7 Commits

Author SHA1 Message Date
Xintao
a4abfb2979 Delete .github/workflows/no-response.yml 2024-04-03 00:39:11 +08:00
Xintao
5ca1078535 update readme 2022-09-20 19:59:08 +08:00
Xintao
fa4c8a03ae add github release workflow, v0.3.0 2022-09-20 19:47:38 +08:00
Xintao
37a7c5726d update readme, v0.2.9 2022-09-20 19:42:33 +08:00
Xintao
382d5be582 Merge branch 'master' of github.com:xinntao/Real-ESRGAN 2022-09-20 19:16:51 +08:00
Xintao
61e81d3108 update inference_video: support auto download 2022-09-20 19:15:25 +08:00
NayamAmarshe
8f5744bc51 Update README.md - Added Upscayl under GUI Apps list (#423) 2022-09-19 19:54:45 +08:00
6 changed files with 90 additions and 48 deletions

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@@ -1,33 +0,0 @@
name: No Response
# TODO: it seems not to work
# Modified from: https://raw.githubusercontent.com/github/docs/main/.github/workflows/no-response.yaml
# **What it does**: Closes issues that don't have enough information to be actionable.
# **Why we have it**: To remove the need for maintainers to remember to check back on issues periodically
# to see if contributors have responded.
# **Who does it impact**: Everyone that works on docs or docs-internal.
on:
issue_comment:
types: [created]
schedule:
# Schedule for five minutes after the hour every hour
- cron: '5 * * * *'
jobs:
noResponse:
runs-on: ubuntu-latest
steps:
- uses: lee-dohm/no-response@v0.5.0
with:
token: ${{ github.token }}
closeComment: >
This issue has been automatically closed because there has been no response
to our request for more information from the original author. With only the
information that is currently in the issue, we don't have enough information
to take action. Please reach out if you have or find the answers we need so
that we can investigate further.
If you still have questions, please improve your description and re-open it.
Thanks :-)

41
.github/workflows/release.yml vendored Normal file
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@@ -0,0 +1,41 @@
name: release
on:
push:
tags:
- '*'
jobs:
build:
permissions: write-all
name: Create Release
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v2
- name: Create Release
id: create_release
uses: actions/create-release@v1
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
with:
tag_name: ${{ github.ref }}
release_name: Real-ESRGAN ${{ github.ref }} Release Note
body: |
🚀 See you again 😸
🚀Have a nice day 😸 and happy everyday 😃
🚀 Long time no see ☄️
✨ **Highlights**
✅ [Features] Support ...
🐛 **Bug Fixes**
🌴 **Improvements**
📢📢📢
<p align="center">
<img src="https://raw.githubusercontent.com/xinntao/Real-ESRGAN/master/assets/realesrgan_logo.png" height=150>
</p>
draft: true
prerelease: false

