diff --git a/README.md b/README.md
index 27109081251e6a846afaf5878d243c61cc440c9d..98820f51583ce99a789c09c17a7a46286ec6b42c 100644
--- a/README.md
+++ b/README.md
@@ -25,9 +25,18 @@
 * [数据集下载地址(百度网盘 Password: c680 )](https://pan.baidu.com/s/1H0YH8jMEXeIcubLEv0W_yw)   
 
 ### 2、脸部检测数据集   
+该项目采用的是开源数据集 WIDERFACE，其下载地址为 http://shuoyang1213.me/WIDERFACE/  
+```  
+@inproceedings{yang2016wider,
+	Author = {Yang, Shuo and Luo, Ping and Loy, Chen Change and Tang, Xiaoou},
+	Booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
+	Title = {WIDER FACE: A Face Detection Benchmark},
+	Year = {2016}}
+```  
+* [该项目制作的训练集的数据集下载地址(百度网盘 Password: r77x )](https://pan.baidu.com/s/1Jsm1qPPzAW46LRW5nUClzQ)   
 
-
-数据格式： size是全图分辨率， (x，y) 是目标物体中心对于全图的归一化坐标，w,h是目标物体边界框对于全图的归一化宽、高。
+### 数据格式  
+size是全图分辨率， (x，y) 是目标物体中心对于全图的归一化坐标，w,h是目标物体边界框对于全图的归一化宽、高。   
 
 ```  
 dw = 1./(size[0])  
@@ -53,7 +62,9 @@ Contextual Attention for Hand Detection in the Wild. S. Narasimhaswamy, Z. Wei,
 ### 1、手部检测预训练模型    
 * [预训练模型下载地址(百度网盘 Password: 7mk0 )](https://pan.baidu.com/s/1hqzvz0MeFX0EdpWXUV6aFg)     
 
-### 2、脸部检测预训练模型  
+### 2、脸部检测预训练模型    
+* [预训练模型下载地址(百度网盘 Password: l2a3 )](https://pan.baidu.com/s/1xVtZUMD94DiT9FQQ66xG1A)     
+
 
 ## 项目使用方法     
 
diff --git a/show_yolo_anno.py b/show_yolo_anno.py
index e1dc6038a8c2548d4c27dfcf20bda0044b102c93..3b65bd3260f4078a2c6844edeef1ec594abea06b 100644
--- a/show_yolo_anno.py
+++ b/show_yolo_anno.py
@@ -9,8 +9,11 @@ import numpy as np
 
 if __name__ == "__main__":
 
-    path='./datasets_fusion_hand_train/anno/train.txt'
-    path_voc_names = './cfg/hand.names'
+    # path='./datasets_fusion_hand_train/anno/train.txt'
+    # path_voc_names = './cfg/hand.names'
+
+    path='./yolo_widerface_open_train/anno/train.txt'
+    path_voc_names = './cfg/face.names'
 
     with open(path_voc_names, 'r') as f:
         label_map = f.readlines()