diff --git a/slim/prune/README.md b/slim/prune/README.md
index d000c329b066e7a09dee1b33a2fe96ec568d6e71..2b4eadc454b9a444a003d4df39e4f39600a70e14 100644
--- a/slim/prune/README.md
+++ b/slim/prune/README.md
@@ -6,7 +6,7 @@
 
 在检测库中，可以直接调用`PaddleDetection/slim/prune/prune.py`脚本实现剪裁，在该脚本中调用了PaddleSlim的[paddleslim.prune.Pruner](https://paddlepaddle.github.io/PaddleSlim/api/prune_api/#Pruner)接口。
 
-该教程中所示操作，如无特殊说明，均在`PaddleDetection/slim/prune/`路径下执行。
+该教程中所示操作，如无特殊说明，均在`PaddleDetection/`路径下执行。
 
 已发布裁剪模型见[压缩模型库](../README.md)
 
@@ -40,8 +40,8 @@
 通过以下命令查看当前模型的所有参数：
 
 ```
-python prune.py \
--c ../../configs/yolov3_mobilenet_v1_voc.yml \
+python slim/prune/prune.py \
+-c ./configs/yolov3_mobilenet_v1_voc.yml \
 --print_params
 ```
 
@@ -56,8 +56,8 @@ python prune.py \
 使用`prune.py`启动裁剪任务时，通过`--pruned_params`选项指定待裁剪的参数名称列表，参数名之间用空格分隔，通过`--pruned_ratios`选项指定各个参数被裁掉的比例。
 
 ```
-python prune.py \
--c ../../configs/yolov3_mobilenet_v1_voc.yml \
+python slim/prune/prune.py \
+-c ./configs/yolov3_mobilenet_v1_voc.yml \
 --pruned_params "yolo_block.0.0.0.conv.weights,yolo_block.0.0.1.conv.weights,yolo_block.0.1.0.conv.weights" \
 --pruned_ratios="0.2,0.3,0.4"
 ```
@@ -67,8 +67,8 @@ python prune.py \
 训练剪裁任务完成后，可通过`eval.py`评估剪裁模型精度，通过`--pruned_params`和`--pruned_ratios`指定裁剪的参数名称列表和各参数裁剪比例。
 
 ```
-python eval.py \
--c ../../configs/yolov3_mobilenet_v1_voc.yml \
+python slim/prune/eval.py \
+-c ./configs/yolov3_mobilenet_v1_voc.yml \
 --pruned_params "yolo_block.0.0.0.conv.weights,yolo_block.0.0.1.conv.weights,yolo_block.0.1.0.conv.weights" \
 --pruned_ratios="0.2,0.3,0.4" \
 -o weights=output/yolov3_mobilenet_v1_voc/model_final
@@ -79,8 +79,8 @@ python eval.py \
 如果想要将剪裁模型接入到C++预测库或者Serving服务，可通过`export_model.py`导出该模型。
 
 ```
-python export_model.py \
--c ../../configs/yolov3_mobilenet_v1_voc.yml \
+python slim/prune/export_model.py \
+-c ./configs/yolov3_mobilenet_v1_voc.yml \
 --pruned_params "yolo_block.0.0.0.conv.weights,yolo_block.0.0.1.conv.weights,yolo_block.0.1.0.conv.weights" \
 --pruned_ratios="0.2,0.3,0.4" \
 -o weights=output/yolov3_mobilenet_v1_voc/model_final
@@ -103,13 +103,13 @@ python export_model.py \
 
 ```
 # demo for faster_rcnn_r50
-python prune.py -c ../../configs/faster_rcnn_r50_1x.yml --pruned_params "res4f_branch2b_weights,res4f_branch2a_weights" --pruned_ratios="0.3,0.4" --eval
+python slim/prune/prune.py -c ./configs/faster_rcnn_r50_1x.yml --pruned_params "res4f_branch2b_weights,res4f_branch2a_weights" --pruned_ratios="0.3,0.4" --eval
 ```
 
 对[mask_rcnn_r50](../../configs/mask_rcnn_r50_1x.yml)剪裁示例如下：
 
 ```
 # demo for mask_rcnn_r50
-python prune.py -c ../../configs/mask_rcnn_r50_1x.yml --pruned_params "res4f_branch2b_weights,res4f_branch2a_weights" --pruned_ratios="0.2,0.3" --eval
+python slim/prune/prune.py -c ./configs/mask_rcnn_r50_1x.yml --pruned_params "res4f_branch2b_weights,res4f_branch2a_weights" --pruned_ratios="0.2,0.3" --eval
 
 ```