diff --git a/configs/det/det_r50_vd_sast_icdar15.yml b/configs/det/det_r50_vd_sast_icdar15.yml
index dbfcefca964e73d42298fbbbc1e654b3bd809c77..674de7fbf250bd712b46e04d42ff0022029fd095 100755
--- a/configs/det/det_r50_vd_sast_icdar15.yml
+++ b/configs/det/det_r50_vd_sast_icdar15.yml
@@ -8,7 +8,7 @@ Global:
   # evaluation is run every 5000 iterations after the 4000th iteration
   eval_batch_step: [4000, 5000]
   cal_metric_during_train: False
-  pretrained_model: ./pretrain_models/ResNet50_vd_ssld_pretrained/
+  pretrained_model: ./pretrain_models/ResNet50_vd_ssld_pretrained
   checkpoints:
   save_inference_dir:
   use_visualdl: False
diff --git a/configs/det/det_r50_vd_sast_totaltext.yml b/configs/det/det_r50_vd_sast_totaltext.yml
index 88dd31f3c21b184d956ad718dae808bb6054532e..44a0766b1bf2790a9633602bc637932529046e34 100755
--- a/configs/det/det_r50_vd_sast_totaltext.yml
+++ b/configs/det/det_r50_vd_sast_totaltext.yml
@@ -8,7 +8,7 @@ Global:
   # evaluation is run every 5000 iterations after the 4000th iteration
   eval_batch_step: [4000, 5000]
   cal_metric_during_train: False
-  pretrained_model: ./pretrain_models/ResNet50_vd_ssld_pretrained/
+  pretrained_model: ./pretrain_models/ResNet50_vd_ssld_pretrained
   checkpoints: 
   save_inference_dir:
   use_visualdl: False
diff --git a/test_tipc/prepare.sh b/test_tipc/prepare.sh
index f3ad242538a9471af237c804eae343da06e2b9dd..9b63bf5b20cd08b4ab08c17d7fd84f53feb93967 100644
--- a/test_tipc/prepare.sh
+++ b/test_tipc/prepare.sh
@@ -87,7 +87,8 @@ elif [ ${MODE} = "whole_infer" ];then
         rm -rf ./train_data/icdar2015
         wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate
         wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar --no-check-certificate
-        cd ./inference && tar xf ${eval_model_name}.tar && tar xf ch_det_data_50.tar && cd ../
+        wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate
+        cd ./inference && tar xf ${eval_model_name}.tar && tar xf ch_det_data_50.tar && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && cd ../
     elif [ ${model_name} = "ocr_server_det" ]; then
         wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_det_train.tar --no-check-certificate
         wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar  --no-check-certificate
diff --git a/tools/infer/utility.py b/tools/infer/utility.py
index 58170e393cdc9d8441408a89c84aa6f88d683db3..98bf0362f6842cb70490e6817ef53fe39109f406 100755
--- a/tools/infer/utility.py
+++ b/tools/infer/utility.py
@@ -205,7 +205,7 @@ def create_predictor(args, mode, logger):
                     "nearest_interp_v2_0.tmp_0": [1, 256, 2, 2]
                 }
                 max_input_shape = {
-                    "x": [1, 3, 2000, 2000],
+                    "x": [1, 3, 1280, 1280],
                     "conv2d_92.tmp_0": [1, 120, 400, 400],
                     "conv2d_91.tmp_0": [1, 24, 200, 200],
                     "conv2d_59.tmp_0": [1, 96, 400, 400],
@@ -255,16 +255,16 @@ def create_predictor(args, mode, logger):
                 opt_input_shape.update(opt_pact_shape)
             elif mode == "rec":
                 min_input_shape = {"x": [1, 3, 32, 10]}
-                max_input_shape = {"x": [args.rec_batch_num, 3, 32, 2000]}
+                max_input_shape = {"x": [args.rec_batch_num, 3, 32, 1024]}
                 opt_input_shape = {"x": [args.rec_batch_num, 3, 32, 320]}
             elif mode == "cls":
                 min_input_shape = {"x": [1, 3, 48, 10]}
-                max_input_shape = {"x": [args.rec_batch_num, 3, 48, 2000]}
+                max_input_shape = {"x": [args.rec_batch_num, 3, 48, 1024]}
                 opt_input_shape = {"x": [args.rec_batch_num, 3, 48, 320]}
             else:
                 min_input_shape = {"x": [1, 3, 10, 10]}
-                max_input_shape = {"x": [1, 3, 1000, 1000]}
-                opt_input_shape = {"x": [1, 3, 500, 500]}
+                max_input_shape = {"x": [1, 3, 512, 512]}
+                opt_input_shape = {"x": [1, 3, 256, 256]}
             config.set_trt_dynamic_shape_info(min_input_shape, max_input_shape,
                                               opt_input_shape)