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v1.2.0
17a886c
2024-01-04 20:43
下载
v1.1.1
e95d9ac
2023-11-15 17:34
下载
v1.1.0
v1.1.0(12/10/2023) New Features - [Feature] Implement of Zero-Shot CLIP Classifier ([#1737](https://github.com/open-mmlab/mmpretrain/pull/1737)) - [Feature] Add minigpt4 gradio demo and training script. ([#1758](https://github.com/open-mmlab/mmpretrain/pull/1758)) Improvements - [Config] New Version of config Adapting MobileNet Algorithm ([#1774](https://github.com/open-mmlab/mmpretrain/pull/1774)) - [Config] Support DINO self-supervised learning in project ([#1756](https://github.com/open-mmlab/mmpretrain/pull/1756)) - [Config] New Version of config Adapting Swin Transformer Algorithm ([#1780](https://github.com/open-mmlab/mmpretrain/pull/1780)) - [Enhance] Add iTPN Supports for Non-three channel image ([#1735](https://github.com/open-mmlab/mmpretrain/pull/1735)) - [Docs] Update dataset download script from opendatalab to openXlab ([#1765](https://github.com/open-mmlab/mmpretrain/pull/1765)) - [Docs] Update COCO-Retrieval dataset docs. ([#1806](https://github.com/open-mmlab/mmpretrain/pull/1806)) Bug Fix - Update `train.py` to compat with new config. - Update OFA module to compat with the latest huggingface. - Fix pipeline bug in ImageRetrievalInferencer.
a4c219e
2023-10-12 17:20
下载
v1.0.2
v1.0.2(15/08/2023) New Features - Add MFF ([#1725](https://github.com/open-mmlab/mmpretrain/pull/1725)) - Support training of BLIP2 ([#1700](https://github.com/open-mmlab/mmpretrain/pull/1700)) Improvements - New Version of config Adapting MAE Algorithm ([#1750](https://github.com/open-mmlab/mmpretrain/pull/1750)) - New Version of config Adapting ConvNeXt Algorithm ([#1760](https://github.com/open-mmlab/mmpretrain/pull/1760)) - New version of config adapting BeitV2 Algorithm ([#1755](https://github.com/open-mmlab/mmpretrain/pull/1755)) - Update `dataset_prepare.md` ([#1732](https://github.com/open-mmlab/mmpretrain/pull/1732)) - New Version of `config` Adapting Vision Transformer Algorithm ([#1727](https://github.com/open-mmlab/mmpretrain/pull/1727)) - Support Infographic VQA dataset and ANLS metric. ([#1667](https://github.com/open-mmlab/mmpretrain/pull/1667)) - Support IconQA dataset. ([#1670](https://github.com/open-mmlab/mmpretrain/pull/1670)) - Fix typo MIMHIVIT to MAEHiViT ([#1749](https://github.com/open-mmlab/mmpretrain/pull/1749))
732b0f4
2023-08-15 15:10
下载
v1.0.1
v1.0.1(31/07/2023) Improvements - Add init_cfg with type='pretrained' to downstream tasks ([#1717](https://github.com/open-mmlab/mmpretrain/pull/1717) - Set 'is_init' in some multimodal methods ([#1718](https://github.com/open-mmlab/mmpretrain/pull/1718) - Adapt test cases on Ascend NPU ([#1728](https://github.com/open-mmlab/mmpretrain/pull/1728) - Add GPU Acceleration Apple silicon mac ([#1699](https://github.com/open-mmlab/mmpretrain/pull/1699) - BEiT refactor ([#1705](https://github.com/open-mmlab/mmpretrain/pull/1705) Bug Fixes - Fix dict update in minigpt4. ([#1709](https://github.com/open-mmlab/mmpretrain/pull/1709) - Fix nested predict for multi-task prediction ([#1716](https://github.com/open-mmlab/mmpretrain/pull/1716) - Fix the issue #1711 "GaussianBlur doesn't work" ([#1722](https://github.com/open-mmlab/mmpretrain/pull/1722) - Just to correct a typo of 'target' ([#1655](https://github.com/open-mmlab/mmpretrain/pull/1655) - Fix freeze without cls_token in vit ([#1693](https://github.com/open-mmlab/mmpretrain/pull/1693) - Fix RandomCrop bug ([#1706](https://github.com/open-mmlab/mmpretrain/pull/1706) Docs Update - Fix spelling ([#1689](https://github.com/open-mmlab/mmpretrain/pull/1689)
5c71eba
2023-07-31 17:08
下载
1.0.0
ae7a7b7
2023-07-05 11:51
