From e4c1865a822dd9a699f4b22aff6a093f62a11250 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E8=B0=A2=E6=98=95=E8=BE=B0?= Date: Tue, 4 Jul 2023 11:11:30 +0800 Subject: [PATCH] Bump1.1 (#3140) Co-authored-by: CSH <40987381+csatsurnh@users.noreply.github.com> --- README.md | 9 ++- README_zh-CN.md | 3 +- configs/_base_/models/fpn_poolformer_s12.py | 6 +- configs/convnext/README.md | 2 +- docker/serve/Dockerfile | 2 +- docs/en/get_started.md | 2 +- docs/en/notes/changelog.md | 86 +++++++++++++++++++++ docs/en/notes/faq.md | 3 +- docs/zh_cn/get_started.md | 2 +- docs/zh_cn/notes/faq.md | 3 +- mmseg/version.py | 2 +- 11 files changed, 105 insertions(+), 15 deletions(-) diff --git a/README.md b/README.md index bc31e6fc83..42b99daa5f 100644 --- a/README.md +++ b/README.md @@ -88,12 +88,12 @@ MMSegmentation v1.x brings remarkable improvements over the 0.x release, offerin ## What's New -v1.0.0 was released on 04/06/2023. +v1.1.0 was released on 07/04/2023. Please refer to [changelog.md](docs/en/notes/changelog.md) for details and release history. -- Add Mapillary Vistas Datasets support to MMSegmentation Core Package ([#2576](https://github.com/open-mmlab/mmsegmentation/pull/2576)) -- Support PIDNet ([#2609](https://github.com/open-mmlab/mmsegmentation/pull/2609)) -- Support SegNeXt ([#2654](https://github.com/open-mmlab/mmsegmentation/pull/2654)) +- Support 24 medical image datasets in [projects](./projects/medical/). +- Add GDAL backend and support remote sensing datasets [LEVIR-CD](https://github.com/open-mmlab/mmsegmentation/pull/2903). +- Support [DDRNet](https://github.com/open-mmlab/mmsegmentation/pull/2855). ## Installation @@ -252,6 +252,7 @@ Results and models are available in the [model zoo](docs/en/model_zoo.md). - [x] [Vaihingen](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#isprs-vaihingen) - [x] [iSAID](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#isaid) - [x] [Mapillary Vistas](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#mapillary-vistas-datasets) +- [x] [LEVIR-CD](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#levir-cd) diff --git a/README_zh-CN.md b/README_zh-CN.md index 684bae0c72..587fdcf042 100644 --- a/README_zh-CN.md +++ b/README_zh-CN.md @@ -87,7 +87,7 @@ MMSegmentation v1.x 在 0.x 版本的基础上有了显著的提升，提供了 ## 更新日志 -最新版本 v1.0.0 在 2023.04.06 发布。 +最新版本 v1.1.0 在 2023.07.04 发布。 如果想了解更多版本更新细节和历史信息，请阅读[更新日志](docs/en/notes/changelog.md)。 ## 安装 @@ -246,6 +246,7 @@ MMSegmentation v1.x 在 0.x 版本的基础上有了显著的提升，提供了 - [x] [Vaihingen](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#isprs-vaihingen) - [x] [iSAID](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/zh_cn/dataset_prepare.md#isaid) - [x] [Mapillary Vistas](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#mapillary-vistas-datasets) +- [x] [LEVIR-CD](https://github.com/open-mmlab/mmsegmentation/blob/main/docs/en/user_guides/2_dataset_prepare.md#levir-cd) diff --git a/configs/_base_/models/fpn_poolformer_s12.py b/configs/_base_/models/fpn_poolformer_s12.py index ee5f08c6d0..086c804837 100644 --- a/configs/_base_/models/fpn_poolformer_s12.py +++ b/configs/_base_/models/fpn_poolformer_s12.py @@ -1,9 +1,9 @@ # model settings norm_cfg = dict(type='SyncBN', requires_grad=True) checkpoint_file = 'https://download.openmmlab.com/mmclassification/v0/poolformer/poolformer-s12_3rdparty_32xb128_in1k_20220414-f8d83051.pth' # noqa -# TODO: delete custom_imports after mmcls supports auto import -# please install mmcls>=1.0 -# import mmcls.models to trigger register_module in mmcls +# TODO: delete custom_imports after mmpretrain supports auto import +# please install mmpretrain >= 1.0.0rc7 +# import mmpretrain.models to trigger register_module in mmpretrain custom_imports = dict( imports=['mmpretrain.models'], allow_failed_imports=False) data_preprocessor = dict( diff --git a/configs/convnext/README.md b/configs/convnext/README.md index cedf467557..d78fe6ee1b 100644 --- a/configs/convnext/README.md +++ b/configs/convnext/README.md @@ -27,7 +27,7 @@ The "Roaring 20s" of visual recognition began with the introduction of Vision Tr - ConvNeXt backbone needs to install [MMClassification](https://github.com/open-mmlab/mmclassification) first, which has abundant backbones for downstream tasks. ```shell -pip install mmcls>=0.20.1 +pip install mmpretrain>=1.0.0rc7 ``` ### Pre-trained Models diff --git a/docker/serve/Dockerfile b/docker/serve/Dockerfile index cc61143f6c..b962c0079b 100644 --- a/docker/serve/Dockerfile +++ b/docker/serve/Dockerfile @@ -4,7 +4,7 @@ ARG CUDNN="8" FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel ARG MMCV="2.0.0" -ARG MMSEG="1.0.0" +ARG MMSEG="1.1.0" ENV PYTHONUNBUFFERED TRUE diff --git a/docs/en/get_started.md b/docs/en/get_started.md index 2f1764f7fb..5c6033d549 100644 --- a/docs/en/get_started.md +++ b/docs/en/get_started.md @@ -4,7 +4,7 @@ In this section we demonstrate how to prepare an environment with PyTorch. -MMSegmentation works on Linux, Windows and macOS. It requires Python 3.6+, CUDA 9.2+ and PyTorch 1.5+. +MMSegmentation works on Linux, Windows and macOS. It requires Python 3.7+, CUDA 10.2+ and PyTorch 1.8+. **Note:** If you are experienced with PyTorch and have already installed it, just skip this part and jump to the [next section](##installation). Otherwise, you can follow these steps for the preparation. diff --git a/docs/en/notes/changelog.md b/docs/en/notes/changelog.md index 729bb8ce19..663241fd84 100644 --- a/docs/en/notes/changelog.md +++ b/docs/en/notes/changelog.md @@ -1,5 +1,91 @@ # Changelog of v1.x +## v1.1.0(06/28/2023) + +## What's Changed + +### Features + +- Support albu transform ([#2943](https://github.com/open-mmlab/mmsegmentation/pull/2943)) +- Support DDRNet ([#2855](https://github.com/open-mmlab/mmsegmentation/pull/2855)) +- Add GDAL backend and Support LEVIR-CD Dataset ([#2903](https://github.com/open-mmlab/mmsegmentation/pull/2903)) +- Support DSDL Dataset ([#2925](https://github.com/open-mmlab/mmsegmentation/pull/2925)) +- huasdorff distance loss ([#2820](https://github.com/open-mmlab/mmsegmentation/pull/2820)) + +### New Projects + +- Support SAM inferencer ([#2897](https://github.com/open-mmlab/mmsegmentation/pull/2897)) +- Added a supported for Visual Attention Network (VAN) ([#2987](https://github.com/open-mmlab/mmsegmentation/pull/2987)) +- add GID dataset ([#3038](https://github.com/open-mmlab/mmsegmentation/pull/3038)) +- add Medical semantic seg dataset: Bactteria ([#2568](https://github.com/open-mmlab/mmsegmentation/pull/2568)) +- add Medical semantic seg dataset: Vampire ([#2633](https://github.com/open-mmlab/mmsegmentation/pull/2633)) +- add Medical semantic seg dataset: Ravir ([#2635](https://github.com/open-mmlab/mmsegmentation/pull/2635)) +- add Medical semantic seg dataset: Cranium ([#2675](https://github.com/open-mmlab/mmsegmentation/pull/2675)) +- add Medical semantic seg dataset: bccs ([#2861](https://github.com/open-mmlab/mmsegmentation/pull/2861)) +- add Medical semantic seg dataset: Gamma Task3 dataset ([#2695](https://github.com/open-mmlab/mmsegmentation/pull/2695)) +- add Medical semantic seg dataset: consep ([#2724](https://github.com/open-mmlab/mmsegmentation/pull/2724)) +- add Medical semantic seg dataset: breast_cancer_cell_seg dataset ([#2726](https://github.com/open-mmlab/mmsegmentation/pull/2726)) +- add Medical semantic seg dataset: chest_image_pneum dataset ([#2727](https://github.com/open-mmlab/mmsegmentation/pull/2727)) +- add Medical semantic seg dataset: conic2022 ([#2725](https://github.com/open-mmlab/mmsegmentation/pull/2725)) +- add Medical semantic seg dataset: dr_hagis ([#2729](https://github.com/open-mmlab/mmsegmentation/pull/2729)) +- add Medical semantic seg dataset: orvs ([#2728](https://github.com/open-mmlab/mmsegmentation/pull/2728)) +- add Medical semantic seg dataset: ISIC-2016 Task1 ([#2708](https://github.com/open-mmlab/mmsegmentation/pull/2708)) +- add