diff --git a/ppocr/data/imaug/east_process.py b/ppocr/data/imaug/east_process.py
index b1d7a5e51939af981dd62c269c930f4bf9ba4179..598b88daee938a159f3e73d7296ede9ec6f4bfcd 100644
--- a/ppocr/data/imaug/east_process.py
+++ b/ppocr/data/imaug/east_process.py
@@ -11,7 +11,10 @@
 #WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 #See the License for the specific language governing permissions and
 #limitations under the License.
-
+"""
+This code is refered from: 
+https://github.com/songdejia/EAST/blob/master/data_utils.py
+"""
 import math
 import cv2
 import numpy as np
@@ -24,10 +27,10 @@ __all__ = ['EASTProcessTrain']
 
 class EASTProcessTrain(object):
     def __init__(self,
-                 image_shape = [512, 512],
-                 background_ratio = 0.125,
-                 min_crop_side_ratio = 0.1,
-                 min_text_size = 10,
+                 image_shape=[512, 512],
+                 background_ratio=0.125,
+                 min_crop_side_ratio=0.1,
+                 min_text_size=10,
                  **kwargs):
         self.input_size = image_shape[1]
         self.random_scale = np.array([0.5, 1, 2.0, 3.0])
@@ -282,12 +285,7 @@ class EASTProcessTrain(object):
                 1.0 / max(min(poly_h, poly_w), 1.0)
         return score_map, geo_map, training_mask
 
-    def crop_area(self,
-                  im,
-                  polys,
-                  tags,
-                  crop_background=False,
-                  max_tries=50):
+    def crop_area(self, im, polys, tags, crop_background=False, max_tries=50):
         """
         make random crop from the input image
         :param im:
@@ -436,4 +434,4 @@ class EASTProcessTrain(object):
         data['geo_map'] = geo_map
         data['training_mask'] = training_mask
         # print(im.shape, score_map.shape, geo_map.shape, training_mask.shape)
-        return data
\ No newline at end of file
+        return data
diff --git a/ppocr/data/imaug/sast_process.py b/ppocr/data/imaug/sast_process.py
index 1536dceb8ee5999226cfe7cf455d70e39b449530..08d03b194dcfab92ab59329857d4a1326531218e 100644
--- a/ppocr/data/imaug/sast_process.py
+++ b/ppocr/data/imaug/sast_process.py
@@ -11,7 +11,10 @@
 #WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 #See the License for the specific language governing permissions and
 #limitations under the License.
-
+"""
+This part code is refered from: 
+https://github.com/songdejia/EAST/blob/master/data_utils.py
+"""
 import math
 import cv2
 import numpy as np
diff --git a/ppocr/postprocess/db_postprocess.py b/ppocr/postprocess/db_postprocess.py
index d9c9869dfcd35cb9b491db826f3bff5f766723f4..27b428ef2e73c9abf81d3881b23979343c8595b2 100755
--- a/ppocr/postprocess/db_postprocess.py
+++ b/ppocr/postprocess/db_postprocess.py
@@ -11,7 +11,10 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-
+"""
+This code is refered from:
+https://github.com/WenmuZhou/DBNet.pytorch/blob/master/post_processing/seg_detector_representer.py
+"""
 from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
@@ -190,7 +193,8 @@ class DBPostProcess(object):
 
 
 class DistillationDBPostProcess(object):
-    def __init__(self, model_name=["student"],
+    def __init__(self,
+                 model_name=["student"],
                  key=None,
                  thresh=0.3,
                  box_thresh=0.6,
@@ -201,12 +205,13 @@ class DistillationDBPostProcess(object):
                  **kwargs):
         self.model_name = model_name
         self.key = key
-        self.post_process = DBPostProcess(thresh=thresh,
-                 box_thresh=box_thresh,
-                 max_candidates=max_candidates,
-                 unclip_ratio=unclip_ratio,
-                 use_dilation=use_dilation,
-                 score_mode=score_mode)
+        self.post_process = DBPostProcess(
+            thresh=thresh,
+            box_thresh=box_thresh,
+            max_candidates=max_candidates,
+            unclip_ratio=unclip_ratio,
+            use_dilation=use_dilation,
+            score_mode=score_mode)
 
     def __call__(self, predicts, shape_list):
         results = {}