下载
v1.0.0rc8
v1.0.0rc8(22/05/2023) Highlights - Support multiple multi-modal algorithms and inferencers. You can explore these features by the [gradio demo](https://github.com/open-mmlab/mmpretrain/tree/main/projects/gradio_demo)! - Add EVA-02, Dino-V2, ViT-SAM and GLIP backbones. - Register torchvision transforms into MMPretrain, you can now easily integrate torchvision's data augmentations in MMPretrain. New Features - Support Chinese CLIP. ([#1576](https://github.com/open-mmlab/mmpretrain/pull/1576)) - Add ScienceQA Metrics ([#1577](https://github.com/open-mmlab/mmpretrain/pull/1577)) - Support multiple multi-modal algorithms and inferencers. ([#1561](https://github.com/open-mmlab/mmpretrain/pull/1561)) - add eva02 backbone ([#1450](https://github.com/open-mmlab/mmpretrain/pull/1450)) - Support dinov2 backbone ([#1522](https://github.com/open-mmlab/mmpretrain/pull/1522)) - Support some downstream classification datasets. ([#1467](https://github.com/open-mmlab/mmpretrain/pull/1467)) - Support GLIP ([#1308](https://github.com/open-mmlab/mmpretrain/pull/1308)) - Register torchvision transforms into mmpretrain ([#1265](https://github.com/open-mmlab/mmpretrain/pull/1265)) - Add ViT of SAM ([#1476](https://github.com/open-mmlab/mmpretrain/pull/1476)) Improvements - [Refactor] Support to freeze channel reduction and add layer decay function ([#1490](https://github.com/open-mmlab/mmpretrain/pull/1490)) - [Refactor] Support resizing pos_embed while loading ckpt and format output ([#1488](https://github.com/open-mmlab/mmpretrain/pull/1488)) Bug Fixes - Fix scienceqa ([#1581](https://github.com/open-mmlab/mmpretrain/pull/1581)) - Fix config of beit ([#1528](https://github.com/open-mmlab/mmpretrain/pull/1528)) - Incorrect stage freeze on RIFormer Model ([#1573](https://github.com/open-mmlab/mmpretrain/pull/1573)) - Fix ddp bugs caused by `out_type`. ([#1570](https://github.com/open-mmlab/mmpretrain/pull/1570)) - Fix multi-task-head loss potential bug ([#1530](https://github.com/open-mmlab/mmpretrain/pull/1530)) - Support bce loss without batch augmentations ([#1525](https://github.com/open-mmlab/mmpretrain/pull/1525)) - Fix clip generator init bug ([#1518](https://github.com/open-mmlab/mmpretrain/pull/1518)) - Fix the bug in binary cross entropy loss ([#1499](https://github.com/open-mmlab/mmpretrain/pull/1499)) Docs Update - Update PoolFormer citation to CVPR version ([#1505](https://github.com/open-mmlab/mmpretrain/pull/1505)) - Refine Inference Doc ([#1489](https://github.com/open-mmlab/mmpretrain/pull/1489)) - Add doc for usage of confusion matrix ([#1513](https://github.com/open-mmlab/mmpretrain/pull/1513)) - Update MMagic link ([#1517](https://github.com/open-mmlab/mmpretrain/pull/1517)) - Fix example_project README ([#1575](https://github.com/open-mmlab/mmpretrain/pull/1575)) - Add NPU support page ([#1481](https://github.com/open-mmlab/mmpretrain/pull/1481)) - train cfg: Removed old description ([#1473](https://github.com/open-mmlab/mmpretrain/pull/1473)) - Fix typo in MultiLabelDataset docstring ([#1483](https://github.com/open-mmlab/mmpretrain/pull/1483))
4dd8a86
2023-05-23 11:22
下载
v1.0.0rc7
9cbecea
2023-04-07 17:34
下载
v1.0.0rc6
