From 2e7f99946b899a7ae4eaec47e87b1a8d5d7cffe4 Mon Sep 17 00:00:00 2001 From: Ma Zerun Date: Thu, 31 Mar 2022 01:36:53 +0800 Subject: [PATCH] Bump version to v0.22.0. (#756) --- README.md | 14 +++++++------- README_zh-CN.md | 18 +++++++++--------- docker/serve/Dockerfile | 2 +- docs/en/changelog.md | 35 +++++++++++++++++++++++++++++++++++ docs/en/install.md | 5 +++-- docs/zh_CN/install.md | 7 ++++--- mmcls/version.py | 2 +- 7 files changed, 60 insertions(+), 23 deletions(-) diff --git a/README.md b/README.md index ecee88a6..ce0b6ec4 100644 --- a/README.md +++ b/README.md @@ -59,6 +59,13 @@ The master branch works with **PyTorch 1.5+**. ## What's new +v0.22.0 was released in 30/3/2022. + +Highlights of the new version: +- Support a series of **CSP Network**, such as CSP-ResNet, CSP-ResNeXt and CSP-DarkNet. +- A new `CustomDataset` class to help you **build dataset of yourself**! +- Support new backbones - **ConvMixer**, **RepMLP** and new dataset - **CUB dataset**. + v0.21.0 was released in 4/3/2022. Highlights of the new version: @@ -66,13 +73,6 @@ Highlights of the new version: - Support **dynamic input shape** for ViT-based algorithms. Now our ViT, DeiT, Swin-Transformer and T2T-ViT support forwarding with any input shape. - Reproduce training results of DeiT. And our DeiT-T and DeiT-S have **higher accuracy** comparing with the official weights. -v0.20.0 was released in 30/1/2022. - -Highlights of the new version: -- Support **K-fold cross-validation**. The tutorial will be released later. -- Support **HRNet**, **ConvNeXt**, **Twins** and **EfficientNet**. -- Support model conversion from PyTorch to **Core ML** by a tool. - Please refer to [changelog.md](docs/en/changelog.md) for more details and other release history. ## Installation diff --git a/README_zh-CN.md b/README_zh-CN.md index cdf9ad4d..8f3c1c93 100644 --- a/README_zh-CN.md +++ b/README_zh-CN.md @@ -57,20 +57,20 @@ MMClassification 是一款基于 PyTorch 的开源图像分类工具箱，是 [O ## 更新日志 +2022/3/30 发布了 v0.22.0 版本 + +新版本亮点： +- 支持了一系列 **CSP Net**，包括 CSP-ResNet，CSP-ResNeXt 和 CSP-DarkNet。 +- 我们提供了一个新的 `CustomDataset` 类，这个类将帮助你轻松使用**自己的数据集**！ +- 支持了新的主干网络 **ConvMixer**、**RepMLP** 和一个新的数据集 **CUB dataset**。 + 2022/3/4 发布了 v0.21.0 版本 新版本亮点： - 支持了 **ResNetV1c** 和 **Wide-ResNet** 两个 ResNet 变种，并提供了预训练模型 -- ViT相关模型支持 **动态输入尺寸**。现在我们的 ViT，DeiT，Swin-Transformer 和 T2T-ViT 支持任意尺寸的输入。 +- ViT 相关模型支持 **动态输入尺寸**。现在我们的 ViT，DeiT，Swin-Transformer 和 T2T-ViT 支持任意尺寸的输入。 - 复现了 DeiT 的训练结果，并且我们的 DeiT-T 和 DeiT-S 拥有比官方权重 **更高的精度**。 -2022/1/30 发布了 v0.20.0 版本 - -新版本亮点： -- 支持 **K 折交叉验证** 工具。相应文档会在后续添加。 -- 支持了 **HRNet**，**ConvNeXt**，**Twins** 以及 **EfficientNet** 四个主干网络，欢迎使用！ -- 支持了从 PyTorch 模型到 Core-ML 模型的转换工具。 - 发布历史和更新细节请参考 [更新日志](docs/en/changelog.md) ## 安装 @@ -91,7 +91,7 @@ pip3 install -e . ## 基础教程 -请参考 [基础教程](https://mmclassification.readthedocs.io/zh_CN/latest/getting_started.html) 来了解 MMClassification 的基本使用。MMClassification 也提供了其他更详细的教程: +请参考 [基础教程](https://mmclassification.readthedocs.io/zh_CN/latest/getting_started.html) 来了解 MMClassification 的基本使用。MMClassification 也提供了其他更详细的教程： - [如何编写配置文件](https://mmclassification.readthedocs.io/zh_CN/latest/tutorials/config.html) - [如何微调模型](https://mmclassification.readthedocs.io/zh_CN/latest/tutorials/finetune.html) diff --git a/docker/serve/Dockerfile b/docker/serve/Dockerfile index 1fb97736..f301726b 100644 --- a/docker/serve/Dockerfile +++ b/docker/serve/Dockerfile @@ -4,7 +4,7 @@ ARG CUDNN="7" FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel ARG MMCV="1.4.2" -ARG MMCLS="0.21.0" +ARG MMCLS="0.22.0" ENV PYTHONUNBUFFERED TRUE diff --git a/docs/en/changelog.md b/docs/en/changelog.md index 00a01012..dfd15301 100644 --- a/docs/en/changelog.md +++ b/docs/en/changelog.md @@ -1,5 +1,40 @@ # Changelog +## v0.22.0(30/3/2022) + +### Highlights + +- Support a series of CSP Network, such as CSP-ResNet, CSP-ResNeXt and CSP-DarkNet. +- A new `CustomDataset` class to help you build dataset of yourself! +- Support ConvMixer, RepMLP and new dataset - CUB dataset. + +### New Features + +- [Feature] Add CSPNet and backbone and checkpoints ([#735](https://github.com/open-mmlab/mmclassification/pull/735)) +- [Feature] Add `CustomDataset`. ([#738](https://github.com/open-mmlab/mmclassification/pull/738)) +- [Feature] Add diff seeds to diff ranks. ([#744](https://github.com/open-mmlab/mmclassification/pull/744)) +- [Feature] Support ConvMixer. ([#716](https://github.com/open-mmlab/mmclassification/pull/716)) +- [Feature] Our `dist_train` & `dist_test` tools support distributed training on multiple machines. ([#734](https://github.com/open-mmlab/mmclassification/pull/734)) +- [Feature] Add RepMLP backbone and checkpoints. ([#709](https://github.com/open-mmlab/mmclassification/pull/709)) +- [Feature] Support CUB dataset. ([#703](https://github.com/open-mmlab/mmclassification/pull/703)) +- [Feature] Support ResizeMix. ([#676](https://github.com/open-mmlab/mmclassification/pull/676)) + + +### Improvements + +- [Enhance] Use `--a-b` instead of `--a_b` in arguments. ([#754](https://github.com/open-mmlab/mmclassification/pull/754)) +- [Enhance] Add `get_cat_ids` and `get_gt_labels` to KFoldDataset. ([#721](https://github.com/open-mmlab/mmclassification/pull/721)) +- [Enhance] Set torch seed in `worker_init_fn`. ([#733](https://github.com/open-mmlab/mmclassification/pull/733)) + +### Bug Fixes + +- [Fix] Fix the discontiguous output feature map of ConvNeXt. ([#743](https://github.com/open-mmlab/mmclassification/pull/743)) + +### Docs Update + +- [Docs] Add brief installation steps in README for copy&paste. ([#755](https://github.com/open-mmlab/mmclassification/pull/755)) +- [Docs] fix logo url link from mmocr to mmcls. ([#732](https://github.com/open-mmlab/mmclassification/pull/732)) + ## v0.21.0(04/03/2022) ### Highlights diff --git a/docs/en/install.md b/docs/en/install.md index 2d068049..d84839b5 100644 --- a/docs/en/install.md +++ b/docs/en/install.md @@ -10,8 +10,9 @@ The compatible MMClassification and MMCV versions are as below. Please install t | MMClassification version | MMCV version | |:------------------------:|:---------------------:| -| dev | mmcv>=1.4.6, <=1.5.0 | -| 0.21.0 (master) | mmcv>=1.4.2, <=1.5.0 | +| dev | mmcv>=1.4.8, <=1.5.0 | +| 0.22.0 (master) | mmcv>=1.4.2, <=1.5.0 | +| 0.21.0 | mmcv>=1.4.2, <=1.5.0 | | 0.20.1 | mmcv>=1.4.2, <=1.5.0 | | 0.19.0 | mmcv>=1.3.16, <=1.5.0 | | 0.18.0 | mmcv>=1.3.16, <=1.5.0 | diff --git a/docs/zh_CN/install.md b/docs/zh_CN/install.md index 350e0131..a254643b 100644 --- a/docs/zh_CN/install.md +++ b/docs/zh_CN/install.md @@ -10,8 +10,9 @@ MMClassification 和 MMCV 的适配关系如下，请安装正确版本的 MMCV | MMClassification 版本 | MMCV 版本 | |:---------------------:|:---------------------:| -| dev | mmcv>=1.4.6, <=1.5.0 | -| 0.21.0 (master)| mmcv>=1.4.2, <=1.5.0 | +| dev | mmcv>=1.4.8, <=1.5.0 | +| 0.22.0 (master)| mmcv>=1.4.2, <=1.5.0 | +| 0.21.0 | mmcv>=1.4.2, <=1.5.0 | | 0.20.1 | mmcv>=1.4.2, <=1.5.0 | | 0.19.0 | mmcv>=1.3.16, <=1.5.0 | | 0.18.0 | mmcv>=1.3.16, <=1.5.0 | @@ -109,7 +110,7 @@ MMClassification 和 MMCV 的适配关系如下，请安装正确版本的 MMCV cd mmclassification ``` -2. [可选] 签出到 `dev` 分支 +2. 【可选】 签出到 `dev` 分支 ```shell git checkout dev diff --git a/mmcls/version.py b/mmcls/version.py index dbe8f2c8..33522c31 100644 --- a/mmcls/version.py +++ b/mmcls/version.py @@ -1,6 +1,6 @@ # Copyright (c) OpenMMLab. All rights reserved -__version__ = '0.21.0' +__version__ = '0.22.0' def parse_version_info(version_str):