2020-12-31 16:41:45 +08:00
## Changelog
2021-07-05 10:19:57 +08:00
### 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 )
2021-06-03 11:42:34 +08:00
### 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 )
2021-05-21 16:36:08 +08:00
### v0.11.1(21/5/2021)
2021-06-03 11:42:34 +08:00
- Refine `new_dataset.md` and add Chinese translation of `finture.md` , `new_dataset.md` .
2021-05-21 16:36:08 +08:00
#### 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 )
2021-05-01 22:26:39 +08:00
### v0.11.0(1/5/2021)
2021-06-03 11:42:34 +08:00
- 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.
2021-05-01 22:26:39 +08:00
#### 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 )
2021-04-01 10:39:18 +08:00
### 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 )
2021-03-01 20:14:53 +08:00
### 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 )
2021-01-31 17:50:40 +08:00
### 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 )
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### v0.7.0(31/12/2020)
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- Add more evaluation metrics.
- Fix bugs.
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#### 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 )
2021-01-31 17:50:40 +08:00
#### 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 )
2020-12-31 16:41:45 +08:00
### 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 )
2021-01-31 17:50:40 +08:00
#### 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 )
2020-12-31 16:41:45 +08:00
#### 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 )