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@@ -22,10 +22,10 @@
🔥 **RealESRGAN_x4plus_anime_6B** for anime images **(动漫插图模型)**. Please see [[*anime_model*](docs/anime_model.md)] 🔥 **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. You can try in our website: [ARC Demo](https://arc.tencent.com/en/ai-demos/imgRestore) (now only support RealESRGAN_x4plus_anime_6B) -->
1. :boom: **Add** online demo: [![Replicate](https://img.shields.io/static/v1?label=Demo&message=Replicate&color=blue)](https://replicate.com/xinntao/realesrgan). 1. :boom: **Update** online Replicate demo: [![Replicate](https://img.shields.io/static/v1?label=Demo&message=Replicate&color=blue)](https://replicate.com/xinntao/realesrgan)
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. Online Colab demo for Real-ESRGAN: [![Colab](https://img.shields.io/static/v1?label=Demo&message=Colab&color=orange)](https://colab.research.google.com/drive/1k2Zod6kSHEvraybHl50Lys0LerhyTMCo?usp=sharing) **|** Online Colab demo for for Real-ESRGAN (**anime videos**): [![Colab](https://img.shields.io/static/v1?label=Demo&message=Colab&color=orange)](https://colab.research.google.com/drive/1yNl9ORUxxlL4N0keJa2SEPB61imPQd1B?usp=sharing)
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. 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) <!-- 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> 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. We extend the powerful ESRGAN to a practical restoration application (namely, Real-ESRGAN), which is trained with pure synthetic data.
@@ -59,6 +59,7 @@ Other recommended projects:<br>
<!---------------------------------- Updates ---------------------------> <!---------------------------------- Updates --------------------------->
## 🚩 Updates ## 🚩 Updates
- ✅ Add the **realesr-general-x4v3** model - a tiny small model for general scenes. It also supports the **-dn** option to balance the noise (avoiding over-smooth results). **-dn** is short for denoising strength.
- ✅ 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. - ✅ 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). - ✅ Add small models for anime videos. More details are in [anime video models](docs/anime_video_model.md).
- ✅ Add the ncnn implementation [Real-ESRGAN-ncnn-vulkan](https://github.com/xinntao/Real-ESRGAN-ncnn-vulkan). - ✅ Add the ncnn implementation [Real-ESRGAN-ncnn-vulkan](https://github.com/xinntao/Real-ESRGAN-ncnn-vulkan).
@@ -259,6 +260,7 @@ If you develop/use Real-ESRGAN in your projects, welcome to let me know.
- [Real-ESRGAN_GUI](https://github.com/net2cn/Real-ESRGAN_GUI) by [net2cn](https://github.com/net2cn) - [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) - [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) - [anime_upscaler](https://github.com/shangar21/anime_upscaler) by [shangar21](https://github.com/shangar21)
- [Upscayl](https://github.com/upscayl/upscayl) by [Nayam Amarshe](https://github.com/NayamAmarshe) and [TGS963](https://github.com/TGS963)
## 🤗 Acknowledgement ## 🤗 Acknowledgement

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@@ -1 +1 @@
0.2.8 0.3.0

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@@ -14,6 +14,7 @@
| [RealESRGAN_x2plus](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth) | X2 | X2 model for general images | | [RealESRGAN_x2plus](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth) | X2 | X2 model for general images |
| [RealESRNet_x4plus](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.1/RealESRNet_x4plus.pth) | X4 | X4 model with MSE loss (over-smooth effects) | | [RealESRNet_x4plus](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.1/RealESRNet_x4plus.pth) | X4 | X4 model with MSE loss (over-smooth effects) |
| [official ESRGAN_x4](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.1/ESRGAN_SRx4_DF2KOST_official-ff704c30.pth) | X4 | official ESRGAN model | | [official ESRGAN_x4](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.1/ESRGAN_SRx4_DF2KOST_official-ff704c30.pth) | X4 | official ESRGAN model |
| [realesr-general-x4v3](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth) | X4 (can also be used for X1, X2, X3) | A tiny small model (consume much fewer GPU memory and time); not too strong deblur and denoise capacity |
The following models are **discriminators**, which are usually used for fine-tuning. The following models are **discriminators**, which are usually used for fine-tuning.

