Real-ESRGAN

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👀Demos | 🚩Updates | ⚡Usage | 🏰Model Zoo | 🔧Install  | 💻Train | ❓FAQ | 🎨Contribution

🔥 AnimeVideo-v3 model (动漫视频小模型). Please see [*anime video models*] and [*comparisons*]
🔥 RealESRGAN_x4plus_anime_6B for anime images (动漫插图模型). Please see [*anime_model*]

1. :boom: Update online Replicate demo: 
1. Online Colab demo for Real-ESRGAN:  | Online Colab demo for for Real-ESRGAN (anime videos): 
1. Portable Windows / Linux / MacOS executable files for Intel/AMD/Nvidia GPU. You can find more information here. The ncnn implementation is in Real-ESRGAN-ncnn-vulkan

Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
We extend the powerful ESRGAN to a practical restoration application (namely, Real-ESRGAN), which is trained with pure synthetic data.

🌌 Thanks for your valuable feedbacks/suggestions. All the feedbacks are updated in feedback.md.

If Real-ESRGAN is helpful, please help to ⭐ this repo or recommend it to your friends 😊 
Other recommended projects:
▶️ GFPGAN: A practical algorithm for real-world face restoration 
▶️ BasicSR: An open-source image and video restoration toolbox
▶️ facexlib: A collection that provides useful face-relation functions.
▶️ HandyView: A PyQt5-based image viewer that is handy for view and comparison 
▶️ HandyFigure: Open source of paper figures 

📖 Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data

> [Paper]   [YouTube Video]   [B站讲解]   [Poster]   [PPT slides]
> Xintao Wang, Liangbin Xie, Chao Dong, Ying Shan 
> Tencent ARC Lab; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences

🚩 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 and comparisons for more details.
- ✅ Add small models for anime videos. More details are in anime video models.
- ✅ Add the ncnn implementation Real-ESRGAN-ncnn-vulkan.
- ✅ Add *RealESRGAN_x4plus_anime_6B.pth*, which is optimized for anime images with much smaller model size. More details and comparisons with waifu2x are in anime_model.md
- ✅ Support finetuning on your own data or paired data (*i.e.*, finetuning ESRGAN). See here
- ✅ Integrate GFPGAN to support face enhancement.
- ✅ Integrated to Huggingface Spaces with Gradio. See Gradio Web Demo. Thanks @AK391
- ✅ Support arbitrary scale with --outscale (It actually further resizes outputs with LANCZOS4). Add *RealESRGAN_x2plus.pth* model.
- ✅ The inference code 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.

👀 Demos Videos

Bilibili

- 大闹天宫片段
- Anime dance cut 动漫魔性舞蹈
- 海贼王片段

YouTube

🔧 Dependencies and Installation

- Python >= 3.7 (Recommend to use Anaconda or Miniconda)
- PyTorch >= 1.7

Installation

1. Clone repo

    bash
    git clone https://github.com/xinntao/Real-ESRGAN.git
    cd Real-ESRGAN

1. Install dependent packages

……（后略，见原文）