[doc] add paddleyolo docs (#7036)

* fix  paddleyolo doc, test=document_fix

* fix paddleyolo doc, test=document_fix

README_cn.md

@@ -56,7 +56,7 @@ PaddleDetection受邀参与首个以YOLO为主题的YOLO Vision世界大会，
     - 发布行人分析工具[PP-Human v2](./deploy/pipeline)，新增打架、打电话、抽烟、闯入四大行为识别，底层算法性能升级，覆盖行人检测、跟踪、属性三类核心算法能力，提供保姆级全流程开发及模型优化策略，支持在线视频流输入
     - 首次发布[PP-Vehicle](./deploy/pipeline)，提供车牌识别、车辆属性分析（颜色、车型）、车流量统计以及违章检测四大功能，兼容图片、在线视频流、视频输入，提供完善的二次开发文档教程
   - 💡 前沿算法：
-    - 全面覆盖的[YOLO家族](docs/feature_models/YOLOSERIES_MODEL.md)经典与最新模型代码库[PaddleDetection_YOLOSeries](https://github.com/nemonameless/PaddleDetection_YOLOSeries): 包括YOLOv3，百度飞桨自研的实时高精度目标检测模型PP-YOLOE，以及前沿检测算法YOLOv4、YOLOv5、YOLOX，YOLOv6及YOLOv7
+    - 全面覆盖的[YOLO家族](docs/feature_models/YOLOSERIES_MODEL.md)经典与最新模型代码库[PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO): 包括YOLOv3，百度飞桨自研的实时高精度目标检测模型PP-YOLOE，以及前沿检测算法YOLOv4、YOLOv5、YOLOX，YOLOv6及YOLOv7
     - 新增基于[ViT](configs/vitdet)骨干网络高精度检测模型，COCO数据集精度达到55.7% mAP；新增[OC-SORT](configs/mot/ocsort)多目标跟踪模型；新增[ConvNeXt](configs/convnext)骨干网络
   - 📋 产业范例：新增[智能健身](https://aistudio.baidu.com/aistudio/projectdetail/4385813)、[打架识别](https://aistudio.baidu.com/aistudio/projectdetail/4086987?channelType=0&channel=0)、[来客分析](https://aistudio.baidu.com/aistudio/projectdetail/4230123?channelType=0&channel=0)、车辆结构化范例
 
@@ -292,7 +292,7 @@ PaddleDetection受邀参与首个以YOLO为主题的YOLO Vision世界大会，
 - `Cascade-Faster-RCNN`为`Cascade-Faster-RCNN-ResNet50vd-DCN`，PaddleDetection将其优化到COCO数据mAP为47.8%时推理速度为20FPS
 - `PP-YOLOE`是对`PP-YOLO v2`模型的进一步优化，L版本在COCO数据集mAP为51.6%，Tesla V100预测速度78.1FPS
 - `PP-YOLOE+`是对`PPOLOE`模型的进一步优化，L版本在COCO数据集mAP为53.3%，Tesla V100预测速度78.1FPS
-- [`YOLOX`](configs/yolox)和[`YOLOv5`](https://github.com/nemonameless/PaddleDetection_YOLOSeries/tree/develop/configs/yolov5)均为基于PaddleDetection复现算法，`YOLOv5`代码在[`PaddleDetection_YOLOSeries`](https://github.com/nemonameless/PaddleDetection_YOLOSeries)中，参照[YOLOSERIES_MODEL](docs/feature_models/YOLOSERIES_MODEL.md)
+- [`YOLOX`](configs/yolox)和[`YOLOv5`](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5)均为基于PaddleDetection复现算法，`YOLOv5`代码在[`PaddleYOLO`](https://github.com/PaddlePaddle/PaddleYOLO)中，参照[YOLOSERIES_MODEL](docs/feature_models/YOLOSERIES_MODEL.md)
 - 图中模型均可在[模型库](#模型库)中获取
 
