Custom image size in Mobilenets v1 and v2 (#101)

* Size 224 is used for custom sizes in MobileNets * The warning message for undefined input shapes in MobileNets was updated
keras-team · Apr 15, 2019 · dda4997 · dda4997
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Showing 2 changed files with 10 additions and 10 deletions.
diff --git a/keras_applications/mobilenet.py b/keras_applications/mobilenet.py
@@ -203,11 +203,11 @@ def MobileNet(input_shape=None,
                              '`0.25`, `0.50`, `0.75` or `1.0` only.')
 
         if rows != cols or rows not in [128, 160, 192, 224]:
-            if rows is None:
-                rows = 224
-                warnings.warn('MobileNet shape is undefined.'
-                              ' Weights for input shape '
-                              '(224, 224) will be loaded.')
+            rows = 224
+            warnings.warn('`input_shape` is undefined or non-square, '
+                          'or `rows` is not in [128, 160, 192, 224]. '
+                          'Weights for input shape (224, 224) will be'
+                          ' loaded as the default.')
 
     if input_tensor is None:
         img_input = layers.Input(shape=input_shape)

diff --git a/keras_applications/mobilenet_v2.py b/keras_applications/mobilenet_v2.py
@@ -290,11 +290,11 @@ def MobileNetV2(input_shape=None,
                              '`1.0`, `1.3` or `1.4` only.')
 
         if rows != cols or rows not in [96, 128, 160, 192, 224]:
-            if rows is None:
-                rows = 224
-                warnings.warn('MobileNet shape is undefined.'
-                              ' Weights for input shape'
-                              '(224, 224) will be loaded.')
+            rows = 224
+            warnings.warn('`input_shape` is undefined or non-square, '
+                          'or `rows` is not in [96, 128, 160, 192, 224].'
+                          ' Weights for input shape (224, 224) will be'
+                          ' loaded as the default.')
 
     if input_tensor is None:
         img_input = layers.Input(shape=input_shape)