Merge pull request #1 from slothkong/master

Fixed argument that broke due to Keras update and improved zero mean subtract module

Author: anujshah1003

transfer_learning_test.py

@@ -2,7 +2,8 @@
 from vgg16 import VGG16
 from resnet50 import ResNet50
 from keras.preprocessing import image
-from imagenet_utils import preprocess_input, decode_predictions
+from keras.applications.imagenet_utils import preprocess_input
+from imagenet_utils import decode_predictions
 
 model = VGG16(include_top=True, weights='imagenet')
 

transfer_learning_vgg16_custom_data.py

@@ -4,7 +4,8 @@
 import time
 from vgg16 import VGG16
 from keras.preprocessing import image
-from imagenet_utils import preprocess_input, decode_predictions
+from keras.applications.imagenet_utils import preprocess_input
+from imagenet_utils import decode_predictions
 from keras.layers import Dense, Activation, Flatten
 from keras.layers import merge, Input
 from keras.models import Model
@@ -33,7 +34,7 @@
 	img_list=os.listdir(data_path+'/'+ dataset)
 	print ('Loaded the images of dataset-'+'{}\n'.format(dataset))
 	for img in img_list:
-		img_path = data_path + '/'+ dataset + '/'+ img 
+		img_path = data_path + '/'+ dataset + '/'+ img
 		img = image.load_img(img_path, target_size=(224, 224))
 		x = image.img_to_array(img)
 		x = np.expand_dims(x, axis=0)
@@ -62,7 +63,7 @@
 labels[606:]=3
 
 names = ['cats','dogs','horses','humans']
-	  
+
 # convert class labels to on-hot encoding
 Y = np_utils.to_categorical(labels, num_classes)
 

vgg16.py

@@ -99,7 +99,7 @@ def VGG16(include_top=True, weights='imagenet',
                                       default_size=224,
                                       min_size=48,
                                       data_format=K.image_data_format(),
-                                      include_top=include_top)
+                                      require_flatten=include_top)
 
     if input_tensor is None:
         img_input = Input(shape=input_shape)