Update 3.x link to main (open-mmlab#10079)

.circleci/test.yml

@@ -91,7 +91,7 @@ jobs:
         type: string
       cuda:
         type: enum
-        enum: ["10.1", "10.2", "11.1"]
+        enum: ["10.1", "10.2", "11.1", "11.7"]
       cudnn:
         type: integer
         default: 7
@@ -161,8 +161,8 @@ workflows:
             - lint
       - build_cpu:
           name: maximum_version_cpu
-          torch: 1.13.0
-          torchvision: 0.14.0
+          torch: 2.0.0
+          torchvision: 0.15.1
           python: 3.9.0
           requires:
             - minimum_version_cpu
@@ -178,6 +178,13 @@ workflows:
           cuda: "10.2"
           requires:
             - hold
+      - build_cuda:
+          name: maximum_version_gpu
+          torch: 2.0.0
+          cuda: "11.7"
+          cudnn: 8
+          requires:
+            - hold
   merge_stage_test:
     when:
       not: << pipeline.parameters.lint_only >>

README.md

@@ -21,15 +21,15 @@
 [![PyPI](https://img.shields.io/pypi/v/mmdet)](https://pypi.org/project/mmdet)
 [![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmdetection.readthedocs.io/en/latest/)
 [![badge](https://github.com/open-mmlab/mmdetection/workflows/build/badge.svg)](https://github.com/open-mmlab/mmdetection/actions)
-[![codecov](https://codecov.io/gh/open-mmlab/mmdetection/branch/master/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmdetection)
-[![license](https://img.shields.io/github/license/open-mmlab/mmdetection.svg)](https://github.com/open-mmlab/mmdetection/blob/master/LICENSE)
+[![codecov](https://codecov.io/gh/open-mmlab/mmdetection/branch/main/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmdetection)
+[![license](https://img.shields.io/github/license/open-mmlab/mmdetection.svg)](https://github.com/open-mmlab/mmdetection/blob/main/LICENSE)
 [![open issues](https://isitmaintained.com/badge/open/open-mmlab/mmdetection.svg)](https://github.com/open-mmlab/mmdetection/issues)
 [![issue resolution](https://isitmaintained.com/badge/resolution/open-mmlab/mmdetection.svg)](https://github.com/open-mmlab/mmdetection/issues)
 
-[📘Documentation](https://mmdetection.readthedocs.io/en/3.x/) |
-[🛠️Installation](https://mmdetection.readthedocs.io/en/3.x/get_started.html) |
-[👀Model Zoo](https://mmdetection.readthedocs.io/en/3.x/model_zoo.html) |
-[🆕Update News](https://mmdetection.readthedocs.io/en/3.x/notes/changelog.html) |
+[📘Documentation](https://mmdetection.readthedocs.io/en/latest/) |
+[🛠️Installation](https://mmdetection.readthedocs.io/en/latest/get_started.html) |
+[👀Model Zoo](https://mmdetection.readthedocs.io/en/latest/model_zoo.html) |
+[🆕Update News](https://mmdetection.readthedocs.io/en/latest/notes/changelog.html) |
 [🚀Ongoing Projects](https://github.com/open-mmlab/mmdetection/projects) |
 [🤔Reporting Issues](https://github.com/open-mmlab/mmdetection/issues/new/choose)
 
@@ -66,7 +66,7 @@ English | [简体中文](README_zh-CN.md)
 MMDetection is an open source object detection toolbox based on PyTorch. It is
 a part of the [OpenMMLab](https://openmmlab.com/) project.
 
-The master branch works with **PyTorch 1.6+**.
+The main branch works with **PyTorch 1.6+**.
 
 <img src="https://user-images.githubusercontent.com/12907710/187674113-2074d658-f2fb-42d1-ac15-9c4a695e64d7.png"/>
 
@@ -114,59 +114,56 @@ We are excited to announce our latest work on real-time object recognition tasks
 <img src="https://user-images.githubusercontent.com/12907710/208044554-1e8de6b5-48d8-44e4-a7b5-75076c7ebb71.png"/>
 </div>
 
-**v3.0.0rc6** was released in 24/2/2023:
+**v3.0.0** was released in 6/4/2023:
 