v1.0.0rc6(06/04/2023) Highlights - Support OOD datasets. - Support confusion matrix calculation and plot. - Support LeViT, XCiT, ViG and ConvNeXt-V2 backbone. New Features - Support Out-of-Distribution datasets like ImageNet-A,R,S,C. ([#1342](https://github.com/open-mmlab/mmclassification/pull/1342)) - Support XCiT Backbone. ([#1305](https://github.com/open-mmlab/mmclassification/pull/1305)) - Support calculate confusion matrix and plot it. ([#1287](https://github.com/open-mmlab/mmclassification/pull/1287)) - Support RetrieverRecall metric & Add ArcFace config ([#1316](https://github.com/open-mmlab/mmclassification/pull/1316)) - Add `ImageClassificationInferencer`. ([#1261](https://github.com/open-mmlab/mmclassification/pull/1261)) - Support InShop Dataset (Image Retrieval). ([#1019](https://github.com/open-mmlab/mmclassification/pull/1019)) - Support LeViT backbone. ([#1238](https://github.com/open-mmlab/mmclassification/pull/1238)) - Support VIG Backbone. ([#1304](https://github.com/open-mmlab/mmclassification/pull/1304)) - Support ConvNeXt-V2 backbone. ([#1294](https://github.com/open-mmlab/mmclassification/pull/1294)) Improvements - [Enhance] Add stochastic depth decay rule in resnet. ([#1363](https://github.com/open-mmlab/mmclassification/pull/1363)) - [Refactor] Update analysis tools and documentations. ([#1359](https://github.com/open-mmlab/mmclassification/pull/1359)) - [Refactor] Unify the `--out` and `--dump` in `tools/test.py`. ([#1307](https://github.com/open-mmlab/mmclassification/pull/1307)) - [Enhance] Enable to toggle whether Gem Pooling is trainable or not. ([#1246](https://github.com/open-mmlab/mmclassification/pull/1246)) - [Improve] Update registries of mmcls. ([#1306](https://github.com/open-mmlab/mmclassification/pull/1306)) - [Tool] Add metafile fill and validation tools. ([#1297](https://github.com/open-mmlab/mmclassification/pull/1297)) - [Improve] Remove useless EfficientnetV2 config files. ([#1300](https://github.com/open-mmlab/mmclassification/pull/1300)) Bug Fixes - Fix precise bn hook ([#1386](https://github.com/open-mmlab/mmclassification/pull/1386)) - Fix acc evalustion wait for long ([#1430](https://github.com/open-mmlab/mmclassification/pull/1430)) - Fix retrieval multi gpu bug ([#1319](https://github.com/open-mmlab/mmclassification/pull/1319)) - Fix error repvgg-deploy base config path. ([#1357](https://github.com/open-mmlab/mmclassification/pull/1357)) - Fix bug in test tools. ([#1309](https://github.com/open-mmlab/mmclassification/pull/1309)) Docs Update - Update Readme ([#1442](https://github.com/open-mmlab/mmclassification/pull/1442)) - Add NPU support page. ([#1437](https://github.com/open-mmlab/mmclassification/pull/1437)) - Translate some tools tutorials to Chinese. ([#1321](https://github.com/open-mmlab/mmclassification/pull/1321)) - Add Chinese translation for runtime.md. ([#1313](https://github.com/open-mmlab/mmclassification/pull/1313))
3ff80f5
2023-04-06 13:05
下载
v1.0.0rc5
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. ([#1253](https://github.com/open-mmlab/mmclassification/pull/1253)) - [Feature] Support TTA and add `--tta` in `tools/test.py`. ([#1161](https://github.com/open-mmlab/mmclassification/pull/1161)) - [Feature] Support Multi-task. ([#1229](https://github.com/open-mmlab/mmclassification/pull/1229)) - [Feature] Add clip backbone. ([#1258](https://github.com/open-mmlab/mmclassification/pull/1258)) - [Feature] Add mixmim backbone with checkpoints. ([#1224](https://github.com/open-mmlab/mmclassification/pull/1224)) - [Feature] Add TinyViT for dev-1.x. ([#1042](https://github.com/open-mmlab/mmclassification/pull/1042)) - [Feature] Add some scripts for development. ([#1257](https://github.com/open-mmlab/mmclassification/pull/1257)) - [Feature] Support EVA. ([#1239](https://github.com/open-mmlab/mmclassification/pull/1239)) - [Feature] Implementation of RevViT. ([#1127](https://github.com/open-mmlab/mmclassification/pull/1127)) Improvements - [Reproduce] Reproduce RepVGG Training Accuracy. ([#1264](https://github.com/open-mmlab/mmclassification/pull/1264)) - [Enhance] Support ConvNeXt More Weights. ([#1240](https://github.com/open-mmlab/mmclassification/pull/1240)) - [Reproduce] Update