diff --git a/facelib/FANSegmentator.py b/facelib/FANSegmentator.py
index e8ff70f..fb7f4d5 100644
--- a/facelib/FANSegmentator.py
+++ b/facelib/FANSegmentator.py
@@ -10,7 +10,7 @@ from interact import interact as io
 from nnlib import nnlib
 
 """
-FANSegmentator is designed to segment faces aligned by 2DFAN-4 landmarks extractor.
+FANSegmentator is designed to exclude obstructions from faces such as hair, fingers, etc.
 
 Dataset used to train located in official DFL mega.nz folder
 https://mega.nz/#F!b9MzCK4B!zEAG9txu7uaRUjXz9PtBqg
diff --git a/models/Model_SAE/Model.py b/models/Model_SAE/Model.py
index 66c5b45..392002c 100644
--- a/models/Model_SAE/Model.py
+++ b/models/Model_SAE/Model.py
@@ -64,7 +64,7 @@ class SAEModel(ModelBase):
             self.options['e_ch_dims'] = np.clip ( io.input_int("Encoder dims per channel (21-85 ?:help skip:%d) : " % (default_e_ch_dims) , default_e_ch_dims, help_message="More encoder dims help to recognize more facial features, but require more VRAM. You can fine-tune model size to fit your GPU." ), 21, 85 )
             default_d_ch_dims = self.options['e_ch_dims'] // 2
             self.options['d_ch_dims'] = np.clip ( io.input_int("Decoder dims per channel (10-85 ?:help skip:%d) : " % (default_d_ch_dims) , default_d_ch_dims, help_message="More decoder dims help to get better details, but require more VRAM. You can fine-tune model size to fit your GPU." ), 10, 85 )
-            self.options['remove_gray_border'] = io.input_bool ("Remove gray border? (y/n, ?:help skip:n) : ", False, help_message="Removes gray border of predicted face, but requires more computing resources.")
+            #self.options['remove_gray_border'] = io.input_bool ("Remove gray border? (y/n, ?:help skip:n) : ", False, help_message="Removes gray border of predicted face, but requires more computing resources.")
         else:
             self.options['ae_dims'] = self.options.get('ae_dims', default_ae_dims)
             self.options['e_ch_dims'] = self.options.get('e_ch_dims', default_e_ch_dims)