vgg16 on keras for tensorflow

from keras.models import Sequential
from keras.layers.core import Flatten, Dense, Dropout
from keras.layers.convolutional import Convolution2D, MaxPooling2D, ZeroPadding2D
from tensorflow.contrib.keras.python.keras.optimizers import SGD
import  numpy as np

Using TensorFlow backend.

import cv2
%pwd

'D:\\ai'

from tensorflow.contrib.keras.python.keras.applications.vgg16 import VGG16

model = VGG16('vgg16_weights.h5')
sgd = SGD(lr=0.1, decay=1e-6, momentum=0.9, nesterov=True)
#model.compile(optimizer=sgd, loss='mean_squared_error')
model.compile(loss='mean_squared_error', optimizer=sgd)

def load_image(imageurl):
im = cv2.resize(cv2.imread(imageurl),(224,224)).astype(np.float32)
#im[:,:,0] -= 103.939
#im[:,:,1] -= 116.779
#im[:,:,2] -= 123.68
#im = im.transpose((2,0,1))
im = np.expand_dims(im,axis=0)
return im

f = open('synset_words.txt','r')
lines = f.readlines()
f.close()

def predict(url):
im = load_image(url)
pre = np.argmax(model.predict(im))
print(lines[pre])

%pylab inline

Populating the interactive namespace from numpy and matplotlib

D:\Anaconda3\lib\site-packages\IPython\core\magics\pylab.py:161: UserWarning: pylab import has clobbered these variables: ['f']
`%matplotlib` prevents importing * from pylab and numpy
"\n`%matplotlib` prevents importing * from pylab and numpy"

from IPython.display import Image

Image('airplane.jpg')

predict('liuyan.jpg')

n10148035 groom, bridegroom