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Changelog

v0.13.0(3/7/2021)

  • Support Swin-Transformer backbone and add training configs for Swin-Transformer on ImageNet.

New Features

  • Support Swin-Transformer backbone and add training configs for Swin-Transformer on ImageNet. (#271)
  • Add pretained model of RegNetX. (#269)
  • Support adding custom hooks in config file. (#305)
  • Improve and add Chinese translation of CONTRIBUTING.md and all tools tutorials. (#320)
  • Dump config before training. (#282)
  • Add torchscript and torchserve deployment tools. (#279, #284)

Improvements

  • Improve test tools and add some new tools. (#322)
  • Correct MobilenetV3 backbone structure and add pretained models. (#291)
  • Refactor PatchEmbed and HybridEmbed as independent components. (#330)
  • Refactor mixup and cutmix as Augments to support more funtions. (#278)
  • Refactor weights initialization method. (#270, #318, #319)
  • Refactor LabelSmoothLoss to support multiple calculation formulas. (#285)

Bug Fixes

  • Fix bug for CPU training. (#286)
  • Fix missing test data when num_imgs can not be evenly divided by num_gpus. (#299)
  • Fix build compatible with pytorch v1.3-1.5. (#301)
  • Fix magnitude_std bug in RandAugment. (#309)
  • Fix bug when samples_per_gpu is 1. (#311)

v0.12.0(3/6/2021)

  • Finish adding Chinese tutorials and build Chinese documentation on readthedocs.
  • Update ResNeXt checkpoints and ResNet checkpoints on CIFAR.

New Features

  • Improve and add Chinese translation of data_pipeline.md and new_modules.md. (#265)
  • Build Chinese translation on readthedocs. (#267)
  • Add an argument efficientnet_style to RandomResizedCrop and CenterCrop. (#268)

Improvements

  • Only allow directory operation when rank==0 when testing. (#258)
  • Fix typo in base_head. (#274)
  • Update ResNeXt checkpoints. (#283)

Bug Fixes

  • Add attribute data.test in MNIST configs. (#264)
  • Download CIFAR/MNIST dataset only on rank 0. (#273)
  • Fix MMCV version compatibility. (#276)
  • Fix CIFAR color channels bug and update checkpoints in model zoo. (#280)

v0.11.1(21/5/2021)

  • Refine new_dataset.md and add Chinese translation of finture.md, new_dataset.md.

New Features

  • Add dim argument for GlobalAveragePooling. (#236)
  • Add random noise to RandAugment magnitude. (#240)
  • Refine new_dataset.md and add Chinese translation of finture.md, new_dataset.md. (#243)

Improvements

  • Refactor arguments passing for Heads. (#239)
  • Allow more flexible magnitude_range in RandAugment. (#249)
  • Inherits MMCV registry so that in the future OpenMMLab repos like MMDet and MMSeg could directly use the backbones supported in MMCls. (#252)

Bug Fixes

  • Fix typo in analyze_results.py. (#237)
  • Fix typo in unittests. (#238)
  • Check if specified tmpdir exists when testing to avoid deleting existing data. (#242 & #258)
  • Add missing config files in MANIFEST.in. (#250 & #255)
  • Use temporary directory under shared directory to collect results to avoid unavailability of temporary directory for multi-node testing. (#251)

v0.11.0(1/5/2021)

  • Support cutmix trick.
  • Support random augmentation.
  • Add tools/deployment/test.py as a ONNX runtime test tool.
  • Support ViT backbone and add training configs for ViT on ImageNet.
  • Add Chinese README.md and some Chinese tutorials.

New Features

  • Support cutmix trick. (#198)
  • Add simplify option in pytorch2onnx.py. (#200)
  • Support random augmentation. (#201)
  • Add config and checkpoint for training ResNet on CIFAR-100. (#208)
  • Add tools/deployment/test.py as a ONNX runtime test tool. (#212)
  • Support ViT backbone and add training configs for ViT on ImageNet. (#214)
  • Add finetuning configs for ViT on ImageNet. (#217)
  • Add device option to support training on CPU. (#219)
  • Add Chinese README.md and some Chinese tutorials. (#221)
  • Add metafile.yml in configs to support interaction with paper with code(PWC) and MMCLI. (#225)
  • Upload configs and converted checkpoints for ViT fintuning on ImageNet. (#230)

Improvements

  • Fix LabelSmoothLoss so that label smoothing and mixup could be enabled at the same time. (#203)
  • Add cal_acc option in ClsHead. (#206)
  • Check CLASSES in checkpoint to avoid unexpected key error. (#207)
  • Check mmcv version when importing mmcls to ensure compatibility. (#209)
  • Update CONTRIBUTING.md to align with that in MMCV. (#210)
  • Change tags to html comments in configs README.md. (#226)
  • Clean codes in ViT backbone. (#227)
  • Reformat pytorch2onnx.md tutorial. (#229)
  • Update setup.py to support MMCLI. (#232)

Bug Fixes

  • Fix missing cutmix_prob in ViT configs. (#220)
  • Fix backend for resize in ResNeXt configs. (#222)

v0.10.0(1/4/2021)

  • Support AutoAugmentation
  • Add tutorials for installation and usage.

