAN_x4plus -i inputs --face_enhance
```
Results are in the `results` folder
#### Inference anime images
<p align="center">
<img src="https://raw.githubusercontent.com/xinntao/public-figures/master/Real-ESRGAN/cmp_realesrgan_anime_1.png">
</p>
Pre-trained models: [RealESRGAN_x4plus_anime_6B](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth)<br>
More details and comparisons with [waifu2x](https://github.com/nihui/waifu2x-ncnn-vulkan) are in [**anime_model.md**](docs/anime_model.md)
```bash
# download model
wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth -P experiments/pretrained_models
# inference
python inference_realesrgan.py -n RealESRGAN_x4plus_anime_6B -i inputs
```
Results are in the `results` folder
---
## BibTeX
@@ -265,11 +237,29 @@ A detailed guide can be found in [Training.md](docs/Training.md).
date = {2021}
}
## :e-mail: Contact
## 📧 Contact
If you have any question, please email `xintao.wang@outlook.com` or `xintaowang@tencent.com`.
## :hugs: Acknowledgement
<!---------------------------------- Projects that use Real-ESRGAN --------------------------->
## 🧩 Projects that use Real-ESRGAN
If you develop/use Real-ESRGAN in your projects, welcome to let me know.
- NCNN-Android: [RealSR-NCNN-Android](https://github.com/tumuyan/RealSR-NCNN-Android) by [tumuyan](https://github.com/tumuyan)
- VapourSynth: [vs-realesrgan](https://github.com/HolyWu/vs-realesrgan) by [HolyWu](https://github.com/HolyWu)
- NCNN: [Real-ESRGAN-ncnn-vulkan](https://github.com/xinntao/Real-ESRGAN-ncnn-vulkan)
&nbsp;&nbsp;&nbsp;&nbsp;**GUI**
- [Waifu2x-Extension-GUI](https://github.com/AaronFeng753/Waifu2x-Extension-GUI) by [AaronFeng753](https://github.com/AaronFeng753)
- [Squirrel-RIFE](https://github.com/Justin62628/Squirrel-RIFE) by [Justin62628](https://github.com/Justin62628)
- [Real-GUI](https://github.com/scifx/Real-GUI) by [scifx](https://github.com/scifx)
- [Real-ESRGAN_GUI](https://github.com/net2cn/Real-ESRGAN_GUI) by [net2cn](https://github.com/net2cn)
- [Real-ESRGAN-EGUI](https://github.com/WGzeyu/Real-ESRGAN-EGUI) by [WGzeyu](https://github.com/WGzeyu)
- [anime_upscaler](https://github.com/shangar21/anime_upscaler) by [shangar21](https://github.com/shangar21)
## 🤗 Acknowledgement
Thanks for all the contributors.

2
docs/CONTRIBUTING.md
View File

@@ -1,5 +1,7 @@
# Contributing to Real-ESRGAN
:art: Real-ESRGAN needs your contributions. Any contributions are welcome, such as new features/models/typo fixes/suggestions/maintenance, *etc*. See [CONTRIBUTING.md](docs/CONTRIBUTING.md). All contributors are list [here](README.md#hugs-acknowledgement).
We like open-source and want to develop practical algorithms for general image restoration. However, individual strength is limited. So, any kinds of contributions are welcome, such as:
- New features

3
docs/anime_video_model.md
View File

@@ -1,7 +1,7 @@
# Anime Video Models
:white_check_mark: We add small models that are optimized for anime videos :-)<br>
More comparisons can be found in [anime_comparisons.md](docs/anime_comparisons.md)
More comparisons can be found in [anime_comparisons.md](anime_comparisons.md)
- [How to Use](#how-to-use)
- [PyTorch Inference](#pytorch-inference)
@@ -42,6 +42,7 @@ CUDA_VISIBLE_DEVICES=0 python inference_realesrgan_video.py -i inputs/video/onep
# multi gpu and multi process inference
CUDA_VISIBLE_DEVICES=0,1,2,3 python inference_realesrgan_video.py -i inputs/video/onepiece_demo.mp4 -n realesr-animevideov3 -s 2 --suffix outx2 --num_process_per_gpu 2
```
```console
Usage:
--num_process_per_gpu The total number of process is num_gpu * num_process_per_gpu. The bottleneck of