 </details>
@@ -341,11 +341,11 @@ PaddleDetection受邀参与首个以YOLO为主题的YOLO Vision世界大会，
 | 模型名称                                                               | COCO精度（mAP） | V100 TensorRT FP16速度(FPS) | 配置文件                                                                                                         | 模型下载                                                                       |
 |:------------------------------------------------------------------ |:-----------:|:-------------------------:|:------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------:|
 | [YOLOX-l](configs/yolox)                                           | 50.1        | 107.5                     | [链接](configs/yolox/yolox_l_300e_coco.yml)                                                                    | [下载地址](https://paddledet.bj.bcebos.com/models/yolox_l_300e_coco.pdparams)  |
-| [YOLOv5-l](https://github.com/nemonameless/PaddleDetection_YOLOSeries/tree/develop/configs/yolov5) | 48.6        | 136.0                     | [链接](https://github.com/nemonameless/PaddleDetection_YOLOSeries/blob/develop/configs/yolov5/yolov5_l_300e_coco.yml) | [下载地址](https://paddledet.bj.bcebos.com/models/yolov5_l_300e_coco.pdparams) |
-| [YOLOv7-l](https://github.com/nemonameless/PaddleDetection_YOLOSeries/tree/develop/configs/yolov7) | 51.0        | 135.0                     | [链接](https://github.com/nemonameless/PaddleDetection_YOLOSeries/blob/develop/configs/yolov7/yolov7_l_300e_coco.yml) | [下载地址](https://paddledet.bj.bcebos.com/models/yolov7_l_300e_coco.pdparams) |
+| [YOLOv5-l](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5) | 48.6        | 136.0                     | [链接](https://github.com/nemonameless/PaddlePaddle/PaddleYOLO/blob/develop/configs/yolov5/yolov5_l_300e_coco.yml) | [下载地址](https://paddledet.bj.bcebos.com/models/yolov5_l_300e_coco.pdparams) |
+| [YOLOv7-l](https://github.com/nemonameless/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7) | 51.0        | 135.0                     | [链接](https://github.com/nemonameless/PaddlePaddle/PaddleYOLO/blob/develop/configs/yolov7/yolov7_l_300e_coco.yml) | [下载地址](https://paddledet.bj.bcebos.com/models/yolov7_l_300e_coco.pdparams) |
 
 **注意:**
-- `YOLOv5`和`YOLOv7`代码在[`PaddleDetection_YOLOSeries`](https://github.com/nemonameless/PaddleDetection_YOLOSeries)中，为基于`PaddleDetection`复现的算法，可参照[YOLOSERIES_MODEL](docs/feature_models/YOLOSERIES_MODEL.md)。
+- `YOLOv5`和`YOLOv7`代码在[`PaddleYOLO`](https://github.com/PaddlePaddle/PaddleYOLO)中，为基于`PaddleDetection`复现的算法，可参照[YOLOSERIES_MODEL](docs/feature_models/YOLOSERIES_MODEL.md)。
 
 #### 其他通用检测模型 [文档链接](docs/MODEL_ZOO_cn.md)
 

README_en.md

@@ -56,7 +56,7 @@ Join the experts of Ultralytics as well as leaders in the space on September 27t
 
   - 💡 Cutting-edge algorithms：
 
-    - Covers [YOLO family](https://github.com/nemonameless/PaddleDetection_YOLOSeries) classic and latest models: YOLOv3, PP-YOLOE (a real-time high-precision object detection model developed by Baidu PaddlePaddle), and cutting-edge detection algorithms such as YOLOv4, YOLOv5, YOLOX, YOLOv6, and YOLOv7
+    - Covers [YOLO family](https://github.com/PaddlePaddle/PaddleYOLO) classic and latest models: YOLOv3, PP-YOLOE (a real-time high-precision object detection model developed by Baidu PaddlePaddle), and cutting-edge detection algorithms such as YOLOv4, YOLOv5, YOLOX, YOLOv6, and YOLOv7
     - Newly add high precision detection model based on [ViT](configs/vitdet) backbone network, with a 55.7% mAP accuracy on COCO dataset; newly add multi-object tracking model [OC-SORT](configs/mot/ocsort); newly add [ConvNeXt](configs/convnext) backbone network.
 
   - 📋 Industrial applications: Newly add [Smart Fitness](https://aistudio.baidu.com/aistudio/projectdetail/4385813), [Fighting recognition](https://aistudio.baidu.com/aistudio/projectdetail/4086987?channelType=0&channel=0),[ and Visitor Analysis](https://aistudio.baidu.com/aistudio/projectdetail/4230123?channelType=0&channel=0).

docs/MODEL_ZOO_cn.md

@@ -97,15 +97,15 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型
 
 ### YOLOv5
 
-请参考[YOLOv5](https://github.com/nemonameless/PaddleDetection_YOLOSeries/tree/develop/configs/yolov5)
+请参考[YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5)
 
 ### YOLOv6
 
-请参考[YOLOv6](https://github.com/nemonameless/PaddleDetection_YOLOSeries/tree/develop/configs/yolov6)
+请参考[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6)
 
 ### YOLOv7
 
-请参考[YOLOv7](https://github.com/nemonameless/PaddleDetection_YOLOSeries/tree/develop/configs/yolov7)
+请参考[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7)
 
 
 ## 旋转框检测

docs/MODEL_ZOO_en.md

@@ -96,15 +96,15 @@ Please refer to[YOLOX](https://github.com/PaddlePaddle/PaddleDetection/tree/deve
 
 ### YOLOv5
 
-Please refer to[YOLOv5](https://github.com/nemonameless/PaddleDetection_YOLOSeries/tree/develop/configs/yolov5)
+Please refer to[YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5)
 
 ### YOLOv6
 
-Please refer to[YOLOv6](https://github.com/nemonameless/PaddleDetection_YOLOSeries/tree/develop/configs/yolov6)
+Please refer to[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6)
 
 ### YOLOv7
 
-Please refer to[YOLOv7](https://github.com/nemonameless/PaddleDetection_YOLOSeries/tree/develop/configs/yolov7)
+Please refer to[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7)
 
 
 ## Rotating frame detection