diff --git a/docs/train/images/deeplab_predict.jpg b/docs/train/images/deeplab_predict.jpg
index bb71b963724e99de8a75509b311d301a50b003e4..8b4b6c00a35f2183f0de7ed7eed9e93e5fb60edb 100644
Binary files a/docs/train/images/deeplab_predict.jpg and b/docs/train/images/deeplab_predict.jpg differ
diff --git a/docs/train/prediction.md b/docs/train/prediction.md
index d5b00ecdda263bc883f87020d937561264c09470..977a93d4a55b31f3a842bd37cb65e0bcafad9548 100644
--- a/docs/train/prediction.md
+++ b/docs/train/prediction.md
@@ -77,7 +77,8 @@ import paddlex as pdx
 test_jpg = './deeplabv3p_mobilenetv2_voc/test.jpg'
 model = pdx.load_model('./deeplabv3p_mobilenetv2_voc')
 result = model.predict(test_jpg)
-pdx.seg.visualize(test_jpg, result, weight=0.6, save_dir='./')
+# 可视化结果存储在./visualized_test.jpg，见下图右(左图为原图)
+pdx.seg.visualize(test_jpg, result, weight=0.0, save_dir='./')
 ```
 
 在上述示例代码中，通过调用`paddlex.seg.visualize`可以对语义分割的预测结果进行可视化，可视化的结果保存在`save_dir`下，见下图。其中`weight`参数用于调整预测结果和原图结果融合展现时的权重，0.0时只展示预测结果mask的可视化，1.0时只展示原图可视化。