update MM series docs (#37)

* 修改了引入代码的描述，增加了对mmengine的说明

* 完成修复mmengine的文档

* 增加了训练结果

* 增加安装和登陆说明

* 增加了mmdetection的文档

* 修改离线看板的链接

* 完成mmsegmentation文档

* 修改了描述，增加了互相引用

* 删掉标题中多的S

* 增加了MMPretrain的配置文件

* 增加了xtuner的简介

* 增加了init的接口link

* 增加了使用案例

* update something

---------

Co-authored-by: ShaohonChen <[email protected]>

.vitepress/config.mts

@@ -153,6 +153,9 @@ function sidebarGuideCloud(): DefaultTheme.SidebarItem[] {
       { text: 'HuggingFace Transformers', link: 'integration/integration-huggingface-transformers' },
       { text: 'Hydra', link: 'integration/integration-hydra' },
       { text: 'MMEngine', link: 'integration/integration-mmengine' },
+      { text: 'MMPretrain', link: 'integration/integration-mmpretrain' },
+      { text: 'MMDetection', link: 'integration/integration-mmdetection' },
+      { text: 'MMSegmentation', link: 'integration/integration-mmsegmentation' },
       { text: 'OpenAI', link: 'integration/integration-openai' },
       { text: 'Omegaconf', link: 'integration/integration-omegaconf' },
       { text: 'PyTorch', link: 'integration/integration-pytorch' },
@@ -162,6 +165,7 @@ function sidebarGuideCloud(): DefaultTheme.SidebarItem[] {
       { text: 'Tensorboard', link: 'integration/integration-tensorboard'},
       { text: 'Ultralytics', link: 'integration/integration-ultralytics' },
       { text: 'Weights & Biases', link: 'integration/integration-wandb'},
+      { text: 'Xtuner', link: 'integration/integration-xtuner'},
       { text: 'ZhipuAI', link: 'integration/integration-zhipuai'},
     ]
   },

zh/guide_cloud/integration/integration-mmdetection.md

@@ -0,0 +1,94 @@
+# MMDetection
+
+:::info 教程
+[mmdetection如何使用swanlab远程查看训练日志](https://zhuanlan.zhihu.com/p/699058426)
+:::
+
+<div align="center">
+<img src="/assets/integration-mmdetection.png" width=600>
+</div>
+
+[MMdetection](https://github.com/open-mmlab/mmdetection) 是一个由 [OpenMMLab](https://openmmlab.com/) 社区开发的深度学习训练框架，建立在 PyTorch 深度学习框架之上，旨在为研究人员和工程师提供一个高效、灵活、易于扩展的目标检测平台。MMDetection 支持多种主流的目标检测方法，并提供了大量预训练模型和丰富的配置选项，使得在目标检测任务中的应用和开发变得更加便捷。
+
+<div align="center">
+<img src="/assets/integration-mmdetection-intro.png">
+</div>
+
+可以通过修改MMDetection的配置文件来使用SwanLab作为实验记录工具。
+
+## 在配置文件中指定SwanLab作为VisBackend
+
+确保你安装了SwanLab，或者使用`pip install -U swanlab`安装最新版。
+
+将如下内容添加到mmdetection的config文件中, 其中`init_kwargs`中填入的参数字典与`swanlab.init`的规则一致:
+
+```python
+# swanlab visualizer
+custom_imports = dict(  # 引入SwanLab作为日志记录器，对于部分不支持custom_imports的项目可以直接初始化SwanlabVisBackend并加入vis_backends
+    imports=["swanlab.integration.mmengine"], allow_failed_imports=False
+)
+
+vis_backends = [
+    dict(
+        type="SwanlabVisBackend",
+        init_kwargs={ # swanlab.init 参数
+            "project": "swanlab-mmengine",
+            "experiment_name": "Your exp",  # 实验名称
+            "description": "Note whatever you want",  # 实验的描述信息
+        },
+    ),
+]
+
+visualizer = dict(
+    type="Visualizer",
+    vis_backends=vis_backends,
+    name="visualizer",
+)
+```
+
+> 有关其他引入方法和更灵活的配置，可以参考[MMEngine接入SwanLab](https://docs.swanlab.cn/zh/guide_cloud/integration/integration-mmengine.html)
+
+## 使用案例：MMDetection训练faster-rcnn
+
+首先克隆[MMDetction](https://github.com/open-mmlab/mmdetection)项目到本地。
+
+然后在faster-rnn对应的config文件（`configs/faster_rcnn/faster-rcnn_r50_fpn_1x_coco.py`）的最后增加下面的代码：
+
+```python
+_base_ = [
+    '../_base_/models/faster-rcnn_r50_fpn.py',
+    '../_base_/datasets/coco_detection.py',
+    '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
+]
+
+# swanlab
+custom_imports = dict(  # 引入SwanLab作为日志记录器
+    imports=["swanlab.integration.mmengine"], allow_failed_imports=False
+)
+vis_backends = [
+    dict(type="LocalVisBackend"),
+    dict(
+        type="SwanlabVisBackend",
+        init_kwargs={  # swanlab.init 参数
+            "project": "MMDetection",  # 项目名称
+            "experiment_name": "faster-rcnn",  # 实验名称
+            "description": "faster-rcnn r50 fpn 1x coco",  # 实验的描述信息
+        },
+    ),
+]
+visualizer = dict(
+    type="DetLocalVisualizer", vis_backends=vis_backends, name="visualizer"
+)
+```
+
+**然后开启训练即可**：
+
+```bash
+python tools/train.py configs/faster_rcnn/faster-rcnn_r50_fpn_1x_coco.py
+```
+
+![ig-mmengine-1](/assets/ig-mmengine-1.png)
+
+**在swanlab中远程查看训练日志**：
+
+![ig-mmengine-2](/assets/ig-mmengine-2.png)