Bump version to 1.0.0rc6 (#1763)

* Bump version to 1.0.0rc6 * fix * update changelog * fix * fix
2023-03-07 20:22:54 +08:00 · 2023-03-07 20:22:54 +08:00 · 45a8d89fb9
parent d56155c82d
commit 45a8d89fb9
6 changed files with 121 additions and 29 deletions
--- a/README.md
+++ b/README.md
@ -54,6 +54,24 @@ English | [简体中文](README_zh-CN.md)
    <img src="https://user-images.githubusercontent.com/25839884/218346691-ceb2116a-465a-40af-8424-9f30d2348ca9.png" width="3%" alt="" /></a>
 </div>

+## Latest Updates
+
+**The default branch has been switched to `1.x` from `main`, and we encourage
+users to migrate to the latest version, though it comes with some cost. Please refer to [Migration Guide](https://mmocr.readthedocs.io/en/dev-1.x/migration/overview.html) for more
+details.**
+
+v1.0.0rc6 was released in 2023-03-07.
+
+1. Two new models, ABCNet v2 (inference only) and SPTS are added to `projects/` folder.
+2. Announcing `Inferencer`, a unified inference interface in OpenMMLab for everyone's easy access and quick inference with all the pre-trained weights. [Docs](https://mmocr.readthedocs.io/en/dev-1.x/user_guides/inference.html)
+3. Users can use test-time augmentation for text recognition tasks. [Docs](https://mmocr.readthedocs.io/en/dev-1.x/user_guides/train_test.html#test-time-augmentation)
+4. Support [batch augmentation](https://openaccess.thecvf.com/content_CVPR_2020/papers/Hoffer_Augment_Your_Batch_Improving_Generalization_Through_Instance_Repetition_CVPR_2020_paper.pdf) through [`BatchAugSampler`](https://github.com/open-mmlab/mmocr/pull/1757), which is a technique used in SPTS.
+5. Dataset Preparer has been refactored to allow more flexible configurations. Besides, users are now able to prepare text recognition datasets in LMDB formats. [Docs](https://mmocr.readthedocs.io/en/dev-1.x/user_guides/data_prepare/dataset_preparer.html#lmdb-format)
+6. Some textspotting datasets have been revised to enhance the correctness and consistency with the common practice.
+7. Potential spurious warnings from `shapely` have been eliminated.
+
+Read [Changelog](https://mmocr.readthedocs.io/en/dev-1.x/notes/changelog.html) for more details!
+
 ## Introduction

 MMOCR is an open-source toolbox based on PyTorch and mmdetection for text detection, text recognition, and the corresponding downstream tasks including key information extraction. It is part of the [OpenMMLab](https://openmmlab.com/) project.
@ -82,21 +100,6 @@ The main branch works with **PyTorch 1.6+**.

  The toolbox provides a comprehensive set of utilities which can help users assess the performance of models. It includes visualizers which allow visualization of images, ground truths as well as predicted bounding boxes, and a validation tool for evaluating checkpoints during training.  It also includes data converters to demonstrate how to convert your own data to the annotation files which the toolbox supports.

-## Latest Updates
-
-**The default branch has been switched to `1.x` from `main`, and we encourage
-users to migrate to the latest version, though it comes with some cost. Please refer to [Migration Guide](https://mmocr.readthedocs.io/en/dev-1.x/migration/overview.html) for more
-details.**
-
-v1.0.0rc5 was released in 2023-01-06.
-
-1. Two models, Aster and SVTR, are added to our model zoo. The full implementation of ABCNet is also available now.
-2. Dataset Preparer supports 5 more datasets: CocoTextV2, FUNSD, TextOCR, NAF, SROIE.
-3. We have 4 more text recognition transforms, and two more helper transforms.
-4. The transform, `FixInvalidPolygon`, is getting smarter at dealing with invalid polygons, and now capable of handling more weird annotations. As a result, a complete training cycle on TotalText dataset can be performed bug-free. The weights of DBNet and FCENet pretrained on TotalText are also released.
-
-Read [Changelog](https://mmocr.readthedocs.io/en/dev-1.x/notes/changelog.html) for more details!
-
 ## What's New in MMOCR 1.0

 1. **New engines**. MMOCR 1.x is based on [MMEngine](https://github.com/open-mmlab/mmengine), which provides a general and powerful runner that allows more flexible customizations and significantly simplifies the entrypoints of high-level interfaces.
--- a/README_zh-CN.md
+++ b/README_zh-CN.md
@ -41,6 +41,28 @@

