diff --git a/02.recognize_digits/README.cn.md b/02.recognize_digits/README.cn.md
index a1488b003d21468602e0d681f6d12a2c475fbbd7..0c88a4f6c0a50ac54aacd09be03b89889d68343d 100644
--- a/02.recognize_digits/README.cn.md
+++ b/02.recognize_digits/README.cn.md
@@ -524,7 +524,7 @@ Test with Epoch 0, avg_cost: 0.053097883707459624, acc: 0.9822850318471338
 
 ### 生成预测输入数据
 
-`infer_3.png` 是数字 3 的一个示例图像。把它变成一个 numpy 数组以匹配数据feed格式。
+[infer_3.png](https://github.com/PaddlePaddle/book/blob/develop/02.recognize_digits/image/infer_3.png) 是数字 3 的一个示例图像。把它变成一个 numpy 数组以匹配数据feed格式。
 
 ```python
 def load_image(file):
@@ -558,7 +558,7 @@ with fluid.scope_guard(inference_scope):
     lab = numpy.argsort(results)
 
     # 打印 infer_3.png 这张图片的预测结果
-    img=Image.open('image/infer_3.png')
+    img=Image.open(cur_dir + 'image/infer_3.png')
     plt.imshow(img)
     print("Inference result of image/infer_3.png is: %d" % lab[0][0][-1])
 ```
diff --git a/02.recognize_digits/README.md b/02.recognize_digits/README.md
index 7fc23137fbaf2e750fbf4a28b1507d6b44ff2092..1776b1dc89366fcd36001e3ddebdc192e2131e4e 100644
--- a/02.recognize_digits/README.md
+++ b/02.recognize_digits/README.md
@@ -508,7 +508,7 @@ You can use trained model to classify handwriting pictures of digits. The progra
 
 ### Generate input data to be inferred
 
-`infer_3.png` is an example picture of number 3. Transform it into a numpy to match feed data format
+[infer_3.png](https://github.com/PaddlePaddle/book/blob/develop/02.recognize_digits/image/infer_3.png) is an example picture of number 3. Transform it into a numpy to match feed data format
 
 
 ```python
@@ -547,7 +547,7 @@ with fluid.scope_guard(inference_scope):
     lab = numpy.argsort(results)
 
     # Print prediction result of  infer_3.png
-    img=Image.open('image/infer_3.png')
+    img=Image.open(cur_dir + 'image/infer_3.png')
     plt.imshow(img)
     print("Inference result of image/infer_3.png is: %d" % lab[0][0][-1])
 ```
diff --git a/02.recognize_digits/index.cn.html b/02.recognize_digits/index.cn.html
index 1fb5d5cb06cfceec6f5c75e99a9d4f7ea06eedd6..3417fa5b326fa8e3515dc6c61da670d0220336eb 100644
--- a/02.recognize_digits/index.cn.html
+++ b/02.recognize_digits/index.cn.html
@@ -566,7 +566,7 @@ Test with Epoch 0, avg_cost: 0.053097883707459624, acc: 0.9822850318471338
 
 ### 生成预测输入数据
 
-`infer_3.png` 是数字 3 的一个示例图像。把它变成一个 numpy 数组以匹配数据feed格式。
+[infer_3.png](https://github.com/PaddlePaddle/book/blob/develop/02.recognize_digits/image/infer_3.png) 是数字 3 的一个示例图像。把它变成一个 numpy 数组以匹配数据feed格式。
 
 ```python
 def load_image(file):
@@ -600,7 +600,7 @@ with fluid.scope_guard(inference_scope):
     lab = numpy.argsort(results)
 
     # 打印 infer_3.png 这张图片的预测结果
-    img=Image.open('image/infer_3.png')
+    img=Image.open(cur_dir + 'image/infer_3.png')
     plt.imshow(img)
     print("Inference result of image/infer_3.png is: %d" % lab[0][0][-1])
 ```
diff --git a/02.recognize_digits/index.html b/02.recognize_digits/index.html
index bf428731efa54ac76f205ff79840d1cfcd211670..a09d04b01a43fd504d7565b620eaabfd0f21f2a6 100644
--- a/02.recognize_digits/index.html
+++ b/02.recognize_digits/index.html
@@ -550,7 +550,7 @@ You can use trained model to classify handwriting pictures of digits. The progra
 
 ### Generate input data to be inferred
 
-`infer_3.png` is an example picture of number 3. Transform it into a numpy to match feed data format
+[infer_3.png](https://github.com/PaddlePaddle/book/blob/develop/02.recognize_digits/image/infer_3.png) is an example picture of number 3. Transform it into a numpy to match feed data format
 
 
 ```python
@@ -589,7 +589,7 @@ with fluid.scope_guard(inference_scope):
     lab = numpy.argsort(results)
 
     # Print prediction result of  infer_3.png
-    img=Image.open('image/infer_3.png')
+    img=Image.open(cur_dir + 'image/infer_3.png')
     plt.imshow(img)
     print("Inference result of image/infer_3.png is: %d" % lab[0][0][-1])
 ```