Ma Zerun
GitHub
parent
da669ec1d7
commit
3ff80f5047
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@ -18,7 +18,7 @@ RUN apt-get update && apt-get install -y ffmpeg libsm6 libxext6 git ninja-build
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# Install MMCV
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RUN pip install openmim
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RUN mim install mmengine "mmcv>=2.0rc0"
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RUN mim install mmengine "mmcv>=2.0.0"
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# Install MMClassification
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RUN conda clean --all
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@ -7,9 +7,9 @@ FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel
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RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub 32
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RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
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ARG MMENGINE="0.3.2"
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ARG MMCV="2.0.0rc1"
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ARG MMCLS="1.0.0rc4"
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ARG MMENGINE="0.7.1"
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ARG MMCV="2.0.0"
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ARG MMCLS="1.0.0rc6"
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ENV PYTHONUNBUFFERED TRUE
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@ -1,5 +1,50 @@
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# Changelog
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## v1.0.0rc6(06/04/2023)
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### Highlights
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- Support OOD datasets.
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- Support confusion matrix calculation and plot.
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- Support LeViT, XCiT, ViG and ConvNeXt-V2 backbone.
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### New Features
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- Support Out-of-Distribution datasets like ImageNet-A,R,S,C. ([#1342](https://github.com/open-mmlab/mmclassification/pull/1342))
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- Support XCiT Backbone. ([#1305](https://github.com/open-mmlab/mmclassification/pull/1305))
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- Support calculate confusion matrix and plot it. ([#1287](https://github.com/open-mmlab/mmclassification/pull/1287))
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- Support RetrieverRecall metric & Add ArcFace config ([#1316](https://github.com/open-mmlab/mmclassification/pull/1316))
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- Add `ImageClassificationInferencer`. ([#1261](https://github.com/open-mmlab/mmclassification/pull/1261))
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- Support InShop Dataset (Image Retrieval). ([#1019](https://github.com/open-mmlab/mmclassification/pull/1019))
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- Support LeViT backbone. ([#1238](https://github.com/open-mmlab/mmclassification/pull/1238))
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- Support VIG Backbone. ([#1304](https://github.com/open-mmlab/mmclassification/pull/1304))
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- Support ConvNeXt-V2 backbone. ([#1294](https://github.com/open-mmlab/mmclassification/pull/1294))
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### Improvements
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- [Enhance] Add stochastic depth decay rule in resnet. ([#1363](https://github.com/open-mmlab/mmclassification/pull/1363))
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- [Refactor] Update analysis tools and documentations. ([#1359](https://github.com/open-mmlab/mmclassification/pull/1359))
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- [Refactor] Unify the `--out` and `--dump` in `tools/test.py`. ([#1307](https://github.com/open-mmlab/mmclassification/pull/1307))
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- [Enhance] Enable to toggle whether Gem Pooling is trainable or not. ([#1246](https://github.com/open-mmlab/mmclassification/pull/1246))
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- [Improve] Update registries of mmcls. ([#1306](https://github.com/open-mmlab/mmclassification/pull/1306))
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- [Tool] Add metafile fill and validation tools. ([#1297](https://github.com/open-mmlab/mmclassification/pull/1297))
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- [Improve] Remove useless EfficientnetV2 config files. ([#1300](https://github.com/open-mmlab/mmclassification/pull/1300))
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### Bug Fixes
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- Fix precise bn hook ([#1386](https://github.com/open-mmlab/mmclassification/pull/1386))
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- Fix acc evalustion wait for long ([#1430](https://github.com/open-mmlab/mmclassification/pull/1430))
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- Fix retrieval multi gpu bug ([#1319](https://github.com/open-mmlab/mmclassification/pull/1319))
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- Fix error repvgg-deploy base config path. ([#1357](https://github.com/open-mmlab/mmclassification/pull/1357))
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- Fix bug in test tools. ([#1309](https://github.com/open-mmlab/mmclassification/pull/1309))
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### Docs Update
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- Update Readme ([#1442](https://github.com/open-mmlab/mmclassification/pull/1442))
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- Add NPU support page. ([#1437](https://github.com/open-mmlab/mmclassification/pull/1437))
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- Translate some tools tutorials to Chinese. ([#1321](https://github.com/open-mmlab/mmclassification/pull/1321))
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- Add Chinese translation for runtime.md. ([#1313](https://github.com/open-mmlab/mmclassification/pull/1313))
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## v1.0.0rc5(30/12/2022)
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### Highlights
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@ -6,11 +6,11 @@ from mmengine.utils import digit_version
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from .apis import * # noqa: F401, F403
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from .version import __version__
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mmcv_minimum_version = '2.0.0rc1'
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mmcv_maximum_version = '2.0.0'
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mmcv_minimum_version = '2.0.0rc4'
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mmcv_maximum_version = '2.1.0'
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mmcv_version = digit_version(mmcv.__version__)
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mmengine_minimum_version = '0.5.0'
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mmengine_minimum_version = '0.7.1'
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mmengine_maximum_version = '1.0.0'
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mmengine_version = digit_version(mmengine.__version__)
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@ -1,6 +1,6 @@
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# Copyright (c) OpenMMLab. All rights reserved
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__version__ = '1.0.0rc5'
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__version__ = '1.0.0rc6'
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def parse_version_info(version_str):
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@ -1,2 +1,2 @@
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mmcv>=2.0.0rc1,<=2.0.0
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mmengine>=0.4.0,<1.0.0
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mmcv>=2.0.0rc4,<=2.1.0
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mmengine>=0.7.1,<1.0.0
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