New Features

  • Add Rotate pipeline for data augmentation. (#167)
  • Add Invert pipeline for data augmentation. (#168)
  • Add Color pipeline for data augmentation. (#171)
  • Add Solarize and Posterize pipeline for data augmentation. (#172)
  • Support fp16 training. (#178)
  • Add tutorials for installation and basic usage of MMClassification.(#176)
  • Support AutoAugmentation, AutoContrast, Equalize, Contrast, Brightness and Sharpness pipelines for data augmentation. (#179)

Improvements

  • Support dynamic shape export to onnx. (#175)
  • Release training configs and update model zoo for fp16 (#184)
  • Use MMCV's EvalHook in MMClassification (#182)

Bug Fixes

  • Fix wrong naming in vgg config (#181)

v0.9.0(1/3/2021)

  • Implement mixup trick.
  • Add a new tool to create TensorRT engine from ONNX, run inference and verify outputs in Python.

New Features

  • Implement mixup and provide configs of training ResNet50 using mixup. (#160)
  • Add Shear pipeline for data augmentation. (#163)
  • Add Translate pipeline for data augmentation. (#165)
  • Add tools/onnx2tensorrt.py as a tool to create TensorRT engine from ONNX, run inference and verify outputs in Python. (#153)

Improvements

  • Add --eval-options in tools/test.py to support eval options override, matching the behavior of other open-mmlab projects. (#158)
  • Support showing and saving painted results in mmcls.apis.test and tools/test.py, matching the behavior of other open-mmlab projects. (#162)

Bug Fixes

  • Fix configs for VGG, replace checkpoints converted from other repos with the ones trained by ourselves and upload the missing logs in the model zoo. (#161)

v0.8.0(31/1/2021)

  • Support multi-label task.
  • Support more flexible metrics settings.
  • Fix bugs.

New Features

  • Add evaluation metrics: mAP, CP, CR, CF1, OP, OR, OF1 for multi-label task. (#123)
  • Add BCE loss for multi-label task. (#130)
  • Add focal loss for multi-label task. (#131)
  • Support PASCAL VOC 2007 dataset for multi-label task. (#134)
  • Add asymmetric loss for multi-label task. (#132)
  • Add analyze_results.py to select images for success/fail demonstration. (#142)
  • Support new metric that calculates the total number of occurrences of each label. (#143)
  • Support class-wise evaluation results. (#143)
  • Add thresholds in eval_metrics. (#146)
  • Add heads and a baseline config for multilabel task. (#145)

Improvements

  • Remove the models with 0 checkpoint and ignore the repeated papers when counting papers to gain more accurate model statistics. (#135)
  • Add tags in README.md. (#137)
  • Fix optional issues in docstring. (#138)
  • Update stat.py to classify papers. (#139)
  • Fix mismatched columns in README.md. (#150)
  • Fix test.py to support more evaluation metrics. (#155)

Bug Fixes

  • Fix bug in VGG weight_init. (#140)
  • Fix bug in 2 ResNet configs in which outdated heads were used. (#147)
  • Fix bug of misordered height and width in RandomCrop and RandomResizedCrop. (#151)
  • Fix missing meta_keys in Collect. (#149 & #152)

v0.7.0(31/12/2020)

  • Add more evaluation metrics.
  • Fix bugs.

New Features

  • Remove installation of MMCV from requirements. (#90)
  • Add 3 evaluation metrics: precision, recall and F-1 score. (#93)
  • Allow config override during testing and inference with --options. (#91 & #96)

Improvements

  • Use build_runner to make runners more flexible. (#54)
  • Support to get category ids in BaseDataset. (#72)
  • Allow CLASSES override during BaseDateset initialization. (#85)
  • Allow input image as ndarray during inference. (#87)
  • Optimize MNIST config. (#98)
  • Add config links in model zoo documentation. (#99)
  • Use functions from MMCV to collect environment. (#103)
  • Refactor config files so that they are now categorized by methods. (#116)
  • Add README in config directory. (#117)
  • Add model statistics. (#119)
  • Refactor documentation in consistency with other MM repositories. (#126)

Bug Fixes

  • Add missing CLASSES argument to dataset wrappers. (#66)
  • Fix slurm evaluation error during training. (#69)
  • Resolve error caused by shape in Accuracy. (#104)
  • Fix bug caused by extremely insufficient data in distributed sampler.(#108)
  • Fix bug in gpu_ids in distributed training. (#107)
  • Fix bug caused by extremely insufficient data in collect results during testing (#114)

v0.6.0(11/10/2020)

  • Support new method: ResNeSt and VGG.
  • Support new dataset: CIFAR10.
  • Provide new tools to do model inference, model conversion from pytorch to onnx.

New Features

  • Add model inference. (#16)
  • Add pytorch2onnx. (#20)
  • Add PIL backend for transform Resize. (#21)
  • Add ResNeSt. (#25)
  • Add VGG and its pretained models. (#27)
  • Add CIFAR10 configs and models. (#38)
  • Add albumentations transforms. (#45)
  • Visualize results on image demo. (#58)

Improvements

  • Replace urlretrieve with urlopen in dataset.utils. (#13)
  • Resize image according to its short edge. (#22)
  • Update ShuffleNet config. (#31)
  • Update pre-trained models for shufflenet_v2, shufflenet_v1, se-resnet50, se-resnet101. (#33)

Bug Fixes

  • Fix init_weights in shufflenet_v2.py. (#29)
  • Fix the parameter size in test_pipeline. (#30)
  • Fix the parameter in cosine lr schedule. (#32)
  • Fix the convert tools for mobilenet_v2. (#34)
  • Fix crash in CenterCrop transform when image is greyscale (#40)
  • Fix outdated configs. (#53)