labeled all convolutional layers

awentzonline · Mar 14, 2016 · 489f2e6 · 489f2e6
1 parent 2c3d6f3
commit 489f2e6
Showing 1 changed file with 7 additions and 7 deletions.
diff --git a/image_analogy/vgg16.py b/image_analogy/vgg16.py
@@ -38,37 +38,37 @@ def get_model(img_width, img_height, weights_path='vgg16_weights.h5', pool_mode=
     model.add(ZeroPadding2D((1, 1), input_shape=(3, img_height, img_width)))
     model.add(Convolution2D(64, 3, 3, activation='relu', name='conv1_1'))
     model.add(ZeroPadding2D((1, 1)))
-    model.add(Convolution2D(64, 3, 3, activation='relu'))
+    model.add(Convolution2D(64, 3, 3, activation='relu', name='conv1_2'))
     model.add(pool_class((2, 2), strides=(2, 2)))
 
     model.add(ZeroPadding2D((1, 1)))
     model.add(Convolution2D(128, 3, 3, activation='relu', name='conv2_1'))
     model.add(ZeroPadding2D((1, 1)))
-    model.add(Convolution2D(128, 3, 3, activation='relu'))
+    model.add(Convolution2D(128, 3, 3, activation='relu', name='conv2_2'))
     model.add(pool_class((2, 2), strides=(2, 2)))
 
     model.add(ZeroPadding2D((1, 1)))
     model.add(Convolution2D(256, 3, 3, activation='relu', name='conv3_1'))
     model.add(ZeroPadding2D((1, 1)))
-    model.add(Convolution2D(256, 3, 3, activation='relu'))
+    model.add(Convolution2D(256, 3, 3, activation='relu', name='conv3_2'))
     model.add(ZeroPadding2D((1, 1)))
-    model.add(Convolution2D(256, 3, 3, activation='relu'))
+    model.add(Convolution2D(256, 3, 3, activation='relu', name='conv3_3'))
     model.add(pool_class((2, 2), strides=(2, 2)))
 
     model.add(ZeroPadding2D((1, 1)))
     model.add(Convolution2D(512, 3, 3, activation='relu', name='conv4_1'))
     model.add(ZeroPadding2D((1, 1)))
     model.add(Convolution2D(512, 3, 3, activation='relu', name='conv4_2'))
     model.add(ZeroPadding2D((1, 1)))
-    model.add(Convolution2D(512, 3, 3, activation='relu'))
+    model.add(Convolution2D(512, 3, 3, activation='relu', name='conv4_3'))
     model.add(pool_class((2, 2), strides=(2, 2)))
 
     model.add(ZeroPadding2D((1, 1)))
     model.add(Convolution2D(512, 3, 3, activation='relu', name='conv5_1'))
     model.add(ZeroPadding2D((1, 1)))
-    model.add(Convolution2D(512, 3, 3, activation='relu'))
+    model.add(Convolution2D(512, 3, 3, activation='relu', name='conv5_2'))
     model.add(ZeroPadding2D((1, 1)))
-    model.add(Convolution2D(512, 3, 3, activation='relu'))
+    model.add(Convolution2D(512, 3, 3, activation='relu', name='conv5_3'))
     model.add(pool_class((2, 2), strides=(2, 2)))
 
     # load the weights of the VGG16 networks