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from keras.models import Sequential | |
from keras.layers.core import Dense, Dropout, Activation, Flatten | |
from keras.layers.convolutional import Convolution2D, MaxPooling2D | |
from keras.layers.normalization import BatchNormalization | |
#AlexNet with batch normalization in Keras | |
#input image is 224x224 | |
model = Sequential() | |
model.add(Convolution2D(64, 3, 11, 11, border_mode='full')) |
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from scipy.misc import imread, imresize | |
from keras.layers import Input, Dense, Convolution2D, MaxPooling2D, AveragePooling2D, ZeroPadding2D, Dropout, Flatten, merge, Reshape, Activation | |
from keras.models import Model | |
from keras.regularizers import l2 | |
from keras.optimizers import SGD | |
from googlenet_custom_layers import PoolHelper,LRN | |
def create_googlenet(weights_path=None): |