Tags: KeiChiTse/mmclassification
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v1.0.0rc5(30/12/2022) Highlights - Support EVA, RevViT, EfficientnetV2, CLIP, TinyViT and MixMIM backbones. - Reproduce the training accuracy of ConvNeXt and RepVGG. - Support multi-task training and testing. - Support Test-time Augmentation. New Features - [Feature] Add EfficientnetV2 Backbone. ([open-mmlab#1253](open-mmlab#1253)) - [Feature] Support TTA and add `--tta` in `tools/test.py`. ([open-mmlab#1161](open-mmlab#1161)) - [Feature] Support Multi-task. ([open-mmlab#1229](open-mmlab#1229)) - [Feature] Add clip backbone. ([open-mmlab#1258](open-mmlab#1258)) - [Feature] Add mixmim backbone with checkpoints. ([open-mmlab#1224](open-mmlab#1224)) - [Feature] Add TinyViT for dev-1.x. ([open-mmlab#1042](open-mmlab#1042)) - [Feature] Add some scripts for development. ([open-mmlab#1257](open-mmlab#1257)) - [Feature] Support EVA. ([open-mmlab#1239](open-mmlab#1239)) - [Feature] Implementation of RevViT. ([open-mmlab#1127](open-mmlab#1127)) Improvements - [Reproduce] Reproduce RepVGG Training Accuracy. ([open-mmlab#1264](open-mmlab#1264)) - [Enhance] Support ConvNeXt More Weights. ([open-mmlab#1240](open-mmlab#1240)) - [Reproduce] Update ConvNeXt config files. ([open-mmlab#1256](open-mmlab#1256)) - [CI] Update CI to test PyTorch 1.13.0. ([open-mmlab#1260](open-mmlab#1260)) - [Project] Add ACCV workshop 1st Solution. ([open-mmlab#1245](open-mmlab#1245)) - [Project] Add Example project. ([open-mmlab#1254](open-mmlab#1254)) Bug Fixes - [Fix] Fix imports in transforms. ([open-mmlab#1255](open-mmlab#1255)) - [Fix] Fix CAM visualization. ([open-mmlab#1248](open-mmlab#1248)) - [Fix] Fix the requirements and lazy register mmcls models. ([open-mmlab#1275](open-mmlab#1275))
v1.0.0rc4(06/12/2022) Highlights - Upgrade API to get pre-defined models of MMClassification. See [open-mmlab#1236](open-mmlab#1236) for more details. - Refactor BEiT backbone and support v1/v2 inference. See [open-mmlab#1144](open-mmlab#1144). New Features - Support getting model from the name defined in the model-index file. ([open-mmlab#1236](open-mmlab#1236)) Improvements - Support evaluate on both EMA and non-EMA models. ([open-mmlab#1204](open-mmlab#1204)) - Refactor BEiT backbone and support v1/v2 inference. ([open-mmlab#1144](open-mmlab#1144)) Bug Fixes - Fix `reparameterize_model.py` doesn't save meta info. ([open-mmlab#1221](open-mmlab#1221)) - Fix dict update in BEiT. ([open-mmlab#1234](open-mmlab#1234)) Docs Update - Update install tutorial. ([open-mmlab#1223](open-mmlab#1223)) - Update MobileNetv2 & MobileNetv3 readme. ([open-mmlab#1222](open-mmlab#1222)) - Add version selection in the banner. ([open-mmlab#1217](open-mmlab#1217))
v0.25.0(06/12/2022) Highlights - Support MLU backend. New Features - Support MLU backend. ([open-mmlab#1159](open-mmlab#1159)) - Support Activation Checkpointing for ConvNeXt. ([open-mmlab#1152](open-mmlab#1152)) Improvements - Add `dist_train_arm.sh` for ARM device and update NPU results. ([open-mmlab#1218](open-mmlab#1218)) Bug Fixes - Fix a bug caused `MMClsWandbHook` stuck. ([open-mmlab#1242](open-mmlab#1242)) - Fix the redundant `device_ids` in `tools/test.py`. ([open-mmlab#1215](open-mmlab#1215)) Docs Update - Add version banner and version warning in master docs. ([open-mmlab#1216](open-mmlab#1216)) - Update NPU support doc. ([open-mmlab#1198](open-mmlab#1198)) - Fixed typo in `pytorch2torchscript.md`. ([open-mmlab#1173](open-mmlab#1173)) - Fix typo in `miscellaneous.md`. ([open-mmlab#1137](open-mmlab#1137)) - further detail for the doc for `ClassBalancedDataset`. ([open-mmlab#901](open-mmlab#901))
