提供更多 python 版本的标注

docs/YOLO标注以及自定义数据集.md

@@ -65,4 +65,5 @@ val: /path/val
 - [Yolo V5标注图片](https://blog.csdn.net/geji001/article/details/133896362)
 - [目标检测VOC格式标注转YOLO标注](https://blog.csdn.net/qq_46300009/article/details/136074559)
 - [利用YOLO标注并训练自己的数据集](https://blog.csdn.net/qq_54452082/article/details/137070072)
-- [使用labelimg对YOLO数据进行标注](https://blog.csdn.net/qq_41940277/article/details/136302943)
+- [使用labelimg对YOLO数据进行标注](https://blog.csdn.net/qq_41940277/article/details/136302943)
+- [免费的标注工具推荐: X-Anylabeling](https://blog.csdn.net/qq_32033383/article/details/136373207)

docs/YOLO环境安装.md

@@ -12,11 +12,12 @@ INFO：`Ultralytics YOLOv8.1.42 🚀 Python-3.8.19 torch-1.13.1+cu117 CPU (Intel
 
 ```shell
 pip install matplotlib==3.6.2 matplotlib-inline==0.1.6
-pip install onnx==1.16.1 onnxruntime==1.16.3 netron==7.6.9 opencv-python==4.9.0.80
+pip install onnx==1.16.2 onnxruntime==1.16.3 netron==7.6.9 opencv-python==4.9.0.80
 pip install pandas==1.5.3
 pip install torch==1.13.1 torchvision==0.14.1 ultralytics==8.1.42 torchaudio==0.13.1 
 # pytorch-cuda=11.7 
 pip install ultralytics
+pip install netron
 ```
 
 因为没有显卡，所以无需安装 onnx-gpu 版本。
@@ -24,7 +25,7 @@ pip install ultralytics
 采用 CUDA 安装：
 
 ```shell
-pip install onnx==1.16.1 onnxruntime-gpu==1.16.3
+pip install onnx==1.16.2 onnxruntime-gpu==1.16.3
 pip install tensorboard==2.8.0 tensorflow-gpu==2.8.4
 pip install nvidia-cuda-nvrtc-cu11==11.7.99
 pip install nvidia-cuda-runtime-cu11==11.7.99
@@ -76,4 +77,14 @@ Versions of relevant libraries:
 [pip3] torch==1.13.1
 [pip3] torchvision==0.14.1
 [conda] Could not collect
+```
+
+## Python11
+
+```shell
+sudo pip install tensorboard==2.8.0 tensorflow==2.8.4
+sudo pip install onnx==1.16.2 onnxruntime==1.16.3
+sudo pip install torch==2.1.2 torchvision==0.16.2
+sudo pip install -U ultralytics==8.3.29
+
 ```