MMClassification Release V0.11.0

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)

MMClassification Release V0.10.0

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)

MMClassification Release V0.9.0

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)

MMClassification Release V0.8.0

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)

MMClassification Release V0.7.0

New Features

• Add evaluation metrics: precision, recall, and F1 score. (#93)
• Allow config override during testing and inference with --options. (#91 & #96)

Improvements

• Remove installation of MMCV from requirements. (#90)
• 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 numpy.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 structures. (#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)

MMClassification Release V0.6.0

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)