 </div>

+## 近期更新
+
+**默认分支已经从 `main` 切换到 `1.x`。我们鼓励用户迁移到最新版本，请参考 [迁移指南](https://mmocr.readthedocs.io/zh_CN/dev-1.x/migration/overview.html) 以了解更多细节。**
+
+最新的版本 v1.0.0rc6 于 2023-03-07 发布。
+
+1. 在 `projects/` 目录中新增了 ABCNet v2 (仅支持推理) 和 SPTS 模型；
+
+2. 新增统一推理接口 `Inferencer`，用户可以方便直接地进行各任务的推理。[文档](https://mmocr.readthedocs.io/zh_CN/dev-1.x/user_guides/inference.html)
+
+3. 支持了文本识别任务的测试时数据增强。[文档](https://mmocr.readthedocs.io/zh_CN/dev-1.x/user_guides/train_test.html#id15)
+
+4. 通过 [`BatchAugSampler`](https://github.com/open-mmlab/mmocr/pull/1757) 支持了 [batch augmentation](https://openaccess.thecvf.com/content_CVPR_2020/papers/Hoffer_Augment_Your_Batch_Improving_Generalization_Through_Instance_Repetition_CVPR_2020_paper.pdf) ，这是 SPTS 中使用的一种技巧。
+
+5. 重构了 Dataset Preparer ，用户现在可以更灵活地配置数据集的预处理流程。除此之外，用户现在也可以将文本识别数据集转换为 LMDB 格式。[文档](https://mmocr.readthedocs.io/zh_CN/dev-1.x/user_guides/data_prepare/dataset_preparer.html#lmdb)
+
+6. 修正了一些端到端数据集的标注，保证了数据集的正确性及与常见实践的一致性。
+
+7. 减少了 `shapely` 中可能出现的一些错误警告。
+
+阅读[更新日志](https://mmocr.readthedocs.io/zh_CN/dev-1.x/notes/changelog.html)以获取更多信息。
+
 ## 简介

 MMOCR 是基于 PyTorch 和 mmdetection 的开源工具箱，专注于文本检测，文本识别以及相应的下游任务，如关键信息提取。 它是 OpenMMLab 项目的一部分。
@ -69,19 +91,6 @@ MMOCR 的模块化设计使用户可以定义自己的优化器，数据预处

 该工具箱提供了一套全面的实用程序，可以帮助用户评估模型的性能。它包括可对图像，标注的真值以及预测结果进行可视化的可视化工具，以及用于在训练过程中评估模型的验证工具。它还包括数据转换器，演示了如何将用户自建的标注数据转换为 MMOCR 支持的标注文件。

-## 近期更新
-
-**默认分支已经从 `main` 切换到 `1.x`。我们鼓励用户迁移到最新版本，请参考 [迁移指南](https://mmocr.readthedocs.io/zh_CN/dev-1.x/migration/overview.html) 以了解更多细节。**
-
-最新的版本 v1.0.0rc5 于 2023-01-06 发布。
-
-1. 新增了 Aster 和 SVTR 模型，并完整支持了 ABCNet 的训练与测试；
-2. Dataset Preparer 新支持了5个数据集：CocoTextV2, FUNSD, TextOCR, NAF, SROIE；
-3. 新增了4个文本识别以及2个辅助运行过程的数据变换。
-4. 数据变换 `FixInvalidPolygon` 现在可以处理更多种类的非法多边形，因此各模型如今也可以顺畅地在 TotalText 数据集上完成训练流程。我们同时也发布了 DBNet 和 FCENet 在 TotalText 上的预训练模型。
-
-阅读[更新日志](https://mmocr.readthedocs.io/zh_CN/dev-1.x/notes/changelog.html)以获取更多信息。
-
 ## MMOCR 1.0 更新汇总

 1. 架构升级：MMOCR 1.x 是基于 [MMEngine](https://github.com/open-mmlab/mmengine)，提供了一个通用的、强大的执行器，允许更灵活的定制，提供了统一的训练和测试入口。
--- a/docs/en/get_started/install.md
+++ b/docs/en/get_started/install.md
@ -237,5 +237,6 @@ MMOCR has different version requirements on MMEngine, MMCV and MMDetection at ea
 | MMOCR          | MMEngine                    | MMCV                       | MMDetection                 |
 | -------------- | --------------------------- | -------------------------- | --------------------------- |
 | dev-1.x        | 0.6.0 \<= mmengine \< 1.0.0 | 2.0.0rc4 \<= mmcv \< 2.1.0 | 3.0.0rc5 \<= mmdet \< 3.1.0 |
+| 1.0.0rc6       | 0.6.0 \<= mmengine \< 1.0.0 | 2.0.0rc4 \<= mmcv \< 2.1.0 | 3.0.0rc5 \<= mmdet \< 3.1.0 |
 | 1.0.0rc\[4-5\] | 0.1.0 \<= mmengine \< 1.0.0 | 2.0.0rc1 \<= mmcv \< 2.1.0 | 3.0.0rc0 \<= mmdet \< 3.1.0 |
 | 1.0.0rc\[0-3\] | 0.0.0 \<= mmengine \< 0.2.0 | 2.0.0rc1 \<= mmcv \< 2.1.0 | 3.0.0rc0 \<= mmdet \< 3.1.0 |
--- a/docs/en/notes/changelog.md
+++ b/docs/en/notes/changelog.md
@ -1,5 +1,82 @@
 # Changelog of v1.x

+## v1.0.0rc5 (07/03/2023)
+
+### Highlights
+
+1. Two new models, ABCNet v2 (inference only) and SPTS are added to `projects/` folder.
+2. Announcing `Inferencer`, a unified inference interface in OpenMMLab for everyone's easy access and quick inference with all the pre-trained weights. [Docs](https://mmocr.readthedocs.io/en/dev-1.x/user_guides/inference.html)
+3. Users can use test-time augmentation for text recognition tasks. [Docs](https://mmocr.readthedocs.io/en/dev-1.x/user_guides/train_test.html#test-time-augmentation)
+4. Support [batch augmentation](https://openaccess.thecvf.com/content_CVPR_2020/papers/Hoffer_Augment_Your_Batch_Improving_Generalization_Through_Instance_Repetition_CVPR_2020_paper.pdf) through [`BatchAugSampler`](https://github.com/open-mmlab/mmocr/pull/1757), which is a technique used in SPTS.
+5. Dataset Preparer has been refactored to allow more flexible configurations. Besides, users are now able to prepare text recognition datasets in LMDB formats. [Docs](https://mmocr.readthedocs.io/en/dev-1.x/user_guides/data_prepare/dataset_preparer.html#lmdb-format)
+6. Some textspotting datasets have been revised to enhance the correctness and consistency with the common practice.
+7. Potential spurious warnings from `shapely` have been eliminated.
+
+### Dependency
+
+This version requires MMEngine >= 0.6.0, MMCV >= 2.0.0rc4 and MMDet >= 3.0.0rc5.
+
+### New Features & Enhancements
+
+- Discard deprecated lmdb dataset format and only support img+label now by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1681
+- abcnetv2 inference by @Harold-lkk in https://github.com/open-mmlab/mmocr/pull/1657
+- Add RepeatAugSampler by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1678
+- SPTS by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1696
+- Refactor Inferencers by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1608
+- Dynamic return type for rescale_polygons by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1702
+- Revise upstream version limit by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1703
+- TextRecogCropConverter add crop with opencv warpPersepective function by @KevinNuNu in https://github.com/open-mmlab/mmocr/pull/1667
+- change cudnn benchmark to false by @Harold-lkk in https://github.com/open-mmlab/mmocr/pull/1705
+- Add ST-pretrained DB-series models and logs by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1635
+- Only keep meta and state_dict when publish model by @Harold-lkk in https://github.com/open-mmlab/mmocr/pull/1729
+- Rec TTA by @Harold-lkk in https://github.com/open-mmlab/mmocr/pull/1401
+- Speedup formatting by replacing np.transpose with torch… by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1719
+- Support auto import modules from registry. by @Harold-lkk in https://github.com/open-mmlab/mmocr/pull/1731
+- Support batch visualization & dumping in Inferencer by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1722
+- add a new argument font_properties to set a specific font file in order to draw Chinese characters properly by @KevinNuNu in https://github.com/open-mmlab/mmocr/pull/1709
+- Refactor data converter and gather by @Harold-lkk in https://github.com/open-mmlab/mmocr/pull/1707
+- Support batch augmentation through BatchAugSampler by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1757
+- Put all registry into registry.py by @Harold-lkk in https://github.com/open-mmlab/mmocr/pull/1760
+- train by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1756
+- configs for regression benchmark by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1755
+- Support lmdb format in Dataset Preparer by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1762
+
+### Docs
+
+- update the link of DBNet by @AllentDan in https://github.com/open-mmlab/mmocr/pull/1672
+- Add notice for default branch switching by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1693
+- docs: Add twitter discord medium youtube link by @vansin in https://github.com/open-mmlab/mmocr/pull/1724
+- Remove unsupported datasets in docs by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1670
+
+### Bug Fixes
+
+- Update dockerfile by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1671
+- Explicitly create np object array for compatibility by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1691
+- Fix a minor error in docstring by @Mountchicken in https://github.com/open-mmlab/mmocr/pull/1685
+- Fix lint by @triple-Mu in https://github.com/open-mmlab/mmocr/pull/1694
+- Fix LoadOCRAnnotation ut by @Harold-lkk in https://github.com/open-mmlab/mmocr/pull/1695
+- Fix isort pre-commit error by @KevinNuNu in https://github.com/open-mmlab/mmocr/pull/1697
+- Update owners by @xinke-wang in https://github.com/open-mmlab/mmocr/pull/1699
+- Detect intersection before using shapley.intersection to eliminate spurious warnings by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1710
+- Fix some inferencer bugs by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1706
+- Fix textocr ignore flag by @xinke-wang in https://github.com/open-mmlab/mmocr/pull/1712
+- Add missing softmax in ASTER forward_test by @Mountchicken in https://github.com/open-mmlab/mmocr/pull/1718
+- Fix head in readme by @vansin in https://github.com/open-mmlab/mmocr/pull/1727
+- Fix some browse dataset script bugs and draw textdet gt instance with ignore flags by @KevinNuNu in https://github.com/open-mmlab/mmocr/pull/1701
+- icdar textrecog ann parser skip data with ignore flag by @KevinNuNu in https://github.com/open-mmlab/mmocr/pull/1708
+- bezier_to_polygon ->  bezier2polygon by @double22a in https://github.com/open-mmlab/mmocr/pull/1739
+- Fix docs recog CharMetric P/R error definition by @KevinNuNu in https://github.com/open-mmlab/mmocr/pull/1740
+- Remove outdated resources in demo/ by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1747
+- Fix wrong ic13 textspotting split data; add lexicons to ic13, ic15 and totaltext by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1758
+- SPTS readme by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1761
+
+### New Contributors
+
+- @triple-Mu made their first contribution in https://github.com/open-mmlab/mmocr/pull/1694
+- @double22a made their first contribution in https://github.com/open-mmlab/mmocr/pull/1739
+
+**Full Changelog**: https://github.com/open-mmlab/mmocr/compare/v1.0.0rc5...v1.0.0rc6
+
 ## v1.0.0rc5 (06/01/2023)

