Package: realesrgan
English|简体中文👀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_6Bfor anime images(动漫插图模型). Please see [anime_model]:boom:Updateonline Replicate demo:Online Colab demo for Real-ESRGAN:|Online Colab demo for for Real-ESRGAN (anime videos):PortableWindows/Linux/MacOSexecutable files for Intel/AMD/Nvidia GPU. You can find more informationhere. The ncnn implementation is inReal-ESRGAN-ncnn-vulkanReal-ESRGAN aims at developingPractical 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 infeedback.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 ShanTencent ARC Lab; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences🚩 Updates✅ Add therealesr-general-x4v3model - a tiny small model for general scenes. It also supports the--dnoption to balance the noise (avoiding over-smooth results).--dnis short for denoising strength.✅ Update theRealESRGAN AnimeVideo-v3model. Please seeanime video modelsandcomparisonsfor more details.✅ Add small models for anime videos. More details are inanime video models.✅ Add the ncnn implementationReal-ESRGAN-ncnn-vulkan.✅ AddRealESRGAN_x4plus_anime_6B.pth, which is optimized foranimeimages with much smaller model size. More details and comparisons withwaifu2xare inanime_model.md✅ Support finetuning on your own data or paired data (i.e., finetuning ESRGAN). Seehere✅ IntegrateGFPGANto supportface enhancement.✅ Integrated toHuggingface SpaceswithGradio. SeeGradio Web Demo. Thanks@AK391✅ Support arbitrary scale with--outscale(It actually further resizes outputs withLANCZOS4). AddRealESRGAN_x2plus.pthmodel.✅The inference codesupports: 1)tileoptions; 2) images withalpha channel; 3)grayimages; 4)16-bitimages.✅ The training codes have been released. A detailed guide can be found inTraining.md.👀 Demos VideosBilibili大闹天宫片段Anime dance cut 动漫魔性舞蹈海贼王片段YouTube🔧 Dependencies and InstallationPython >= 3.7 (Recommend to useAnacondaorMiniconda)PyTorch >= 1.7InstallationClone repogitclonehttps://github.com/xinntao/Real-ESRGAN.gitcdReal-ESRGANInstall dependent packages# Install basicsr - https://github.com/xinntao/BasicSR# We use BasicSR for both training and inferencepipinstallbasicsr# facexlib and gfpgan are for face enhancementpipinstallfacexlib
pipinstallgfpgan
pipinstall-rrequirements.txt
pythonsetup.pydevelop⚡ Quick InferenceThere are usually three ways to inference Real-ESRGAN.Online inferencePortable executable files (NCNN)Python scriptOnline inferenceYou can try in our website:ARC Demo(now only support RealESRGAN_x4plus_anime_6B)Colab Demofor Real-ESRGAN|Colab Demofor Real-ESRGAN (anime videos).Portable executable files (NCNN)You can downloadWindows/Linux/MacOSexecutable files for Intel/AMD/Nvidia GPU.This executable file isportableand includes all the binaries and models required. No CUDA or PyTorch environment is needed.You can simply run the following command (the Windows example, more information is in the README.md of each executable files):./realesrgan-ncnn-vulkan.exe-iinput.jpg-ooutput.png-nmodel_nameWe have provided five models:realesrgan-x4plus  (default)realesrnet-x4plusrealesrgan-x4plus-anime (optimized for anime images, small model size)realesr-animevideov3 (animation video)You can use the-nargument for other models, for example,./realesrgan-ncnn-vulkan.exe -i input.jpg -o output.png -n realesrnet-x4plusUsage of portable executable filesPlease refer toReal-ESRGAN-ncnn-vulkanfor more details.Note that it does not support all the functions (such asoutscale) as the python scriptinference_realesrgan.py.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 outputNote 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.Python scriptUsage of python scriptYou can use X4 model forarbitrary output sizewith the argumentoutscale. The program will further perform cheap resize operation after the Real-ESRGAN output.Usage: python inference_realesrgan.py -n RealESRGAN_x4plus -i infile -o outfile [options]...A common command: python inference_realesrgan.py -n RealESRGAN_x4plus -i infile --outscale 3.5 --face_enhance-h                   show this help-i --input           Input image or folder. Default: inputs-o --output          Output folder. Default: results-n --model_name      Model name. Default: RealESRGAN_x4plus-s, --outscale       The final upsampling scale of the image. Default: 4--suffix             Suffix of the restored image. Default: out-t, --tile           Tile size, 0 for no tile during testing. Default: 0--face_enhance       Whether to use GFPGAN to enhance face. Default: False--fp32               Use fp32 precision during inference. Default: fp16 (half precision).--ext                Image extension. Options: auto | jpg | png, auto means using the same extension as inputs. Default: autoInference general imagesDownload pre-trained models:RealESRGAN_x4plus.pthwgethttps://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth-PweightsInference!pythoninference_realesrgan.py-nRealESRGAN_x4plus-iinputs--face_enhanceResults are in theresultsfolderInference anime imagesPre-trained models:RealESRGAN_x4plus_anime_6BMore details and comparisons withwaifu2xare inanime_model.md# download modelwgethttps://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth-Pweights# inferencepythoninference_realesrgan.py-nRealESRGAN_x4plus_anime_6B-iinputsResults are in theresultsfolderBibTeX@InProceedings{wang2021realesrgan,
    author    = {Xintao Wang and Liangbin Xie and Chao Dong and Ying Shan},
    title     = {Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data},
    booktitle = {International Conference on Computer Vision Workshops (ICCVW)},
    date      = {2021}
}📧 ContactIf you have any question, please emailxintao.wang@outlook.comorxintaowang@tencent.com.🧩 Projects that use Real-ESRGANIf you develop/use Real-ESRGAN in your projects, welcome to let me know.NCNN-Android:RealSR-NCNN-AndroidbytumuyanVapourSynth:vs-realesrganbyHolyWuNCNN:Real-ESRGAN-ncnn-vulkanGUIWaifu2x-Extension-GUIbyAaronFeng753Squirrel-RIFEbyJustin62628Real-GUIbyscifxReal-ESRGAN_GUIbynet2cnReal-ESRGAN-EGUIbyWGzeyuanime_upscalerbyshangar21UpscaylbyNayam AmarsheandTGS963🤗 AcknowledgementThanks for all the contributors.AK391: Integrate RealESRGAN toHuggingface SpaceswithGradio. SeeGradio Web Demo.Asiimoviet: Translate the README.md to Chinese (中文).2ji3150: Thanks for thedetailed and valuable feedbacks/suggestions.Jared-02: Translate the Training.md to Chinese (中文).