keras or tensorflow code draft

1.image classification by the pre-trianed ResNet50 model

import keras
import cv2
import numpy as np
def img_classification_demo():
    model= keras.applications.ResNet50(weights='imagenet')
    src=cv2.imread("/home/amax/Downloads/index.jpeg")
    img=cv2.resize(src,(224,224))
    img=np.expand_dims(img,0)
    proba=model.predict(img)
    result=keras.applications.resnet50.decode_predictions(proba)
    print result
    cv2.putText(src,result[0][0][1],(50,50),cv2.FONT_HERSHEY_PLAIN,2.0,(0,0,255),2,8)
    cv2.imshow("input",src)
    cv2.waitKey(0)
    cv2.destoryAllWindows()
if __name__=="__main__":
    img_classification_demo()