 ### Highlights
@ -41,6 +118,7 @@
 - Add Chinese translation for browse_dataset.py by @xinke-wang in https://github.com/open-mmlab/mmocr/pull/1647
 - updata abcnet doc by @Harold-lkk in https://github.com/open-mmlab/mmocr/pull/1658
 - update the dbnetpp\`s readme file by @zhuyue66 in https://github.com/open-mmlab/mmocr/pull/1626
+- Inferencer docs by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1744

 ### Bug Fixes

--- a/docs/zh_cn/get_started/install.md
+++ b/docs/zh_cn/get_started/install.md
@ -236,5 +236,6 @@ docker run --gpus all --shm-size=8g -it -v {实际数据目录}:/mmocr/data mmoc
 | MMOCR          | MMEngine                    | MMCV                       | MMDetection                 |
 | -------------- | --------------------------- | -------------------------- | --------------------------- |
 | dev-1.x        | 0.6.0 \<= mmengine \< 1.0.0 | 2.0.0rc4 \<= mmcv \< 2.1.0 | 3.0.0rc5 \<= mmdet \< 3.1.0 |
+| 1.0.0rc6       | 0.6.0 \<= mmengine \< 1.0.0 | 2.0.0rc4 \<= mmcv \< 2.1.0 | 3.0.0rc5 \<= mmdet \< 3.1.0 |
 | 1.0.0rc\[4-5\] | 0.1.0 \<= mmengine \< 1.0.0 | 2.0.0rc1 \<= mmcv \< 2.1.0 | 3.0.0rc0 \<= mmdet \< 3.1.0 |
 | 1.0.0rc\[0-3\] | 0.0.0 \<= mmengine \< 0.2.0 | 2.0.0rc1 \<= mmcv \< 2.1.0 | 3.0.0rc0 \<= mmdet \< 3.1.0 |
--- a/mmocr/version.py
+++ b/mmocr/version.py
@ -1,4 +1,4 @@
 # Copyright (c) Open-MMLab. All rights reserved.

-__version__ = '1.0.0rc5'
+__version__ = '1.0.0rc6'
 short_version = __version__