-- Support [Boxinst](configs/boxinst), [Objects365 Dataset](configs/objects365), and [Separated and Occluded COCO metric](docs/en/user_guides/useful_tools.md#coco-separated--occluded-mask-metric)
-- Support [ConvNeXt-V2](projects/ConvNeXt-V2), [DiffusionDet](projects/DiffusionDet), and inference of [EfficientDet](projects/EfficientDet) and [Detic](projects/Detic) in `Projects`
-- Refactor [DETR](configs/detr) series and support [Conditional-DETR](configs/conditional_detr), [DAB-DETR](configs/dab_detr), and [DINO](configs/dino)
-- Support `DetInferencer` for inference, Test Time Augmentation, and automatically importing modules from registry
-- Support RTMDet-Ins ONNXRuntime and TensorRT [deployment](configs/rtmdet/README.md#deployment-tutorial)
-- Support [calculating FLOPs of detectors](docs/en/user_guides/useful_tools.md#Model-Complexity)
+- Release MMDetection 3.0.0 official version
+- Support Semi-automatic annotation Base [Label-Studio](projects/LabelStudio) (#10039)
+- Support [EfficientDet](projects/EfficientDet) in projects (#9810)
 
 ## Installation
 
-Please refer to [Installation](https://mmdetection.readthedocs.io/en/3.x/get_started.html) for installation instructions.
+Please refer to [Installation](https://mmdetection.readthedocs.io/en/latest/get_started.html) for installation instructions.
 
 ## Getting Started
 
-Please see [Overview](https://mmdetection.readthedocs.io/en/3.x/get_started.html) for the general introduction of MMDetection.
+Please see [Overview](https://mmdetection.readthedocs.io/en/latest/get_started.html) for the general introduction of MMDetection.
 
-For detailed user guides and advanced guides, please refer to our [documentation](https://mmdetection.readthedocs.io/en/3.x/):
+For detailed user guides and advanced guides, please refer to our [documentation](https://mmdetection.readthedocs.io/en/latest/):
 
 - User Guides
 
   <details>
 
-  - [Train & Test](https://mmdetection.readthedocs.io/en/3.x/user_guides/index.html#train-test)
-    - [Learn about Configs](https://mmdetection.readthedocs.io/en/3.x/user_guides/config.html)
-    - [Inference with existing models](https://mmdetection.readthedocs.io/en/3.x/user_guides/inference.html)
-    - [Dataset Prepare](https://mmdetection.readthedocs.io/en/3.x/user_guides/dataset_prepare.html)
-    - [Test existing models on standard datasets](https://mmdetection.readthedocs.io/en/3.x/user_guides/test.html)
-    - [Train predefined models on standard datasets](https://mmdetection.readthedocs.io/en/3.x/user_guides/train.html)
-    - [Train with customized datasets](https://mmdetection.readthedocs.io/en/3.x/user_guides/train.html#train-with-customized-datasets)
-    - [Train with customized models and standard datasets](https://mmdetection.readthedocs.io/en/3.x/user_guides/new_model.html)
-    - [Finetuning Models](https://mmdetection.readthedocs.io/en/3.x/user_guides/finetune.html)
-    - [Test Results Submission](https://mmdetection.readthedocs.io/en/3.x/user_guides/test_results_submission.html)
-    - [Weight initialization](https://mmdetection.readthedocs.io/en/3.x/user_guides/init_cfg.html)
-    - [Use a single stage detector as RPN](https://mmdetection.readthedocs.io/en/3.x/user_guides/single_stage_as_rpn.html)
-    - [Semi-supervised Object Detection](https://mmdetection.readthedocs.io/en/3.x/user_guides/semi_det.html)
-  - [Useful Tools](https://mmdetection.readthedocs.io/en/3.x/user_guides/index.html#useful-tools)
+  - [Train & Test](https://mmdetection.readthedocs.io/en/latest/user_guides/index.html#train-test)
+    - [Learn about Configs](https://mmdetection.readthedocs.io/en/latest/user_guides/config.html)
+    - [Inference with existing models](https://mmdetection.readthedocs.io/en/latest/user_guides/inference.html)
+    - [Dataset Prepare](https://mmdetection.readthedocs.io/en/latest/user_guides/dataset_prepare.html)
+    - [Test existing models on standard datasets](https://mmdetection.readthedocs.io/en/latest/user_guides/test.html)
+    - [Train predefined models on standard datasets](https://mmdetection.readthedocs.io/en/latest/user_guides/train.html)
+    - [Train with customized datasets](https://mmdetection.readthedocs.io/en/latest/user_guides/train.html#train-with-customized-datasets)
+    - [Train with customized models and standard datasets](https://mmdetection.readthedocs.io/en/latest/user_guides/new_model.html)
+    - [Finetuning Models](https://mmdetection.readthedocs.io/en/latest/user_guides/finetune.html)
+    - [Test Results Submission](https://mmdetection.readthedocs.io/en/latest/user_guides/test_results_submission.html)
+    - [Weight initialization](https://mmdetection.readthedocs.io/en/latest/user_guides/init_cfg.html)
+    - [Use a single stage detector as RPN](https://mmdetection.readthedocs.io/en/latest/user_guides/single_stage_as_rpn.html)
+    - [Semi-supervised Object Detection](https://mmdetection.readthedocs.io/en/latest/user_guides/semi_det.html)
+  - [Useful Tools](https://mmdetection.readthedocs.io/en/latest/user_guides/index.html#useful-tools)
 