v1.0.0rc3(21/11/2022) Highlights - Add **Switch Recipe** Hook, Now we can modify training pipeline, mixup and loss settings during training, see [open-mmlab#1101](open-mmlab#1101). - Add **TIMM and HuggingFace** wrappers. Now you can train/use models in TIMM/HuggingFace directly, see [open-mmlab#1102](open-mmlab#1102). - Support **retrieval tasks**, see [open-mmlab#1055](open-mmlab#1055). - Reproduce **mobileone** training accuracy. See [open-mmlab#1191](open-mmlab#1191) New Features - Add checkpoints from EfficientNets NoisyStudent & L2. ([open-mmlab#1122](open-mmlab#1122)) - Migrate CSRA head to 1.x. ([open-mmlab#1177](open-mmlab#1177)) - Support RepLKnet backbone. ([open-mmlab#1129](open-mmlab#1129)) - Add Switch Recipe Hook. ([open-mmlab#1101](open-mmlab#1101)) - Add adan optimizer. ([open-mmlab#1180](open-mmlab#1180)) - Support DaViT. ([open-mmlab#1105](open-mmlab#1105)) - Support Activation Checkpointing for ConvNeXt. ([open-mmlab#1153](open-mmlab#1153)) - Add TIMM and HuggingFace wrappers to build classifiers from them directly. ([open-mmlab#1102](open-mmlab#1102)) - Add reduction for neck ([open-mmlab#978](open-mmlab#978)) - Support HorNet Backbone for dev1.x. ([open-mmlab#1094](open-mmlab#1094)) - Add arcface head. ([open-mmlab#926](open-mmlab#926)) - Add Base Retriever and Image2Image Retriever for retrieval tasks. ([open-mmlab#1055](open-mmlab#1055)) - Support MobileViT backbone. ([open-mmlab#1068](open-mmlab#1068)) Improvements - [Enhance] Enhance ArcFaceClsHead. ([open-mmlab#1181](open-mmlab#1181)) - [Refactor] Refactor to use new fileio API in MMEngine. ([open-mmlab#1176](open-mmlab#1176)) - [Enhance] Reproduce mobileone training accuracy. ([open-mmlab#1191](open-mmlab#1191)) - [Enhance] add deleting params info in swinv2. ([open-mmlab#1142](open-mmlab#1142)) - [Enhance] Add more mobilenetv3 pretrains. ([open-mmlab#1154](open-mmlab#1154)) - [Enhancement] RepVGG for YOLOX-PAI for dev-1.x. ([open-mmlab#1126](open-mmlab#1126)) - [Improve] Speed up data preprocessor. ([open-mmlab#1064](open-mmlab#1064)) Bug Fixes - Fix the torchserve. ([open-mmlab#1143](open-mmlab#1143)) - Fix configs due to api refactor of `num_classes`. ([open-mmlab#1184](open-mmlab#1184)) - Update mmcls2torchserve. ([open-mmlab#1189](open-mmlab#1189)) - Fix for `inference_model` cannot get classes information in checkpoint. ([open-mmlab#1093](open-mmlab#1093)) Docs Update - Add not-found page extension. ([open-mmlab#1207](open-mmlab#1207)) - update visualization doc. ([open-mmlab#1160](open-mmlab#1160)) - Support sort and search the Model Summary table. ([open-mmlab#1100](open-mmlab#1100)) - Improve the ResNet model page. ([open-mmlab#1118](open-mmlab#1118)) - update the readme of convnext. ([open-mmlab#1156](open-mmlab#1156)) - Fix the installation docs link in README. ([open-mmlab#1164](open-mmlab#1164)) - Improve ViT and MobileViT model pages. ([open-mmlab#1155](open-mmlab#1155)) - Improve Swin Doc and Add Tabs enxtation. ([open-mmlab#1145](open-mmlab#1145)) - Add MMEval projects link in README. ([open-mmlab#1162](open-mmlab#1162)) - Add runtime configuration docs. ([open-mmlab#1128](open-mmlab#1128)) - Add custom evaluation docs ([open-mmlab#1130](open-mmlab#1130)) - Add custom pipeline docs. ([open-mmlab#1124](open-mmlab#1124)) - Add MMYOLO projects link in MMCLS1.x. ([open-mmlab#1117](open-mmlab#1117))
v0.24.1(31/10/2022) New Features - Support mmcls with NPU backend. ([open-mmlab#1072](open-mmlab#1072)) Bug Fixes - Fix performance issue in convnext DDP train. ([open-mmlab#1098](open-mmlab#1098))
v1.0.0rc2(12/10/2022) New Features - Support DeiT3. ([open-mmlab#1065](open-mmlab#1065)) Improvements - Update `analyze_results.py` for dev-1.x. ([open-mmlab#1071](open-mmlab#1071)) - Get scores from inference api. ([open-mmlab#1070](open-mmlab#1070)) Bug Fixes - Update requirements. ([open-mmlab#1083](open-mmlab#1083)) Docs Update - Add 1x docs schedule. ([open-mmlab#1015](open-mmlab#1015))
