diff --git a/deploy/cpp_infer/tools/config.txt b/deploy/cpp_infer/tools/config.txt
index e185377e2f2c9cbd5c1d8ed09ba43df9c41c05d2..24e4ef0de7d844ba4bd6c11f2cba08766c0e5ddf 100644
--- a/deploy/cpp_infer/tools/config.txt
+++ b/deploy/cpp_infer/tools/config.txt
@@ -9,7 +9,7 @@ use_mkldnn 0
 max_side_len  960
 det_db_thresh  0.3
 det_db_box_thresh  0.5
-det_db_unclip_ratio  2.0
+det_db_unclip_ratio  1.6
 det_model_dir  ./inference/ch_ppocr_mobile_v2.0_det_infer/
 
 # cls config
diff --git a/doc/doc_ch/installation.md b/doc/doc_ch/installation.md
index fce151eb9fee567477c09eee211633f7377dddb3..7e7523b999aa6fdee9bbaa4fb388655e01c28c16 100644
--- a/doc/doc_ch/installation.md
+++ b/doc/doc_ch/installation.md
@@ -30,7 +30,7 @@ sudo nvidia-docker run --name ppocr -v $PWD:/paddle --shm-size=64G --network=hos
 sudo docker container exec -it ppocr /bin/bash
 ```
 
-**2. 安装PaddlePaddle Fluid v2.0**
+**2. 安装PaddlePaddle 2.0**
 ```
 pip3 install --upgrade pip
 
diff --git a/doc/doc_en/inference_en.md b/doc/doc_en/inference_en.md
index 6b745619c968f50e063ee78bd23c0a73f14f4511..aa3e0536cb6a4cb73f0388293ce72183c62e87a1 100755
--- a/doc/doc_en/inference_en.md
+++ b/doc/doc_en/inference_en.md
@@ -5,7 +5,8 @@ The inference model (the model saved by `paddle.jit.save`) is generally a solidi
 
 The model saved during the training process is the checkpoints model, which saves the parameters of the model and is mostly used to resume training.
 
-Compared with the checkpoints model, the inference model will additionally save the structural information of the model. It has superior performance in predicting in deployment and accelerating inferencing, is flexible and convenient, and is suitable for integration with actual systems. For more details, please refer to the document [Classification Framework](https://github.com/PaddlePaddle/PaddleClas/blob/master/docs/zh_CN/extension/paddle_inference.md).
+Compared with the checkpoints model, the inference model will additionally save the structural information of the model. Therefore, it is easier to deploy because the model structure and model parameters are already solidified in the inference model file, and is suitable for integration with actual systems.
+For more details, please refer to the document [Classification Framework](https://github.com/PaddlePaddle/PaddleClas/blob/release%2F2.0/docs/zh_CN/extension/paddle_mobile_inference.md).
 
 Next, we first introduce how to convert a trained model into an inference model, and then we will introduce text detection, text recognition, angle class, and the concatenation of them based on inference model.
 
diff --git a/doc/doc_en/installation_en.md b/doc/doc_en/installation_en.md
index 35c1881d12087e6509a68b504729d9ef20240e9c..dec384b2f27f8bb36ee67d8b040b532b30e0b028 100644
--- a/doc/doc_en/installation_en.md
+++ b/doc/doc_en/installation_en.md
@@ -33,7 +33,7 @@ You can also visit [DockerHub](https://hub.docker.com/r/paddlepaddle/paddle/tags
 sudo docker container exec -it ppocr /bin/bash
 ```
 
-**2. Install PaddlePaddle Fluid v2.0**
+**2. Install PaddlePaddle 2.0**
 ```
 pip3 install --upgrade pip
 
diff --git a/tools/infer/predict_det.py b/tools/infer/predict_det.py
index 077692afa84a745cb1b1fcb5b2c71f3dd5653013..26febf1c0da21f8b53114e2e236a5ea246e823a8 100755
--- a/tools/infer/predict_det.py
+++ b/tools/infer/predict_det.py
@@ -64,7 +64,7 @@ class TextDetector(object):
             postprocess_params["box_thresh"] = args.det_db_box_thresh
             postprocess_params["max_candidates"] = 1000
             postprocess_params["unclip_ratio"] = args.det_db_unclip_ratio
-            postprocess_params["use_dilation"] = True
+            postprocess_params["use_dilation"] = args.use_dialtion
         elif self.det_algorithm == "EAST":
             postprocess_params['name'] = 'EASTPostProcess'
             postprocess_params["score_thresh"] = args.det_east_score_thresh
diff --git a/tools/infer/utility.py b/tools/infer/utility.py
index 4171a29bdd4194813638b72f0aae015da48fbcb1..70e855c7437675ba499129ee219b64d91548a443 100755
--- a/tools/infer/utility.py
+++ b/tools/infer/utility.py
@@ -47,6 +47,8 @@ def parse_args():
     parser.add_argument("--det_db_box_thresh", type=float, default=0.5)
     parser.add_argument("--det_db_unclip_ratio", type=float, default=1.6)
     parser.add_argument("--max_batch_size", type=int, default=10)
+    parser.add_argument("--use_dialtion", type=bool, default=False)
+
     # EAST parmas
     parser.add_argument("--det_east_score_thresh", type=float, default=0.8)
     parser.add_argument("--det_east_cover_thresh", type=float, default=0.1)
@@ -123,6 +125,8 @@ def create_predictor(args, mode, logger):
             # cache 10 different shapes for mkldnn to avoid memory leak
             config.set_mkldnn_cache_capacity(10)
             config.enable_mkldnn()
+            #  TODO LDOUBLEV: fix mkldnn bug when bach_size  > 1
+            #config.set_mkldnn_op({'conv2d', 'depthwise_conv2d', 'pool2d', 'batch_norm'})
             args.rec_batch_num = 1
 
     # config.enable_memory_optim()