   </details>
 
 - Advanced Guides
 
   <details>
 
-  - [Basic Concepts](https://mmdetection.readthedocs.io/en/3.x/advanced_guides/index.html#basic-concepts)
-  - [Component Customization](https://mmdetection.readthedocs.io/en/3.x/advanced_guides/index.html#component-customization)
-  - [How to](https://mmdetection.readthedocs.io/en/3.x/advanced_guides/index.html#how-to)
+  - [Basic Concepts](https://mmdetection.readthedocs.io/en/latest/advanced_guides/index.html#basic-concepts)
+  - [Component Customization](https://mmdetection.readthedocs.io/en/latest/advanced_guides/index.html#component-customization)
+  - [How to](https://mmdetection.readthedocs.io/en/latest/advanced_guides/index.html#how-to)
 
   </details>
 
 We also provide object detection colab tutorial [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](demo/MMDet_Tutorial.ipynb) and instance segmentation colab tutorial [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](demo/MMDet_InstanceSeg_Tutorial.ipynb).
 
-To migrate from MMDetection 2.x, please refer to [migration](https://mmdetection.readthedocs.io/en/3.x/migration.html).
+To migrate from MMDetection 2.x, please refer to [migration](https://mmdetection.readthedocs.io/en/latest/migration.html).
 
 ## Overview of Benchmark and Model Zoo
 

README_zh-CN.md

@@ -21,15 +21,15 @@
 [![PyPI](https://img.shields.io/pypi/v/mmdet)](https://pypi.org/project/mmdet)
 [![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmdetection.readthedocs.io/en/latest/)
 [![badge](https://github.com/open-mmlab/mmdetection/workflows/build/badge.svg)](https://github.com/open-mmlab/mmdetection/actions)
-[![codecov](https://codecov.io/gh/open-mmlab/mmdetection/branch/master/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmdetection)
-[![license](https://img.shields.io/github/license/open-mmlab/mmdetection.svg)](https://github.com/open-mmlab/mmdetection/blob/master/LICENSE)
+[![codecov](https://codecov.io/gh/open-mmlab/mmdetection/branch/main/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmdetection)
+[![license](https://img.shields.io/github/license/open-mmlab/mmdetection.svg)](https://github.com/open-mmlab/mmdetection/blob/main/LICENSE)
 [![open issues](https://isitmaintained.com/badge/open/open-mmlab/mmdetection.svg)](https://github.com/open-mmlab/mmdetection/issues)
 [![issue resolution](https://isitmaintained.com/badge/resolution/open-mmlab/mmdetection.svg)](https://github.com/open-mmlab/mmdetection/issues)
 
-[📘使用文档](https://mmdetection.readthedocs.io/zh_CN/3.x/) |
-[🛠️安装教程](https://mmdetection.readthedocs.io/zh_CN/3.x/get_started.html) |
-[👀模型库](https://mmdetection.readthedocs.io/zh_CN/3.x/model_zoo.html) |
-[🆕更新日志](https://mmdetection.readthedocs.io/en/3.x/notes/changelog.html) |
+[📘使用文档](https://mmdetection.readthedocs.io/zh_CN/latest/) |
+[🛠️安装教程](https://mmdetection.readthedocs.io/zh_CN/latest/get_started.html) |
+[👀模型库](https://mmdetection.readthedocs.io/zh_CN/latest/model_zoo.html) |
+[🆕更新日志](https://mmdetection.readthedocs.io/en/latest/notes/changelog.html) |
 [🚀进行中的项目](https://github.com/open-mmlab/mmdetection/projects) |
 [🤔报告问题](https://github.com/open-mmlab/mmdetection/issues/new/choose)
 
