diff --git a/deploy/cpp_infer/src/ocr_rec.cpp b/deploy/cpp_infer/src/ocr_rec.cpp
index fa1e44ff7a62f178d64b2494f4b769e8618128ac..76873dad3c871a027c7fccd88409227639edefdf 100644
--- a/deploy/cpp_infer/src/ocr_rec.cpp
+++ b/deploy/cpp_infer/src/ocr_rec.cpp
@@ -76,7 +76,7 @@ void CRNNRecognizer::Run(std::vector<std::vector<std::vector<int>>> boxes,
           float(*std::max_element(&predict_batch[n * predict_shape[2]],
                                   &predict_batch[(n + 1) * predict_shape[2]]));
 
-      if (argmax_idx > 0 && (!(i > 0 && argmax_idx == last_index))) {
+      if (argmax_idx > 0 && (!(n > 0 && argmax_idx == last_index))) {
         score += max_value;
         count += 1;
         str_res.push_back(label_list_[argmax_idx]);
diff --git a/ppocr/data/imaug/make_shrink_map.py b/ppocr/data/imaug/make_shrink_map.py
index e8e4d43f10fe5e673f9038194c5c83c396faec73..ccdcd015d29a590a6ad5a2add8c285ed256bfb50 100644
--- a/ppocr/data/imaug/make_shrink_map.py
+++ b/ppocr/data/imaug/make_shrink_map.py
@@ -32,7 +32,6 @@ class MakeShrinkMap(object):
         text_polys, ignore_tags = self.validate_polygons(text_polys,
                                                          ignore_tags, h, w)
         gt = np.zeros((h, w), dtype=np.float32)
-        # gt = np.zeros((1, h, w), dtype=np.float32)
         mask = np.ones((h, w), dtype=np.float32)
         for i in range(len(text_polys)):
             polygon = text_polys[i]
@@ -51,7 +50,8 @@ class MakeShrinkMap(object):
                 shrinked = []
 
                 # Increase the shrink ratio every time we get multiple polygon returned back 
-                possible_ratios = np.arange(self.shrink_ratio, 1, self.shrink_ratio)
+                possible_ratios = np.arange(self.shrink_ratio, 1,
+                                            self.shrink_ratio)
                 np.append(possible_ratios, 1)
                 # print(possible_ratios)
                 for ratio in possible_ratios:
@@ -104,4 +104,4 @@ class MakeShrinkMap(object):
             edge += (polygon[next_index, 0] - polygon[i, 0]) * (
                 polygon[next_index, 1] - polygon[i, 1])
 
-        return edge / 2.
\ No newline at end of file
+        return edge / 2.
diff --git a/tools/infer/predict_det.py b/tools/infer/predict_det.py
index 76c6a4478ae37e650901c8b8704e15e4a94911c4..b14825bdd8bad55b709d84bdf6df6575d90c7d95 100755
--- a/tools/infer/predict_det.py
+++ b/tools/infer/predict_det.py
@@ -39,10 +39,7 @@ class TextDetector(object):
         self.args = args
         self.det_algorithm = args.det_algorithm
         pre_process_list = [{
-            'DetResizeForTest': {
-                'limit_side_len': args.det_limit_side_len,
-                'limit_type': args.det_limit_type
-            }
+            'DetResizeForTest': None
         }, {
             'NormalizeImage': {
                 'std': [0.229, 0.224, 0.225],
diff --git a/tools/infer_det.py b/tools/infer_det.py
index d890970ec14c25815fed8366d9257495f7485e0d..913d617defea18fe881e6fd2212b1df20f7d26d3 100755
--- a/tools/infer_det.py
+++ b/tools/infer_det.py
@@ -97,7 +97,7 @@ def main():
             preds = model(images)
             post_result = post_process_class(preds, shape_list)
             boxes = post_result[0]['points']
-            # write resule
+            # write result
             dt_boxes_json = []
             for box in boxes:
                 tmp_json = {"transcription": ""}