Welcome to MMClassification’s documentation!

Get Started

• Prerequisites
• Installation

User Guides

• Inference with existing models
• Prepare Dataset
• Training and Test
• Learn about Configs
• Fine-tune Models

Useful Tools

• Dataset Visualization
• Hyper-parameter Scheduler Visualization
• Class Activation Map(CAM) Visualization
• How to Get the Complete Config
• Verify Dataset
• Log and Results Analysis
• Model Complexity Analysis
• Torchserve Deployment

Advanced Guides

• Adding New Dataset
• Customize Data Pipeline
• Customize Models
• Customize Training Schedule
• Customize Runtime Settings
• Customize Evaluation Metrics
• Data Flow (TODO)
• Convention in MMCLS

Model zoo

• Model Zoo Summary
• BEiT
• BEiT V2
• CLIP
• Conformer
• ConvMixer
• ConvNeXt
• ConvNeXt V2
• CSPNet
• CSRA
• DaViT
• DeiT
• DeiT III: Revenge of the ViT
• DenseNet
• EdgeNeXt
• EfficientFormer
• EfficientNet
• EfficientNetV2
• EVA
• HorNet
• HRNet
• Inception V3
• LeViT
• MixMIM
• Mlp-Mixer
• MobileNet V2
• MobileNet V3
• MobileOne
• MobileVit
• MViT V2
• PoolFormer
• RegNet
• RepLKNet
• RepMLP
• RepVGG
• Res2Net
• ResNet
• ResNeXt
• Reversible Vision Transformers
• SE-ResNet
• ShuffleNet V1
• ShuffleNet V2
• Swin Transformer
• Swin Transformer V2
• Tokens-to-Token ViT
• TinyViT
• TNT
• Twins
• Visual Attention Network
• VGG
• VIG
• Vision Transformer
• Wide-ResNet

Migration

• Migration from MMClassification 0.x

API Reference

• mmcls.apis
• mmcls.engine
• mmcls.datasets
• Data Process
• mmcls.models
• mmcls.structures
• mmcls.visualization
• mmcls.evaluation
• mmcls.utils

Notes

• Contributing to MMClassification
• Projects based on MMClassification
• Changelog
• Frequently Asked Questions

Switch Language

• English
• 简体中文

Indices and tables

• Index

• Search Page