@@ -113,61 +113,58 @@ MMDetection 是一个基于 PyTorch 的目标检测开源工具箱。它是 [Ope
 <img src="https://user-images.githubusercontent.com/12907710/208044554-1e8de6b5-48d8-44e4-a7b5-75076c7ebb71.png"/>
 </div>
 
-**v3.0.0rc6** 版本已经在 2023.2.24 发布：
+**v3.0.0** 版本已经在 2023.4.6 发布：
 
-- 支持了 [Boxinst](configs/boxinst), [Objects365 Dataset](configs/objects365) 和 [Separated and Occluded COCO metric](docs/zh_cn/user_guides/useful_tools.md#coco-分离和遮挡实例分割性能评估)
-- 在 `Projects` 中支持了 [ConvNeXt-V2](projects/ConvNeXt-V2), [DiffusionDet](projects/DiffusionDet) 和 [EfficientDet](projects/EfficientDet), [Detic](projects/Detic) 的推理
-- 重构了 [DETR](configs/detr) 系列并支持了 [Conditional-DETR](configs/conditional_detr), [DAB-DETR](configs/dab_detr) 和 [DINO](configs/dino)
-- 支持了通过 `DetInferencer` 用于推理, Test Time Augmentation 以及从注册表(registry)自动导入模块
-- 支持了 RTMDet-Ins 的 ONNXRuntime 和 TensorRT [部署](configs/rtmdet/README.md#deployment-tutorial)
-- 支持了检测器[计算 FLOPS](docs/zh_cn/user_guides/useful_tools.md#模型复杂度)
+- 发布 MMDetection 3.0.0 正式版
+- 基于 [Label-Studio](projects/LabelStudio) 支持半自动标注流程
+- projects 中支持了 [EfficientDet](projects/EfficientDet)
 
 ## 安装
 
-请参考[快速入门文档](https://mmdetection.readthedocs.io/zh_CN/3.x/get_started.html)进行安装。
+请参考[快速入门文档](https://mmdetection.readthedocs.io/zh_CN/latest/get_started.html)进行安装。
 
 ## 教程
 
-请阅读[概述](https://mmdetection.readthedocs.io/zh_CN/3.x/get_started.html)对 MMDetection 进行初步的了解。
+请阅读[概述](https://mmdetection.readthedocs.io/zh_CN/latest/get_started.html)对 MMDetection 进行初步的了解。
 
-为了帮助用户更进一步了解 MMDetection，我们准备了用户指南和进阶指南，请阅读我们的[文档](https://mmdetection.readthedocs.io/zh_CN/3.x/)：
+为了帮助用户更进一步了解 MMDetection，我们准备了用户指南和进阶指南，请阅读我们的[文档](https://mmdetection.readthedocs.io/zh_CN/latest/)：
 
