Package: ray-mmedit
OpenMMLab websiteHOTOpenMMLab platformTRY IT OUT📘Documentation|🛠️Installation|👀Model Zoo|🆕Update News|🚀Ongoing Projects|🤔Reporting IssuesEnglish |简体中文IntroductionMMEditing is an open-source image and video editing toolbox based on PyTorch. It is a part of theOpenMMLabproject.Currently, MMEditing supports the following tasks:The master branch works withPyTorch 1.5+.Some Demos:https://user-images.githubusercontent.com/12756472/175944645-cabe8c2b-9f25-440b-91cc-cdac4e752c5a.mp4https://user-images.githubusercontent.com/12756472/158972813-d8d0f19c-f49c-4618-9967-52652726ef19.mp4Major featuresModular designWe decompose the editing framework into different components and one can easily construct a customized editor framework by combining different modules.Support of multiple tasks in editingThe toolbox directly supports popular and contemporaryinpainting,matting,super-resolutionandgenerationtasks.State of the artThe toolbox provides state-of-the-art methods in inpainting/matting/super-resolution/generation.Note thatMMSRhas been merged into this repo, as a part of MMEditing.
With elaborate designs of the new framework and careful implementations,
hope MMEditing could provide better experience.What's New💎 Stable version0.16.0was released in 31/10/2022:VisualizationHookis deprecated. Users should useMMEditVisualizationHookinstead.Fix FLAVR register.Fix the number of channels in RDB.Please refer tochangelog.mdfor details and release history.🌟 Preview of 1.x versionA brand new version ofMMEditing v1.0.0rc1was released in 24/09/2022:Support all the tasks, models, metrics, and losses inMMGeneration😍。Unifies interfaces of all components based onMMEngine.Refactored and more flexiblearchitecture.Find more new features in1.x branch. Issues and PRs are welcome!InstallationMMEditing depends onPyTorchandMMCV.
Below are quick steps for installation.Step 1.Install PyTorch followingofficial instructions.Step 2.Install MMCV withMIM.pip3installopenmim
miminstallmmcv-fullStep 3.Install MMEditing from source.gitclonehttps://github.com/open-mmlab/mmediting.gitcdmmediting
pip3install-e.Please refer toinstall.mdfor more detailed instruction.Getting StartedPlease seegetting_started.mdanddemo.mdfor the basic usage of MMEditing.Model ZooSupported algorithms:InpaintingGlobal&Local(ToG'2017)DeepFillv1(CVPR'2018)PConv(ECCV'2018)DeepFillv2(CVPR'2019)AOT-GAN(TVCG'2021)MattingDIM(CVPR'2017)IndexNet(ICCV'2019)GCA(AAAI'2020)Image-Super-ResolutionSRCNN(TPAMI'2015)SRResNet&SRGAN(CVPR'2016)EDSR(CVPR'2017)ESRGAN(ECCV'2018)RDN(CVPR'2018)DIC(CVPR'2020)TTSR(CVPR'2020)GLEAN(CVPR'2021)LIIF(CVPR'2021)Video-Super-ResolutionEDVR(CVPR'2019)TOF(IJCV'2019)TDAN(CVPR'2020)BasicVSR(CVPR'2021)IconVSR(CVPR'2021)BasicVSR++(CVPR'2022)RealBasicVSR(CVPR'2022)GenerationCycleGAN(ICCV'2017)pix2pix(CVPR'2017)Video InterpolationTOFlow(IJCV'2019)CAIN(AAAI'2020)FLAVR(CVPR'2021)Please refer tomodel_zoofor more details.ContributingWe appreciate all contributions to improve MMEditing. Please refer to ourcontributing guidelines.AcknowledgementMMEditing is an open source project that is contributed by researchers and engineers from various colleges and companies. We appreciate all the contributors who implement their methods or add new features, as well as users who give valuable feedbacks. We wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new methods.CitationIf MMEditing is helpful to your research, please cite it as below.@misc{mmediting2022,title={{MMEditing}: {OpenMMLab} Image and Video Editing Toolbox},author={{MMEditing Contributors}},howpublished={\url{https://github.com/open-mmlab/mmediting}},year={2022}}LicenseThis project is released under theApache 2.0 license.Projects in OpenMMLabMMCV: OpenMMLab foundational library for computer vision.MIM: MIM installs OpenMMLab packages.MMClassification: OpenMMLab image classification toolbox and benchmark.MMDetection: OpenMMLab detection toolbox and benchmark.MMDetection3D: OpenMMLab's next-generation platform for general 3D object detection.MMRotate: OpenMMLab rotated object detection toolbox and benchmark.MMSegmentation: OpenMMLab semantic segmentation toolbox and benchmark.MMOCR: OpenMMLab text detection, recognition, and understanding toolbox.MMPose: OpenMMLab pose estimation toolbox and benchmark.MMHuman3D: OpenMMLab 3D human parametric model toolbox and benchmark.MMSelfSup: OpenMMLab self-supervised learning toolbox and benchmark.MMRazor: OpenMMLab model compression toolbox and benchmark.MMFewShot: OpenMMLab fewshot learning toolbox and benchmark.MMAction2: OpenMMLab's next-generation action understanding toolbox and benchmark.MMTracking: OpenMMLab video perception toolbox and benchmark.MMFlow: OpenMMLab optical flow toolbox and benchmark.MMEditing: OpenMMLab image and video editing toolbox.MMGeneration: OpenMMLab image and video generative models toolbox.MMDeploy: OpenMMLab model deployment framework.