ConvNeXt config files. ([#1256](https://github.com/open-mmlab/mmclassification/pull/1256)) - [CI] Update CI to test PyTorch 1.13.0. ([#1260](https://github.com/open-mmlab/mmclassification/pull/1260)) - [Project] Add ACCV workshop 1st Solution. ([#1245](https://github.com/open-mmlab/mmclassification/pull/1245)) - [Project] Add Example project. ([#1254](https://github.com/open-mmlab/mmclassification/pull/1254)) Bug Fixes - [Fix] Fix imports in transforms. ([#1255](https://github.com/open-mmlab/mmclassification/pull/1255)) - [Fix] Fix CAM visualization. ([#1248](https://github.com/open-mmlab/mmclassification/pull/1248)) - [Fix] Fix the requirements and lazy register mmcls models. ([#1275](https://github.com/open-mmlab/mmclassification/pull/1275))
c7ec630
2022-12-30 17:32
下载
v0.25.0
v0.25.0(06/12/2022) Highlights - Support MLU backend. New Features - Support MLU backend. ([#1159](https://github.com/open-mmlab/mmclassification/pull/1159)) - Support Activation Checkpointing for ConvNeXt. ([#1152](https://github.com/open-mmlab/mmclassification/pull/1152)) Improvements - Add `dist_train_arm.sh` for ARM device and update NPU results. ([#1218](https://github.com/open-mmlab/mmclassification/pull/1218)) Bug Fixes - Fix a bug caused `MMClsWandbHook` stuck. ([#1242](https://github.com/open-mmlab/mmclassification/pull/1242)) - Fix the redundant `device_ids` in `tools/test.py`. ([#1215](https://github.com/open-mmlab/mmclassification/pull/1215)) Docs Update - Add version banner and version warning in master docs. ([#1216](https://github.com/open-mmlab/mmclassification/pull/1216)) - Update NPU support doc. ([#1198](https://github.com/open-mmlab/mmclassification/pull/1198)) - Fixed typo in `pytorch2torchscript.md`. ([#1173](https://github.com/open-mmlab/mmclassification/pull/1173)) - Fix typo in `miscellaneous.md`. ([#1137](https://github.com/open-mmlab/mmclassification/pull/1137)) - further detail for the doc for `ClassBalancedDataset`. ([#901](https://github.com/open-mmlab/mmclassification/pull/901))
2495400
2022-12-06 18:25
下载
v1.0.0rc4
v1.0.0rc4(06/12/2022) Highlights - Upgrade API to get pre-defined models of MMClassification. See [#1236](https://github.com/open-mmlab/mmclassification/pull/1236) for more details. - Refactor BEiT backbone and support v1/v2 inference. See [#1144](https://github.com/open-mmlab/mmclassification/pull/1144). New Features - Support getting model from the name defined in the model-index file. ([#1236](https://github.com/open-mmlab/mmclassification/pull/1236)) Improvements - Support evaluate on both EMA and non-EMA models. ([#1204](https://github.com/open-mmlab/mmclassification/pull/1204)) - Refactor BEiT backbone and support v1/v2 inference. ([#1144](https://github.com/open-mmlab/mmclassification/pull/1144)) Bug Fixes - Fix `reparameterize_model.py` doesn't save meta info. ([#1221](https://github.com/open-mmlab/mmclassification/pull/1221)) - Fix dict update in BEiT. ([#1234](https://github.com/open-mmlab/mmclassification/pull/1234)) Docs Update - Update install tutorial. ([#1223](https://github.com/open-mmlab/mmclassification/pull/1223)) - Update MobileNetv2 & MobileNetv3 readme. ([#1222](https://github.com/open-mmlab/mmclassification/pull/1222)) - Add version selection in the banner. ([#1217](https://github.com/open-mmlab/mmclassification/pull/1217))
458ac4c
2022-12-06 18:00
下载
v1.0.0rc3