 - 用户指南
 
   <details>
 
-  - [训练 & 测试](https://mmdetection.readthedocs.io/zh_CN/3.x/user_guides/index.html#train-test)
-    - [学习配置文件](https://mmdetection.readthedocs.io/zh_CN/3.x/user_guides/config.html)
-    - [使用已有模型在标准数据集上进行推理](https://mmdetection.readthedocs.io/en/3.x/user_guides/inference.html)
-    - [数据集准备](https://mmdetection.readthedocs.io/zh_CN/3.x/user_guides/dataset_prepare.html)
-    - [测试现有模型](https://mmdetection.readthedocs.io/zh_CN/3.x/user_guides/test.html)
-    - [在标准数据集上训练预定义的模型](https://mmdetection.readthedocs.io/zh_CN/3.x/user_guides/train.html)
-    - [在自定义数据集上进行训练](https://mmdetection.readthedocs.io/zh_CN/3.x/user_guides/train.html#train-with-customized-datasets)
-    - [在标准数据集上训练自定义模型](https://mmdetection.readthedocs.io/zh_CN/3.x/user_guides/new_model.html)
-    - [模型微调](https://mmdetection.readthedocs.io/zh_CN/3.x/user_guides/finetune.html)
-    - [提交测试结果](https://mmdetection.readthedocs.io/zh_CN/3.x/user_guides/test_results_submission.html)
-    - [权重初始化](https://mmdetection.readthedocs.io/zh_CN/3.x/user_guides/init_cfg.html)
-    - [将单阶段检测器作为 RPN](https://mmdetection.readthedocs.io/zh_CN/3.x/user_guides/single_stage_as_rpn.html)
-    - [半监督目标检测](https://mmdetection.readthedocs.io/zh_CN/3.x/user_guides/semi_det.html)
-  - [实用工具](https://mmdetection.readthedocs.io/zh_CN/3.x/user_guides/index.html#useful-tools)
+  - [训练 & 测试](https://mmdetection.readthedocs.io/zh_CN/latest/user_guides/index.html#train-test)
+    - [学习配置文件](https://mmdetection.readthedocs.io/zh_CN/latest/user_guides/config.html)
+    - [使用已有模型在标准数据集上进行推理](https://mmdetection.readthedocs.io/en/latest/user_guides/inference.html)
+    - [数据集准备](https://mmdetection.readthedocs.io/zh_CN/latest/user_guides/dataset_prepare.html)
+    - [测试现有模型](https://mmdetection.readthedocs.io/zh_CN/latest/user_guides/test.html)
+    - [在标准数据集上训练预定义的模型](https://mmdetection.readthedocs.io/zh_CN/latest/user_guides/train.html)
+    - [在自定义数据集上进行训练](https://mmdetection.readthedocs.io/zh_CN/latest/user_guides/train.html#train-with-customized-datasets)
+    - [在标准数据集上训练自定义模型](https://mmdetection.readthedocs.io/zh_CN/latest/user_guides/new_model.html)
+    - [模型微调](https://mmdetection.readthedocs.io/zh_CN/latest/user_guides/finetune.html)
+    - [提交测试结果](https://mmdetection.readthedocs.io/zh_CN/latest/user_guides/test_results_submission.html)
+    - [权重初始化](https://mmdetection.readthedocs.io/zh_CN/latest/user_guides/init_cfg.html)
+    - [将单阶段检测器作为 RPN](https://mmdetection.readthedocs.io/zh_CN/latest/user_guides/single_stage_as_rpn.html)
+    - [半监督目标检测](https://mmdetection.readthedocs.io/zh_CN/latest/user_guides/semi_det.html)
+  - [实用工具](https://mmdetection.readthedocs.io/zh_CN/latest/user_guides/index.html#useful-tools)
 
   </details>
 
 - 进阶指南
 
   <details>
 
-  - [基础概念](https://mmdetection.readthedocs.io/zh_CN/3.x/advanced_guides/index.html#basic-concepts)
-  - [组件定制](https://mmdetection.readthedocs.io/zh_CN/3.x/advanced_guides/index.html#component-customization)
-  - [How to](https://mmdetection.readthedocs.io/zh_CN/3.x/advanced_guides/index.html#how-to)
+  - [基础概念](https://mmdetection.readthedocs.io/zh_CN/latest/advanced_guides/index.html#basic-concepts)
+  - [组件定制](https://mmdetection.readthedocs.io/zh_CN/latest/advanced_guides/index.html#component-customization)
+  - [How to](https://mmdetection.readthedocs.io/zh_CN/latest/advanced_guides/index.html#how-to)
 
   </details>
 
 我们提供了检测的 colab 教程 [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](demo/MMDet_Tutorial.ipynb) 和 实例分割的 colab 教程 [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](demo/MMDet_Tutorial.ipynb)
 
 同时，我们还提供了 [MMDetection 中文解读文案汇总](docs/zh_cn/article.md)
 
-若需要将2.x版本的代码迁移至新版，请参考[迁移文档](https://mmdetection.readthedocs.io/en/3.x/migration.html)。
+若需要将2.x版本的代码迁移至新版，请参考[迁移文档](https://mmdetection.readthedocs.io/en/latest/migration.html)。
 
 ## 基准测试和模型库
 

configs/fast_rcnn/README.md

@@ -59,7 +59,7 @@ The `pred_instance` is an `InstanceData` containing the sorted boxes and scores
       8
   ```
 
-  Users can refer to [test tutorial](https://mmdetection.readthedocs.io/en/3.x/user_guides/test.html) for more details.
+  Users can refer to [test tutorial](https://mmdetection.readthedocs.io/en/latest/user_guides/test.html) for more details.
 
 - Then, modify the path of `proposal_file` in the dataset and using `ProposalBroadcaster` to process both ground truth bounding boxes and region proposals in pipelines.
   An example of Fast R-CNN important setting can be seen as below: