diff --git a/official/cv/yolov3_resnet18/README.md b/official/cv/yolov3_resnet18/README.md
index 1e0a3244f1846481164904f9c792d9210b9cad66..46281a40f148790e388644b73c7ad60a2ebfcfac 100644
--- a/official/cv/yolov3_resnet18/README.md
+++ b/official/cv/yolov3_resnet18/README.md
@@ -41,7 +41,7 @@ And we use ResNet18 as the backbone of YOLOv3_ResNet18. The architecture of ResN
 
 Note that you can run the scripts based on the dataset mentioned in original paper or widely used in relevant domain/network architecture. In the following sections, we will introduce how to run the scripts using the related dataset below.
 
-Dataset used: [COCO2017](<http://images.cocodataset.org/>)
+Dataset used: [COCO2017](<http://images.cocodataset.org/>), labeling uses unpublished face, human body labeling data, temporarily does not provide public reproduction, only provides pre-training [checkpoint](https://download.mindspore.cn/model_zoo/r1.2/yolov3resnet18_ascend_v120_coco2017_official_cv_bs32_acc86/yolov3resnet18_ascend_v120_coco2017_official_cv_bs32_acc86.ckpt).
 
 - Dataset size锛�19G
     - Train锛�18G锛�118000 images  
diff --git a/official/cv/yolov3_resnet18/README_CN.md b/official/cv/yolov3_resnet18/README_CN.md
index c7d0c30f7b4e6c694827084b5d4bae932f93992f..6b0719df85514e8c86e3603e9932a0a9b26338db 100644
--- a/official/cv/yolov3_resnet18/README_CN.md
+++ b/official/cv/yolov3_resnet18/README_CN.md
@@ -43,7 +43,7 @@ YOLOv3鏁翠綋缃戠粶鏋舵瀯濡備笅锛�
 
 # 鏁版嵁闆�
 
-浣跨敤鐨勬暟鎹泦锛歔COCO 2017](<http://images.cocodataset.org/>)
+浣跨敤鐨勬暟鎹泦锛歔COCO 2017](<http://images.cocodataset.org/>)锛屾爣娉ㄤ娇鐢ㄦ湭鍏紑鐨勪汉鑴�/浜轰綋鏍囨敞鏁版嵁锛屾殏鏃朵笉鎻愪緵鍏紑澶嶇幇锛屼粎鎻愪緵棰勮缁僛checkpoint](https://download.mindspore.cn/model_zoo/r1.2/yolov3resnet18_ascend_v120_coco2017_official_cv_bs32_acc86/yolov3resnet18_ascend_v120_coco2017_official_cv_bs32_acc86.ckpt).
 
 - 鏁版嵁闆嗗ぇ灏忥細19 GB
     - 璁粌闆嗭細18 GB锛�118000寮犲浘鐗