diff --git a/ppstructure/vqa/README.md b/ppstructure/vqa/README.md
index 66cc5b933b72beaa1c8beb548a4f1baffc91a531..3bfca3049731534aaa6799d79ec29af7f4219078 100644
--- a/ppstructure/vqa/README.md
+++ b/ppstructure/vqa/README.md
@@ -203,7 +203,7 @@ First use the `tools/infer_vqa_token_ser.py` script to complete the prediction o
 
 ```shell
 export CUDA_VISIBLE_DEVICES=0
-python3 tools/eval_with_label_end2end.py --gt_json_path XFUND/zh_val/xfun_normalize_val.json --pred_json_path output_res/infer_results.txt
+python3 ppstructure/vqa/tools/eval_with_label_end2end.py --gt_json_path XFUND/zh_val/xfun_normalize_val.json --pred_json_path output_res/infer_results.txt
 ````
 
 <a name="53"></a>
@@ -247,7 +247,7 @@ Finally, `precision`, `recall`, `hmean` and other indicators will be printed
 Use the following command to complete the series prediction of `OCR engine + SER + RE`, taking the pretrained SER and RE models as an example:
 ```shell
 export CUDA_VISIBLE_DEVICES=0
-python3 tools/infer_vqa_token_ser_re.py -c configs/vqa/re/layoutxlm.yml -o Architecture.Backbone.checkpoints=pretrain/re_LayoutXLM_xfun_zh/Global.infer_img=doc/vqa/input/zh_val_21.jpg -c_ser configs/vqa/ser/layoutxlm. yml -o_ser Architecture.Backbone.checkpoints=pretrain/ser_LayoutXLM_xfun_zh/
+python3 tools/infer_vqa_token_ser_re.py -c configs/vqa/re/layoutxlm.yml -o Architecture.Backbone.checkpoints=pretrain/re_LayoutXLM_xfun_zh/ Global.infer_img=doc/vqa/input/zh_val_21.jpg -c_ser configs/vqa/ser/layoutxlm. yml -o_ser Architecture.Backbone.checkpoints=pretrain/ser_LayoutXLM_xfun_zh/
 ````
 
 Finally, the prediction result visualization image and the prediction result text file will be saved in the directory configured by the `config.Global.save_res_path` field. The prediction result text file is named `infer_results.txt`.
diff --git a/ppstructure/vqa/README_ch.md b/ppstructure/vqa/README_ch.md
index b677dc07bce6c1a752d753b6a1c538b4d3f99271..abf8e4883c25d3092baa5d1fcc86d1571d04ac93 100644
--- a/ppstructure/vqa/README_ch.md
+++ b/ppstructure/vqa/README_ch.md
@@ -198,7 +198,7 @@ CUDA_VISIBLE_DEVICES=0 python3 tools/infer_vqa_token_ser.py -c configs/vqa/ser/l
 
 ```shell
 export CUDA_VISIBLE_DEVICES=0
-python3 tools/eval_with_label_end2end.py --gt_json_path XFUND/zh_val/xfun_normalize_val.json  --pred_json_path output_res/infer_results.txt
+python3 ppstructure/vqa/tools/eval_with_label_end2end.py --gt_json_path XFUND/zh_val/xfun_normalize_val.json  --pred_json_path output_res/infer_results.txt
 ```
 
 ### 5.3 RE