Welcome to MMEditing’s documentation!

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Get Started

• Prerequisites
• Installation
  • Install with CPU only
  • Another option: Docker Image
  • A from-scratch setup script
• Demo
  • Inpainting
  • Matting
  • Restoration (Image)
  • Restoration (Face Image)
  • Restoration (Video)
  • Generation

Model Zoo

• Overview
  • Inpainting Models
  • Matting Models
  • Super-Resolution Models
  • Generation Models
• Inpainting Models
  • DeepFillv1 (CVPR’2018)
  • DeepFillv2 (CVPR’2019)
  • Global&Local (ToG’2017)
  • PConv (ECCV’2018)
• Matting Models
  • DIM (CVPR’2017)
  • GCA (AAAI’2020)
  • IndexNet (ICCV’2019)
• Super-Resolution Models
  • BasicVSR (CVPR’2021)
  • BasicVSR++
  • DIC (CVPR’2020)
  • EDSR (CVPR’2017)
  • EDVR (CVPRW’2019)
  • ESRGAN (ECCVW’2018)
  • GLEAN (CVPR’2021)
  • IconVSR (CVPR’2021)
  • LIIF (CVPR’2021)
  • RDN (CVPR’2018)
  • RealBasicVSR (arXiv’2021)
  • Real-ESRGAN (ICCVW’2021)
  • SRCNN (TPAMI’2015)
  • SRGAN (CVPR’2016)
  • TDAN (CVPR’2020)
  • TOFlow (IJCV’2019)
  • TTSR (CVPR’2020)
• Generation Models
  • CycleGAN (ICCV’2017)
  • Pix2Pix (CVPR’2017)

Datasets

• Overview
  • Generation Datasets
  • Inpainting Datasets
  • Matting Datasets
  • Super-Resolution Datasets
• Inpainting Datasets
  • CelebA-HQ Dataset
  • Paris Street View Dataset
  • Places365 Dataset
• Matting Datasets
  • Composition-1k Dataset
• Super-Resolution Datasets
  • DF2K_OST Dataset
  • DIV2K Dataset
  • REDS Dataset
  • Vid4 Dataset
  • Vimeo90K Dataset
• Generation Datasets
  • Paired Dataset for Pix2pix
  • Unpaired Dataset for CycleGAN

Quick Run

• Inference with pre-trained models
  • Test a pre-trained model
• Train a model
  • Train with single/multiple GPUs
  • Train with Slurm
  • Launch multiple jobs on a single machine

Tutorials

• Tutorial 1: Learn about Configs
  • Config Name Style
  • Config System for Generation
  • Config System for Inpainting
  • Config System for Matting
  • Config System for Restoration

Useful Tools and Scripts

• Useful tools
  • Get the FLOPs and params (experimental)
  • Publish a model
  • Convert to ONNX (experimental)
  • Convert ONNX to TensorRT (experimental)
  • Evaluate ONNX and TensorRT Models (experimental)

Notes

• Benchmark

FAQ

• FAQ
  • Use intermediate variables in configs

API Reference

• mmedit.core
• mmedit.datasets
  • datasets
  • pipelines
• mmedit.models
  • models
  • common
  • backbones
  • components
  • losses
• mmedit.utils

Switch Language

• English
• 简体中文

Indices and tables

• Index

• Module Index

• Search Page