Medical semantic seg dataset: ISIC-2017 Task1 ([#2709](https://github.com/open-mmlab/mmsegmentation/pull/2709)) +- add Medical semantic seg dataset: Kvasir seg ([#2677](https://github.com/open-mmlab/mmsegmentation/pull/2677)) +- add Medical semantic seg dataset: Kvasir seg aliyun ([#2678](https://github.com/open-mmlab/mmsegmentation/pull/2678)) +- add Medical semantic seg dataset: Rite ([#2680](https://github.com/open-mmlab/mmsegmentation/pull/2680)) +- add Medical semantic seg dataset: Fusc2021 ([#2682](https://github.com/open-mmlab/mmsegmentation/pull/2682)) +- add Medical semantic seg dataset: 2pm vessel ([#2685](https://github.com/open-mmlab/mmsegmentation/pull/2685)) +- add Medical semantic seg dataset: Pcam ([#2684](https://github.com/open-mmlab/mmsegmentation/pull/2684)) +- add Medical semantic seg dataset: Pannuke ([#2683](https://github.com/open-mmlab/mmsegmentation/pull/2683)) +- add Medical semantic seg dataset: Covid 19 ct cxr ([#2688](https://github.com/open-mmlab/mmsegmentation/pull/2688)) +- add Medical semantic seg dataset: Crass ([#2690](https://github.com/open-mmlab/mmsegmentation/pull/2690)) +- add Medical semantic seg dataset: Chest x ray images with pneumothorax masks ([#2687](https://github.com/open-mmlab/mmsegmentation/pull/2687)) + +### Enhancement + +- Robust mapping from image path to seg map path ([#3091](https://github.com/open-mmlab/mmsegmentation/pull/3091)) +- Change assertion logic inference cfg.model.test_cfg ([#3012](https://github.com/open-mmlab/mmsegmentation/pull/3012)) +- Refactor dice loss ([#3002](https://github.com/open-mmlab/mmsegmentation/pull/3002)) +- Update Dockerfile libgl1-mesa-dev ([#3095](https://github.com/open-mmlab/mmsegmentation/pull/3095)) +- Prevent passed `ann_file` from silently failing to load ([#2966](https://github.com/open-mmlab/mmsegmentation/pull/2966)) +- Update the translation of models documentation ([#2833](https://github.com/open-mmlab/mmsegmentation/pull/2833)) +- Add docs contents at README.md ([#3083](https://github.com/open-mmlab/mmsegmentation/pull/3083)) +- Enhance swin pretrained model loading ([#3097](https://github.com/open-mmlab/mmsegmentation/pull/3097)) + +### Bug Fixes + +- Handle case where device is neither CPU nor CUDA in HamHead ([#2868](https://github.com/open-mmlab/mmsegmentation/pull/2868)) +- Fix bugs when out_channels==1 ([#2911](https://github.com/open-mmlab/mmsegmentation/pull/2911)) +- Fix binary C=1 focal loss & dataset fileio ([#2935](https://github.com/open-mmlab/mmsegmentation/pull/2935)) +- Fix isaid dataset pre-processing tool ([#3010](https://github.com/open-mmlab/mmsegmentation/pull/3010)) +- Fix bug cannot use both '--tta' and '--out' while testing ([#3067](https://github.com/open-mmlab/mmsegmentation/pull/3067)) +- Fix inferencer ut ([#3117](https://github.com/open-mmlab/mmsegmentation/pull/3117)) +- Fix document ([#2863](https://github.com/open-mmlab/mmsegmentation/pull/2863), [#2896](https://github.com/open-mmlab/mmsegmentation/pull/2896), [#2919](https://github.com/open-mmlab/mmsegmentation/pull/2919), [#2951](https://github.com/open-mmlab/mmsegmentation/pull/2951), [#2970](https://github.com/open-mmlab/mmsegmentation/pull/2970), [#2961](https://github.com/open-mmlab/mmsegmentation/pull/2961), [#3042](https://github.com/open-mmlab/mmsegmentation/pull/3042), ) +- Fix squeeze error when N=1 and C=1 ([#2933](https://github.com/open-mmlab/mmsegmentation/pull/2933)) + +## New Contributors + +- @liu-mengyang made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2896 +- @likyoo made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2911 +- @1qh made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2902 +- @JoshuaChou2018 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2951 +- @jts250 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2833 +- @MGAMZ made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2970 +- @tianbinli made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2568 +- @Provable0816 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2633 +- @Zoulinx made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2903 +- @wufan-tb made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2925 +- @haruishi43 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2966 +- @Masaaki-75 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2675 +- @tang576225574 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2987 +- @Kedreamix made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/3010 +- @nightrain01 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/3067 +- @shigengtian made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/3095 +- @SheffieldCao made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/3097 +- @wangruohui made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/3091 +- @LHamnett made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/3012 + ## v1.0.0(04/06/2023) ### Highlights diff --git a/docs/en/notes/faq.md b/docs/en/notes/faq.md index 018c06cfbd..8401d7457c 100644 --- a/docs/en/notes/faq.md +++ b/docs/en/notes/faq.md @@ -9,7 +9,8 @@ The compatible MMSegmentation, MMCV and MMEngine versions are as below. Please i | MMSegmentation version | MMCV version | MMEngine version | MMClassification (optional) version | MMDetection (optional) version | | :--------------------: | :----------------------------: | :---------------: | :---------------------------------: | :----------------------------: | | dev-1.x branch | mmcv >= 2.0.0 | MMEngine >= 0.7.4 | mmpretrain>=1.0.0rc7 | mmdet >= 3.0.0 | -| main branch | mmcv >= 2.0.0rc4 | MMEngine >= 0.7.1 | mmcls==1.0.0rc6 | mmdet >= 3.0.0 | +| main branch | mmcv >= 2.0.0 | MMEngine >= 0.7.4 | mmpretrain>=1.0.0rc7 | mmdet >= 3.0.0 | +| 1.1.0 | mmcv >= 2.0.0 | MMEngine >= 0.7.4 | mmpretrain>=1.0.0rc7 | mmdet >= 3.0.0 | | 1.0.0 | mmcv >= 2.0.0rc4 | MMEngine >= 0.7.1 | mmcls==1.0.0rc6 | mmdet >= 3.0.0 | | 1.0.0rc6 | mmcv >= 2.0.0rc4 | MMEngine >= 0.5.0 | mmcls>=1.0.0rc0 | mmdet >= 3.0.0rc6 | | 1.0.0rc5 | mmcv >= 2.0.0rc4 | MMEngine >= 0.2.0 | mmcls>=1.0.0rc0 | mmdet>=3.0.0rc6 | diff --git a/docs/zh_cn/get_started.md b/docs/zh_cn/get_started.md index 5a33a48857..b92ab33490 100644 --- a/docs/zh_cn/get_started.md +++ b/docs/zh_cn/get_started.md @@ -4,7 +4,7 @@ 本教程中，我们将会演示如何使用 PyTorch 准备环境。 -MMSegmentation 可以在 Linux, Windows 和 macOS 系统上运行，并且需要安装 Python 3.6+, CUDA 9.2+ 和 PyTorch 1.5+ +MMSegmentation 可以在 Linux, Windows 和 macOS 系统上运行，并且需要安装 Python 3.7+, CUDA 10.2+ 和 PyTorch 1.8+ **注意:** 如果您已经安装了 PyTorch, 可以跳过该部分，直接到[下一小节](##安装)。否则，您可以按照以下步骤操作。 diff --git a/docs/zh_cn/notes/faq.md b/docs/zh_cn/notes/faq.md index 353bfd2489..83bcb22e42 100644 --- a/docs/zh_cn/notes/faq.md +++ b/docs/zh_cn/notes/faq.md @@ -9,7 +9,8 @@ | MMSegmentation version | MMCV version | MMEngine version | MMClassification (optional) version | MMDetection (optional) version | | :--------------------: | :----------------------------: | :---------------: | :---------------------------------: | :----------------------------: | | dev-1.x branch | mmcv >= 2.0.0 | MMEngine >= 0.7.4 | mmpretrain>=1.0.0rc7 | mmdet >= 3.0.0 | -| main branch | mmcv >= 2.0.0rc4 | MMEngine >= 0.7.1 | mmcls==1.0.0rc6 | mmdet >= 3.0.0 | +| main branch | mmcv >= 2.0.0 | MMEngine >= 0.7.4 | mmpretrain>=1.0.0rc7 | mmdet >= 3.0.0 | +| 1.1.0 | mmcv >= 2.0.0 | MMEngine >= 0.7.4 | mmpretrain>=1.0.0rc7 | mmdet >= 3.0.0 | | 1.0.0 | mmcv >= 2.0.0rc4 | MMEngine >= 0.7.1 | mmcls==1.0.0rc6 | mmdet >= 3.0.0 | | 1.0.0rc6 | mmcv >= 2.0.0rc4 | MMEngine >= 0.5.0 | mmcls>=1.0.0rc0 | mmdet >= 3.0.0rc6 | | 1.0.0rc5 | mmcv >= 2.0.0rc4 | MMEngine >= 0.2.0 | mmcls>=1.0.0rc0 | mmdet>=3.0.0rc6 | diff --git a/mmseg/version.py b/mmseg/version.py index 748e4cb495..3a632a31e8 100644 --- a/mmseg/version.py +++ b/mmseg/version.py @@ -1,6 +1,6 @@ # Copyright (c) Open-MMLab. All rights reserved. -__version__ = '1.0.0' +__version__ = '1.1.0' def parse_version_info(version_str):