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@@ -8,6 +8,7 @@ import shutil
import subprocess import subprocess
import torch import torch
from basicsr.archs.rrdbnet_arch import RRDBNet from basicsr.archs.rrdbnet_arch import RRDBNet
from basicsr.utils.download_util import load_file_from_url
from os import path as osp from os import path as osp
from tqdm import tqdm from tqdm import tqdm
@@ -172,32 +173,55 @@ class Writer:
def inference_video(args, video_save_path, device=None, total_workers=1, worker_idx=0): def inference_video(args, video_save_path, device=None, total_workers=1, worker_idx=0):
# ---------------------- determine models according to model names ---------------------- # # ---------------------- determine models according to model names ---------------------- #
args.model_name = args.model_name.split('.pth')[0] args.model_name = args.model_name.split('.pth')[0]
if args.model_name in ['RealESRGAN_x4plus', 'RealESRNet_x4plus']: # x4 RRDBNet model if args.model_name == 'RealESRGAN_x4plus': # x4 RRDBNet model
model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4) model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
netscale = 4 netscale = 4
elif args.model_name in ['RealESRGAN_x4plus_anime_6B']: # x4 RRDBNet model with 6 blocks file_url = ['https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth']
elif args.model_name == 'RealESRNet_x4plus': # x4 RRDBNet model
model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
netscale = 4
file_url = ['https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.1/RealESRNet_x4plus.pth']
elif args.model_name == 'RealESRGAN_x4plus_anime_6B': # x4 RRDBNet model with 6 blocks
model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=6, num_grow_ch=32, scale=4) model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=6, num_grow_ch=32, scale=4)
netscale = 4 netscale = 4
elif args.model_name in ['RealESRGAN_x2plus']: # x2 RRDBNet model file_url = ['https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth']
elif args.model_name == 'RealESRGAN_x2plus': # x2 RRDBNet model
model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=2) model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=2)
netscale = 2 netscale = 2
elif args.model_name in ['realesr-animevideov3']: # x4 VGG-style model (XS size) file_url = ['https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth']
elif args.model_name == 'realesr-animevideov3': # x4 VGG-style model (XS size)
model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=16, upscale=4, act_type='prelu') model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=16, upscale=4, act_type='prelu')
netscale = 4 netscale = 4
else: file_url = ['https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-animevideov3.pth']
raise NotImplementedError elif args.model_name == 'realesr-general-x4v3': # x4 VGG-style model (S size)
model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
netscale = 4
file_url = [
'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-wdn-x4v3.pth',
'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth'
]
# ---------------------- determine model paths ---------------------- # # ---------------------- determine model paths ---------------------- #
model_path = os.path.join('experiments/pretrained_models', args.model_name + '.pth')
if not os.path.isfile(model_path):
model_path = os.path.join('weights', args.model_name + '.pth') model_path = os.path.join('weights', args.model_name + '.pth')
if not os.path.isfile(model_path): if not os.path.isfile(model_path):
raise ValueError(f'Model {args.model_name} does not exist.') ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
for url in file_url:
# model_path will be updated
model_path = load_file_from_url(
url=url, model_dir=os.path.join(ROOT_DIR, 'weights'), progress=True, file_name=None)
# use dni to control the denoise strength
dni_weight = None
if args.model_name == 'realesr-general-x4v3' and args.denoise_strength != 1:
wdn_model_path = model_path.replace('realesr-general-x4v3', 'realesr-general-wdn-x4v3')
model_path = [model_path, wdn_model_path]
dni_weight = [args.denoise_strength, 1 - args.denoise_strength]
# restorer # restorer
upsampler = RealESRGANer( upsampler = RealESRGANer(
scale=netscale, scale=netscale,
model_path=model_path, model_path=model_path,
dni_weight=dni_weight,
model=model, model=model,
tile=args.tile, tile=args.tile,
tile_pad=args.tile_pad, tile_pad=args.tile_pad,
@@ -312,9 +336,16 @@ def main():
type=str, type=str,
default='realesr-animevideov3', default='realesr-animevideov3',
help=('Model names: realesr-animevideov3 | RealESRGAN_x4plus_anime_6B | RealESRGAN_x4plus | RealESRNet_x4plus |' help=('Model names: realesr-animevideov3 | RealESRGAN_x4plus_anime_6B | RealESRGAN_x4plus | RealESRNet_x4plus |'
' RealESRGAN_x2plus | ' ' RealESRGAN_x2plus | realesr-general-x4v3'
'Default:realesr-animevideov3')) 'Default:realesr-animevideov3'))
parser.add_argument('-o', '--output', type=str, default='results', help='Output folder') parser.add_argument('-o', '--output', type=str, default='results', help='Output folder')
parser.add_argument(
'-dn',
'--denoise_strength',
type=float,
default=0.5,
help=('Denoise strength. 0 for weak denoise (keep noise), 1 for strong denoise ability. '
'Only used for the realesr-general-x4v3 model'))
parser.add_argument('-s', '--outscale', type=float, default=4, help='The final upsampling scale of the image') parser.add_argument('-s', '--outscale', type=float, default=4, help='The final upsampling scale of the image')
parser.add_argument('--suffix', type=str, default='out', help='Suffix of the restored video') parser.add_argument('--suffix', type=str, default='out', help='Suffix of the restored video')
parser.add_argument('-t', '--tile', type=int, default=0, help='Tile size, 0 for no tile during testing') parser.add_argument('-t', '--tile', type=int, default=0, help='Tile size, 0 for no tile during testing')