Advertisement
Not a member of Pastebin yet?
Sign Up,
it unlocks many cool features!
- model = Sequential()
- model.add(ZeroPadding2D((1,1),input_shape=(224,224, 3)))
- model.add(Convolution2D(64, (3, 3), activation='relu'))
- model.add(ZeroPadding2D((1,1)))
- model.add(Convolution2D(64, (3, 3), activation='relu'))
- model.add(MaxPooling2D((2,2), strides=(2,2)))
- model.add(ZeroPadding2D((1,1)))
- model.add(Convolution2D(128, (3, 3), activation='relu'))
- model.add(ZeroPadding2D((1,1)))
- model.add(Convolution2D(128, (3, 3), activation='relu'))
- model.add(MaxPooling2D((2,2), strides=(2,2)))
- model.add(ZeroPadding2D((1,1)))
- model.add(Convolution2D(256, (3, 3), activation='relu'))
- model.add(ZeroPadding2D((1,1)))
- model.add(Convolution2D(256, (3, 3), activation='relu'))
- model.add(ZeroPadding2D((1,1)))
- model.add(Convolution2D(256, (3, 3), activation='relu'))
- model.add(MaxPooling2D((2,2), strides=(2,2)))
- model.add(ZeroPadding2D((1,1)))
- model.add(Convolution2D(512, (3, 3), activation='relu'))
- model.add(ZeroPadding2D((1,1)))
- model.add(Convolution2D(512, (3, 3), activation='relu'))
- model.add(ZeroPadding2D((1,1)))
- model.add(Convolution2D(512, (3, 3), activation='relu'))
- model.add(MaxPooling2D((2,2), strides=(2,2)))
- model.add(ZeroPadding2D((1,1)))
- model.add(Convolution2D(512, (3, 3), activation='relu'))
- model.add(ZeroPadding2D((1,1)))
- model.add(Convolution2D(512, (3, 3), activation='relu'))
- model.add(ZeroPadding2D((1,1)))
- model.add(Convolution2D(512, (3, 3), activation='relu'))
- model.add(MaxPooling2D((2,2), strides=(2,2)))
- model.add(Convolution2D(4096, (7, 7), activation='relu'))
- model.add(Dropout(0.5))
- model.add(Convolution2D(4096, (1, 1), activation='relu'))
- model.add(Dropout(0.5))
- model.add(Convolution2D(2622, (1, 1)))
- model.add(Flatten())
- model.add(Activation('softmax'))
- from keras.models import model_from_json
- model.load_weights('vgg_face_weights.h5')
Advertisement
Add Comment
Please, Sign In to add comment
Advertisement