[Docs] Update rtmpose docs

docs/en/advanced_guides/customize_evaluation.md

@@ -1,3 +1,5 @@
 # Customize Evaluation
 
 Coming soon.
+
+Currently, you can refer to [Evaluation Tutorial of MMEngine](https://mmengine.readthedocs.io/en/latest/tutorials/evaluation.html) to customize your own evaluation.

docs/en/user_guides/how_to_deploy.md

@@ -96,9 +96,9 @@ python ./tools/deploy.py \
 
 Parameter descriptions:
 
-- `deploy_cfg`: Deployment configuration specific to mmdeploy, including inference framework type, quantization, and whether the input shape is dynamic or static. The configuration files may have reference relationships, and `configs/mmpretrain/classification_ncnn_static.py` is an example.
+- `deploy_cfg`: Deployment configuration specific to mmdeploy, including inference framework type, quantization, and whether the input shape is dynamic or static. The configuration files may have reference relationships, and `configs/mmpose/pose-detection_simcc_onnxruntime_dynamic.py` is an example.
 
-- `model_cfg`: Model configuration specific to the mm algorithm library, e.g., `mmpose/configs/pose-detection_simcc_onnxruntime_dynamic.py`, independent of mmdeploy path.
+- `model_cfg`: Model configuration specific to the mm algorithm library, e.g., `mmpose/configs/body_2d_keypoint/rtmpose/coco/rtmpose-m_8xb256-420e_aic-coco-256x192.py`, independent of mmdeploy path.
 
 - `checkpoint`: Path to the torch model. It can be a local file path or a download link (e.g., `http/https`).
 

docs/zh_cn/advanced_guides/customize_evaluation.md

@@ -1,3 +1,5 @@
 # Customize Evaluation
 
 Coming soon.
+
+Currently, you can refer to [Evaluation Tutorial of MMEngine](https://mmengine.readthedocs.io/en/latest/tutorials/evaluation.html) to customize your own evaluation.

docs/zh_cn/user_guides/how_to_deploy.md

@@ -96,9 +96,9 @@ python ./tools/deploy.py \
 
 参数描述：
 
-- `deploy_cfg` : mmdeploy 针对此模型的部署配置，包含推理框架类型、是否量化、输入 shape 是否动态等。配置文件之间可能有引用关系，configs/mmpretrain/classification_ncnn_static.py 是一个示例。
+- `deploy_cfg` : mmdeploy 针对此模型的部署配置，包含推理框架类型、是否量化、输入 shape 是否动态等。配置文件之间可能有引用关系，`configs/mmpose/pose-detection_simcc_onnxruntime_dynamic.py` 是一个示例。
 
-- `model_cfg` : mm 算法库的模型配置，例如 mmpretrain/configs/vision_transformer/vit-base-p32_ft-64xb64_in1k-384.py，与 mmdeploy 的路径无关。
+- `model_cfg` : mm 算法库的模型配置，例如 `mmpose/configs/body_2d_keypoint/rtmpose/coco/rtmpose-m_8xb256-420e_aic-coco-256x192.py`，与 mmdeploy 的路径无关。
 
 - `checkpoint` : torch 模型路径。可以 http/https 开头，详见 mmcv.FileClient 的实现。
 

projects/README.md

@@ -30,7 +30,11 @@ We also provide some documentation listed below to help you get started:
 
 ## Project List
 
-- **[:zap:RTMPose](./rtmpose)**: Real-Time Multi-Person Pose Estimation toolkit based on MMPose
+- **[:zap:RTMPose](./rtmpose)**: Real-Time Multi-Person Pose Estimation toolkit based on MMPose <sup>
+  <a href="https://openxlab.org.cn/apps/detail/mmpose/RTMPose">
+  <i>TRY IT NOW</i>
+  </a>
+  </sup>
 
   <div align="center">
   <img src="https://github.com/open-mmlab/mmpose/assets/13503330/5b637d76-41dd-4376-9a7f-854cd120799d" width=800 height=200 />