diff --git a/ppocr/modeling/architectures/det_model.py b/ppocr/modeling/architectures/det_model.py
index 5016546ac08d06d361d0352498ac853084e61bca..516413e9920b94d3b53f078fe4a73188a9435068 100755
--- a/ppocr/modeling/architectures/det_model.py
+++ b/ppocr/modeling/architectures/det_model.py
@@ -32,6 +32,7 @@ class DetModel(object):
             params (dict): the super parameters for detection module.
         """
         global_params = params['Global']
+        self.global_params = global_params
         self.algorithm = global_params['algorithm']
 
         backbone_params = deepcopy(params["Backbone"])
@@ -64,11 +65,23 @@ class DetModel(object):
         if mode == "train":
             if self.algorithm == "EAST":
                 score = fluid.layers.data(
-                    name='score', shape=[1, 128, 128], dtype='float32')
+                    name='score',
+                    shape=[
+                        1, int(image_shape[1] // 4), int(image_shape[2] // 4)
+                    ],
+                    dtype='float32')
                 geo = fluid.layers.data(
-                    name='geo', shape=[9, 128, 128], dtype='float32')
+                    name='geo',
+                    shape=[
+                        9, int(image_shape[1] // 4), int(image_shape[2] // 4)
+                    ],
+                    dtype='float32')
                 mask = fluid.layers.data(
-                    name='mask', shape=[1, 128, 128], dtype='float32')
+                    name='mask',
+                    shape=[
+                        1, int(image_shape[1] // 4), int(image_shape[2] // 4)
+                    ],
+                    dtype='float32')
                 feed_list = [image, score, geo, mask]
                 labels = {'score': score, 'geo': geo, 'mask': mask}
             elif self.algorithm == "DB":