MMClassification Release V0.18.0

Highlights

• Support MLP-Mixer backbone and provide pre-trained checkpoints.
• Add a tool to visualize the learning rate curve of the training phase. Welcome to use with the tutorial!

New Features

• Add MLP Mixer Backbone. (#528, #539)
• Support positive weights in BCE. (#516)
• Add a tool to visualize learning rate in each iterations. (#498)

Improvements

• Use CircleCI to do unit tests. (#567)
• Focal loss for single label tasks. (#548)
• Remove useless import_modules_from_string. (#544)
• Rename config files according to the config name standard. (#508)
• Use reset_classifier to remove head of timm backbones. (#534)
• Support passing arguments to loss from head. (#523)
• Refactor Resize transform and add Pad transform. (#506)
• Update mmcv dependency version. (#509)

Bug Fixes

• Fix bug when using ClassBalancedDataset. (#555)
• Fix a bug when using iter-based runner with 'val' workflow. (#542)
• Fix interpolation method checking in Resize. (#547)
• Fix a bug when load checkpoints in mulit-GPUs environment. (#527)
• Fix an error on indexing scalar metrics in analyze_result.py. (#518)
• Fix wrong condition judgment in analyze_logs.py and prevent empty curve. (#510)

Docs Update

• Fix vit config and model broken links. (#564)
• Add abstract and image for every paper. (#546)
• Add mmflow and mim in banner and readme. (#543)
• Add schedule and runtime tutorial docs. (#499)
• Add the top-5 acc in ResNet-CIFAR README. (#531)
• Fix TOC of visualization.md and add example images. (#513)
• Use docs link of other projects and add MMCV docs. (#511)

Contributors

A total of 9 developers contributed to this release.

@Ezra-Yu @LeoXing1996 @mzr1996 @0x4f5da2 @huoshuai-dot @imyhxy @juanjompz @okotaku @xcnick