v1.0.0rc3(21/11/2022) Highlights - Add **Switch Recipe** Hook, Now we can modify training pipeline, mixup and loss settings during training, see [#1101](https://github.com/open-mmlab/mmclassification/pull/1101). - Add **TIMM and HuggingFace** wrappers. Now you can train/use models in TIMM/HuggingFace directly, see [#1102](https://github.com/open-mmlab/mmclassification/pull/1102). - Support **retrieval tasks**, see [#1055](https://github.com/open-mmlab/mmclassification/pull/1055). - Reproduce **mobileone** training accuracy. See [#1191](https://github.com/open-mmlab/mmclassification/pull/1191) New Features - Add checkpoints from EfficientNets NoisyStudent & L2. ([#1122](https://github.com/open-mmlab/mmclassification/pull/1122)) - Migrate CSRA head to 1.x. ([#1177](https://github.com/open-mmlab/mmclassification/pull/1177)) - Support RepLKnet backbone. ([#1129](https://github.com/open-mmlab/mmclassification/pull/1129)) - Add Switch Recipe Hook. ([#1101](https://github.com/open-mmlab/mmclassification/pull/1101)) - Add adan optimizer. ([#1180](https://github.com/open-mmlab/mmclassification/pull/1180)) - Support DaViT. ([#1105](https://github.com/open-mmlab/mmclassification/pull/1105)) - Support Activation Checkpointing for ConvNeXt. ([#1153](https://github.com/open-mmlab/mmclassification/pull/1153)) - Add TIMM and HuggingFace wrappers to build classifiers from them directly. ([#1102](https://github.com/open-mmlab/mmclassification/pull/1102)) - Add reduction for neck ([#978](https://github.com/open-mmlab/mmclassification/pull/978)) - Support HorNet Backbone for dev1.x. ([#1094](https://github.com/open-mmlab/mmclassification/pull/1094)) - Add arcface head. ([#926](https://github.com/open-mmlab/mmclassification/pull/926)) - Add Base Retriever and Image2Image Retriever for retrieval tasks. ([#1055](https://github.com/open-mmlab/mmclassification/pull/1055)) - Support MobileViT backbone. ([#1068](https://github.com/open-mmlab/mmclassification/pull/1068)) Improvements - [Enhance] Enhance ArcFaceClsHead. ([#1181](https://github.com/open-mmlab/mmclassification/pull/1181)) - [Refactor] Refactor to use new fileio API in MMEngine. ([#1176](https://github.com/open-mmlab/mmclassification/pull/1176)) - [Enhance] Reproduce mobileone training accuracy. ([#1191](https://github.com/open-mmlab/mmclassification/pull/1191)) - [Enhance] add deleting params info in swinv2. ([#1142](https://github.com/open-mmlab/mmclassification/pull/1142)) - [Enhance] Add more mobilenetv3 pretrains. ([#1154](https://github.com/open-mmlab/mmclassification/pull/1154)) - [Enhancement] RepVGG for YOLOX-PAI for dev-1.x. ([#1126](https://github.com/open-mmlab/mmclassification/pull/1126)) - [Improve] Speed up data preprocessor. ([#1064](https://github.com/open-mmlab/mmclassification/pull/1064)) Bug Fixes - Fix the torchserve. ([#1143](https://github.com/open-mmlab/mmclassification/pull/1143)) - Fix configs due to api refactor of `num_classes`. ([#1184](https://github.com/open-mmlab/mmclassification/pull/1184)) - Update mmcls2torchserve. ([#1189](https://github.com/open-mmlab/mmclassification/pull/1189)) - Fix for `inference_model` cannot get classes information in checkpoint. ([#1093](https://github.com/open-mmlab/mmclassification/pull/1093)) Docs Update - Add not-found page extension. ([#1207](https://github.com/open-mmlab/mmclassification/pull/1207)) - update visualization doc. ([#1160](https://github.com/open-mmlab/mmclassification/pull/1160)) - Support sort and search the Model Summary table. ([#1100](https://github.com/open-mmlab/mmclassification/pull/1100)) - Improve the ResNet model page. ([#1118](https://github.com/open-mmlab/mmclassification/pull/1118)) - update the readme of convnext. ([#1156](https://github.com/open-mmlab/mmclassification/pull/1156)) - Fix the installation docs link in README. ([#1164](https://github.com/open-mmlab/mmclassification/pull/1164)) - Improve ViT and MobileViT model pages. ([#1155](https://github.com/open-mmlab/mmclassification/pull/1155)) - Improve Swin Doc and Add Tabs