v1.0.0rc1(30/9/2022) New Features - Support MViT for MMCLS 1.x ([open-mmlab#1023](open-mmlab#1023)) - Add ViT huge architecture. ([open-mmlab#1049](open-mmlab#1049)) - Support EdgeNeXt for dev-1.x. ([open-mmlab#1037](open-mmlab#1037)) - Support Swin Transformer V2 for MMCLS 1.x. ([open-mmlab#1029](open-mmlab#1029)) - Add efficientformer Backbone for MMCls 1.x. ([open-mmlab#1031](open-mmlab#1031)) - Add MobileOne Backbone For MMCls 1.x. ([open-mmlab#1030](open-mmlab#1030)) - Support BEiT Transformer layer. ([open-mmlab#919](open-mmlab#919)) Improvements - \[Refactor\] Fix visualization tools. ([open-mmlab#1045](open-mmlab#1045)) - \[Improve\] Update benchmark scripts ([open-mmlab#1028](open-mmlab#1028)) - \[Improve\] Update tools to enable `pin_memory` and `persistent_workers` by default. ([open-mmlab#1024](open-mmlab#1024)) - \[CI\] Update circle-ci and github workflow. ([open-mmlab#1018](open-mmlab#1018)) Bug Fixes - Fix verify dataset tool in 1.x. ([open-mmlab#1062](open-mmlab#1062)) - Fix `loss_weight` in `LabelSmoothLoss`. ([open-mmlab#1058](open-mmlab#1058)) - Fix the output position of Swin-Transformer. ([open-mmlab#947](open-mmlab#947)) Docs Update - Auto generate model summary table. ([open-mmlab#1010](open-mmlab#1010)) - Refactor new modules tutorial. ([open-mmlab#998](open-mmlab#998))
v0.24.0(30/9/2022) Highlights - Support HorNet, EfficientFormerm, SwinTransformer V2 and MViT backbones. - Support Standford Cars dataset. New Features - Support HorNet Backbone. ([open-mmlab#1013](open-mmlab#1013)) - Support EfficientFormer. ([open-mmlab#954](open-mmlab#954)) - Support Stanford Cars dataset. ([open-mmlab#893](open-mmlab#893)) - Support CSRA head. ([open-mmlab#881](open-mmlab#881)) - Support Swin Transform V2. ([open-mmlab#799](open-mmlab#799)) - Support MViT and add checkpoints. ([open-mmlab#924](open-mmlab#924)) Improvements - \[Improve\] replace loop of progressbar in api/test. ([open-mmlab#878](open-mmlab#878)) - \[Enhance\] RepVGG for YOLOX-PAI. ([open-mmlab#1025](open-mmlab#1025)) - \[Enhancement\] Update VAN. ([open-mmlab#1017](open-mmlab#1017)) - \[Refactor\] Re-write `get_sinusoid_encoding` from third-party implementation. ([open-mmlab#965](open-mmlab#965)) - \[Improve\] Upgrade onnxsim to v0.4.0. ([open-mmlab#915](open-mmlab#915)) - \[Improve\] Fixed typo in `RepVGG`. ([open-mmlab#985](open-mmlab#985)) - \[Improve\] Using `train_step` instead of `forward` in PreciseBNHook ([open-mmlab#964](open-mmlab#964)) - \[Improve\] Use `forward_dummy` to calculate FLOPS. ([open-mmlab#953](open-mmlab#953)) Bug Fixes - Fix warning with `torch.meshgrid`. ([open-mmlab#860](open-mmlab#860)) - Add matplotlib minimum version requriments. ([open-mmlab#909](open-mmlab#909)) - val loader should not drop last by default. ([open-mmlab#857](open-mmlab#857)) - Fix config.device bug in toturial. ([open-mmlab#1059](open-mmlab#1059)) - Fix attenstion clamp max params ([open-mmlab#1034](open-mmlab#1034)) - Fix device mismatch in Swin-v2. ([open-mmlab#976](open-mmlab#976)) - Fix the output position of Swin-Transformer. ([open-mmlab#947](open-mmlab#947)) Docs Update - Fix typo in config.md. ([open-mmlab#827](open-mmlab#827)) - Add version for torchvision to avoide error. ([open-mmlab#903](open-mmlab#903)) - Fixed typo for `--out-dir` option of analyze_results.py. ([open-mmlab#898](open-mmlab#898)) - Refine the docstring of RegNet ([open-mmlab#935](open-mmlab#935))
v1.0.0rc0(31/8/2022) MMClassification 1.0.0rc0 is the first version of MMClassification 1.x, a part of the OpenMMLab 2.0 projects. Built upon the new [training engine](https://github.com/open-mmlab/mmengine), MMClassification 1.x unifies the interfaces of dataset, models, evaluation, and visualization. And there are some BC-breaking changes. Please check [the migration tutorial](https://mmclassification.readthedocs.io/en/1.x/migration.html) for more details.
v0.23.2(28/7/2022) New Features - Support MPS device. ([open-mmlab#894](open-mmlab#894)) Bug Fixes - Fix a bug in Albu which caused crashing. ([open-mmlab#918](open-mmlab#918))
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