diff --git a/paddlex/cv/datasets/easydata_cls.py b/paddlex/cv/datasets/easydata_cls.py
index ecf0f759c59a1ce9c5c24ce0369f83a3ebd14b94..c947206045d32ee2c22e3218aaa1e3dfc81db4c0 100644
--- a/paddlex/cv/datasets/easydata_cls.py
+++ b/paddlex/cv/datasets/easydata_cls.py
@@ -76,7 +76,7 @@ class EasyDataCls(ImageNet):
                     raise IOError(
                         'The image file {} is not exist!'.format(img_file))
                 with open(json_file, mode='r', \
-                          encoding=get_encoding(label_list)) as j:
+                          encoding=get_encoding(json_file)) as j:
                     json_info = json.load(j)
                 label = json_info['labels'][0]['name']
                 self.file_list.append([img_file, self.labels.index(label)])
diff --git a/paddlex/cv/datasets/easydata_det.py b/paddlex/cv/datasets/easydata_det.py
index d22cb3961c917a4c88bc355ed52a7fb272808642..87f5bac4d0b40844621b58bb824432846c22972c 100644
--- a/paddlex/cv/datasets/easydata_det.py
+++ b/paddlex/cv/datasets/easydata_det.py
@@ -96,7 +96,7 @@ class EasyDataDet(VOCDetection):
                     raise IOError(
                         'The image file {} is not exist!'.format(img_file))
                 with open(json_file, mode='r', \
-                          encoding=get_encoding(label_list)) as j:
+                          encoding=get_encoding(json_file)) as j:
                     json_info = json.load(j)
                 im_id = np.array([ct])
                 im = cv2.imread(img_file)
diff --git a/paddlex/cv/datasets/easydata_seg.py b/paddlex/cv/datasets/easydata_seg.py
index 7828524c209e544706cfc5e6cb2b4ae767a47ada..4e5f51135ad9ff24c0a6a4433b67c22032040bf3 100644
--- a/paddlex/cv/datasets/easydata_seg.py
+++ b/paddlex/cv/datasets/easydata_seg.py
@@ -79,7 +79,7 @@ class EasyDataSeg(Dataset):
                     raise IOError(
                         'The image file {} is not exist!'.format(img_file))
                 with open(json_file, mode='r', \
-                          encoding=get_encoding(label_list)) as j:
+                          encoding=get_encoding(json_file)) as j:
                     json_info = json.load(j)
                 im = cv2.imread(img_file)
                 im_w = im.shape[1]