enxtation. ([#1145](https://github.com/open-mmlab/mmclassification/pull/1145)) - Add MMEval projects link in README. ([#1162](https://github.com/open-mmlab/mmclassification/pull/1162)) - Add runtime configuration docs. ([#1128](https://github.com/open-mmlab/mmclassification/pull/1128)) - Add custom evaluation docs ([#1130](https://github.com/open-mmlab/mmclassification/pull/1130)) - Add custom pipeline docs. ([#1124](https://github.com/open-mmlab/mmclassification/pull/1124)) - Add MMYOLO projects link in MMCLS1.x. ([#1117](https://github.com/open-mmlab/mmclassification/pull/1117))
13ff394
2022-11-21 18:21
下载
v0.24.1
v0.24.1(31/10/2022) New Features - Support mmcls with NPU backend. ([#1072](https://github.com/open-mmlab/mmclassification/pull/1072)) Bug Fixes - Fix performance issue in convnext DDP train. ([#1098](https://github.com/open-mmlab/mmclassification/pull/1098))
8c63bb5
2022-11-01 14:19
下载
v1.0.0rc2
v1.0.0rc2(12/10/2022) New Features - Support DeiT3. ([#1065](https://github.com/open-mmlab/mmclassification/pull/1065)) Improvements - Update `analyze_results.py` for dev-1.x. ([#1071](https://github.com/open-mmlab/mmclassification/pull/1071)) - Get scores from inference api. ([#1070](https://github.com/open-mmlab/mmclassification/pull/1070)) Bug Fixes - Update requirements. ([#1083](https://github.com/open-mmlab/mmclassification/pull/1083)) Docs Update - Add 1x docs schedule. ([#1015](https://github.com/open-mmlab/mmclassification/pull/1015))
31c67ff
2022-10-12 16:52
下载
v0.24.0
v0.24.0(30/9/2022) Highlights - Support HorNet, EfficientFormerm, SwinTransformer V2 and MViT backbones. - Support Standford Cars dataset. New Features - Support HorNet Backbone. ([#1013](https://github.com/open-mmlab/mmclassification/pull/1013)) - Support EfficientFormer. ([#954](https://github.com/open-mmlab/mmclassification/pull/954)) - Support Stanford Cars dataset. ([#893](https://github.com/open-mmlab/mmclassification/pull/893)) - Support CSRA head. ([#881](https://github.com/open-mmlab/mmclassification/pull/881)) - Support Swin Transform V2. ([#799](https://github.com/open-mmlab/mmclassification/pull/799)) - Support MViT and add checkpoints. ([#924](https://github.com/open-mmlab/mmclassification/pull/924)) Improvements - \[Improve\] replace loop of progressbar in api/test. ([#878](https://github.com/open-mmlab/mmclassification/pull/878)) - \[Enhance\] RepVGG for YOLOX-PAI. ([#1025](https://github.com/open-mmlab/mmclassification/pull/1025)) - \[Enhancement\] Update VAN. ([#1017](https://github.com/open-mmlab/mmclassification/pull/1017)) - \[Refactor\] Re-write `get_sinusoid_encoding` from third-party implementation. ([#965](https://github.com/open-mmlab/mmclassification/pull/965)) - \[Improve\] Upgrade onnxsim to v0.4.0. ([#915](https://github.com/open-mmlab/mmclassification/pull/915)) - \[Improve\] Fixed typo in `RepVGG`. ([#985](https://github.com/open-mmlab/mmclassification/pull/985)) - \[Improve\] Using `train_step` instead of `forward` in PreciseBNHook ([#964](https://github.com/open-mmlab/mmclassification/pull/964)) - \[Improve\] Use `forward_dummy` to calculate FLOPS. ([#953](https://github.com/open-mmlab/mmclassification/pull/953)) Bug Fixes - Fix warning with `torch.meshgrid`. ([#860](https://github.com/open-mmlab/mmclassification/pull/860)) - Add matplotlib minimum version requriments. ([#909](https://github.com/open-mmlab/mmclassification/pull/909)) - val loader should not drop last by default. ([#857](https://github.com/open-mmlab/mmclassification/pull/857)) - Fix config.device bug in toturial. ([#1059](https://github.com/open-mmlab/mmclassification/pull/1059)) - Fix attenstion clamp max params ([#1034](https://github.com/open-mmlab/mmclassification/pull/1034)) - Fix