diff --git a/models/Model_UFM/Model.py b/models/Model_UFM/Model.py
index 323d675..030ff0d 100644
--- a/models/Model_UFM/Model.py
+++ b/models/Model_UFM/Model.py
@@ -91,11 +91,11 @@ class UFMModel(ModelBase):
         pred_src_dst = self.decoder_src(warped_dst_code)
         pred_src_dstm = self.decoder_srcm(warped_dst_code)
         
-        target_srcm_blurred = tf_gaussian_blur(4.0)(target_srcm)        
+        target_srcm_blurred = tf_gaussian_blur(resolution // 32)(target_srcm)        
         target_srcm_sigm = target_srcm_blurred / 2.0 + 0.5
         target_srcm_anti_sigm = 1.0 - target_srcm_sigm
 
-        target_dstm_blurred = tf_gaussian_blur(4.0)(target_dstm)
+        target_dstm_blurred = tf_gaussian_blur(resolution // 32)(target_dstm)
         target_dstm_sigm = target_dstm_blurred / 2.0 + 0.5
         target_dstm_anti_sigm = 1.0 - target_dstm_sigm
         
@@ -249,7 +249,7 @@ class UFMModel(ModelBase):
     @staticmethod
     def EncFlow(ngf=64, num_downs=4, lowest_dense=512):
         exec (nnlib.import_all(), locals(), globals())
-
+        
         use_bias = True
         def XNormalization(x):
             return InstanceNormalization (axis=3, gamma_initializer=RandomNormal(1., 0.02))(x)
@@ -264,7 +264,7 @@ class UFMModel(ModelBase):
             for i in range(num_downs):
                 x = LeakyReLU(0.1)(XNormalization(Conv2D( min(ngf* (2**i), ngf*8) , 5, 2, 'same')(x)))
                 
-                if i == num_downs-1:
+                if i == 3:
                     x_shape = K.int_shape(x)[1:]
                     x = Reshape(x_shape)(Dense( np.prod(x_shape) )(Dense(lowest_dense)(Flatten()(x))))
                 result += [x]