diff --git a/tools/infer/predict_rec.py b/tools/infer/predict_rec.py
index bb4a31706471b9b1745519ac9f390d01b60d5d44..5a9d4fda3d53a9759d623b6374919e1c7d1df886 100755
--- a/tools/infer/predict_rec.py
+++ b/tools/infer/predict_rec.py
@@ -277,7 +277,7 @@ def main(args):
     if args.warmup:
         img = np.random.uniform(0, 255, [32, 320, 3]).astype(np.uint8)
         for i in range(2):
-            res = text_recognizer([img])
+            res = text_recognizer([img] * int(args.rec_batch_num))
 
     for image_file in image_file_list:
         img, flag = check_and_read_gif(image_file)
diff --git a/tools/infer/utility.py b/tools/infer/utility.py
index 93b54505c36e5f18913bad8b70d49b4f28334477..1c82280099f17f6d3bf848669e47439505f10576 100755
--- a/tools/infer/utility.py
+++ b/tools/infer/utility.py
@@ -231,13 +231,13 @@ def create_predictor(args, mode, logger):
             max_input_shape.update(max_pact_shape)
             opt_input_shape.update(opt_pact_shape)
         elif mode == "rec":
-            min_input_shape = {"x": [1, 3, 32, 10]}
+            min_input_shape = {"x": [args.rec_batch_num, 3, 32, 10]}
             max_input_shape = {"x": [args.rec_batch_num, 3, 32, 2000]}
-            opt_input_shape = {"x": [512, 3, 32, 320]}
+            opt_input_shape = {"x": [args.rec_batch_num, 3, 32, 320]}
         elif mode == "cls":
-            min_input_shape = {"x": [1, 3, 48, 10]}
+            min_input_shape = {"x": [args.rec_batch_num, 3, 48, 10]}
             max_input_shape = {"x": [args.rec_batch_num, 3, 48, 2000]}
-            opt_input_shape = {"x": [512, 3, 48, 320]}
+            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]}