diff --git a/model_zoo/official/cv/maskrcnn/README.md b/model_zoo/official/cv/maskrcnn/README.md
index 65c66596a98..36fcbd15897 100644
--- a/model_zoo/official/cv/maskrcnn/README.md
+++ b/model_zoo/official/cv/maskrcnn/README.md
@@ -94,7 +94,8 @@ sh run_distribute_train.sh [MINDSPORE_HCCL_CONFIG_PATH] [PRETRAINED_MODEL]
 sh run_standalone_train.sh [PRETRAINED_MODEL]
 ```
  
-> About rank_table.json, you can refer to the [distributed training tutorial](https://www.mindspore.cn/tutorial/en/master/advanced_use/distributed_training.html).
+> hccl.json which is specified by MINDSPORE_HCCL_CONFIG_PATH is needed when you are running a distribute task. You can generate it by using the [hccl_tools](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/utils/hccl_tools).
+> As for PRETRAINED_MODEL，if not set, the model will be trained from the very beginning.Ready-made pretrained_models are not available now. Stay tuned.
 
 #### Result
  
@@ -118,10 +119,10 @@ epoch: 12 step: 7393 ,rpn_loss: 0.06482, rcnn_loss: 0.47681, rpn_cls_loss: 0.047
  
 ```
 # infer
-sh run_eval.sh [VALIDATION_DATASET_PATH] [CHECKPOINT_PATH]
+sh run_eval.sh [VALIDATION_ANN_FILE_JSON] [CHECKPOINT_PATH]
 ```
- 
-> checkpoint can be produced in training process.
+> As for the COCO2017 dataset, VALIDATION_ANN_FILE_JSON is refer to the annotations/instances_val2017.json in the dataset directory.  
+> checkpoint can be produced and saved in training process, whose folder name begins with "train/checkpoint" or "train_parallel*/checkpoint".
 
 #### Result