device mismatch in Swin-v2. ([#976](https://github.com/open-mmlab/mmclassification/pull/976)) - Fix the output position of Swin-Transformer. ([#947](https://github.com/open-mmlab/mmclassification/pull/947)) Docs Update - Fix typo in config.md. ([#827](https://github.com/open-mmlab/mmclassification/pull/827)) - Add version for torchvision to avoide error. ([#903](https://github.com/open-mmlab/mmclassification/pull/903)) - Fixed typo for `--out-dir` option of analyze_results.py. ([#898](https://github.com/open-mmlab/mmclassification/pull/898)) - Refine the docstring of RegNet ([#935](https://github.com/open-mmlab/mmclassification/pull/935))
91b85bb
2022-09-30 18:06
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v1.0.0rc1
v1.0.0rc1(30/9/2022) New Features - Support MViT for MMCLS 1.x ([#1023](https://github.com/open-mmlab/mmclassification/pull/1023)) - Add ViT huge architecture. ([#1049](https://github.com/open-mmlab/mmclassification/pull/1049)) - Support EdgeNeXt for dev-1.x. ([#1037](https://github.com/open-mmlab/mmclassification/pull/1037)) - Support Swin Transformer V2 for MMCLS 1.x. ([#1029](https://github.com/open-mmlab/mmclassification/pull/1029)) - Add efficientformer Backbone for MMCls 1.x. ([#1031](https://github.com/open-mmlab/mmclassification/pull/1031)) - Add MobileOne Backbone For MMCls 1.x. ([#1030](https://github.com/open-mmlab/mmclassification/pull/1030)) - Support BEiT Transformer layer. ([#919](https://github.com/open-mmlab/mmclassification/pull/919)) Improvements - \[Refactor\] Fix visualization tools. ([#1045](https://github.com/open-mmlab/mmclassification/pull/1045)) - \[Improve\] Update benchmark scripts ([#1028](https://github.com/open-mmlab/mmclassification/pull/1028)) - \[Improve\] Update tools to enable `pin_memory` and `persistent_workers` by default. ([#1024](https://github.com/open-mmlab/mmclassification/pull/1024)) - \[CI\] Update circle-ci and github workflow. ([#1018](https://github.com/open-mmlab/mmclassification/pull/1018)) Bug Fixes - Fix verify dataset tool in 1.x. ([#1062](https://github.com/open-mmlab/mmclassification/pull/1062)) - Fix `loss_weight` in `LabelSmoothLoss`. ([#1058](https://github.com/open-mmlab/mmclassification/pull/1058)) - Fix the output position of Swin-Transformer. ([#947](https://github.com/open-mmlab/mmclassification/pull/947)) Docs Update - Auto generate model summary table. ([#1010](https://github.com/open-mmlab/mmclassification/pull/1010)) - Refactor new modules tutorial. ([#998](https://github.com/open-mmlab/mmclassification/pull/998))
38bea38
2022-09-30 17:39
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v1.0.0rc0
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.
a009d29
2022-09-01 00:13
下载
v0.23.2
v0.23.2(28/7/2022) New Features - Support MPS device. ([#894](https://github.com/open-mmlab/mmclassification/pull/894)) Bug Fixes - Fix a bug in Albu which caused crashing. ([#918](https://github.com/open-mmlab/mmclassification/pull/918))
71ef7ba
2022-07-28 14:15
下载
v0.23.1
v0.23.1(2/6/2022) New Features - [Feature] Dedicated MMClsWandbHook for MMClassification (Weights and Biases Integration) ([#764](https://github.com/open-mmlab/mmclassification/pull/764)) Improvements - [Refactor] Use mdformat instead of markdownlint to format markdown. ([#844](https://github.com/open-mmlab/mmclassification/pull/844)) Bug Fixes - [Fix] Fix wrong `--local_rank`. Docs Update - [Docs] Update install tutorials. ([#854](https://github.com/open-mmlab/mmclassification/pull/854)) - [Docs] Fix wrong link in README. ([#835](https://github.com/open-mmlab/mmclassification/pull/835))
313d357
2022-06-02 21:22
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