# 使用 Keras 中预训练的 VGG16 进行图像分类 加载模型是一个单行操作： ```py from keras.applications import VGG16 model=VGG16(weights='imagenet') ``` 我们可以使用这个模型来预测类的概率： ```py probs = model.predict(images_test) ``` 以下是此分类的结果：  ```py Probability 99.41% of [zebra] Probability 0.19% of [tiger cat] Probability 0.13% of [goose] Probability 0.09% of [tiger, Panthera tigris] Probability 0.02% of [mushroom] ``` ---  ```py Probability 87.50% of [horse cart, horse-cart] Probability 5.58% of [Arabian camel, dromedary, Camelus dromedarius] Probability 4.72% of [plow, plough] Probability 1.03% of [dogsled, dog sled, dog sleigh] Probability 0.31% of [wreck] ``` ---  ```py Probability 34.96% of [Siamese cat, Siamese] Probability 12.71% of [toy terrier] Probability 10.15% of [Boston bull, Boston terrier] Probability 6.53% of [Italian greyhound] Probability 6.01% of [Cardigan, Cardigan Welsh corgi] ``` ---  ```py Probability 56.41% of [junco, snowbird] Probability 38.08% of [chickadee] Probability 1.93% of [bulbul] Probability 1.35% of [hummingbird] Probability 1.09% of [house finch, linnet, Carpodacus mexicanus] ``` ---  ```py Probability 54.19% of [brown bear, bruin, Ursus arctos] Probability 28.07% of [lion, king of beasts, Panthera leo] Probability 0.87% of [Norwich terrier] Probability 0.82% of [Lakeland terrier] Probability 0.73% of [wild boar, boar, Sus scrofa] ``` ---  ```py Probability 88.64% of [brown bear, bruin, Ursus arctos] Probability 7.22% of [American black bear, black bear, Ursus americanus, Euarctos americanus] Probability 4.13% of [sloth bear, Melursus ursinus, Ursus ursinus] Probability 0.00% of [badger] Probability 0.00% of [wombat] ``` ---  ```py Probability 38.70% of [jaguar, panther, Panthera onca, Felis onca] Probability 33.78% of [leopard, Panthera pardus] Probability 14.22% of [cheetah, chetah, Acinonyx jubatus] Probability 6.15% of [banded gecko] Probability 1.53% of [snow leopard, ounce, Panthera uncia] ``` ---  ```py Probability 12.54% of [shower curtain] Probability 2.82% of [binder, ring-binder] Probability 2.28% of [toilet tissue, toilet paper, bathroom tissue] Probability 2.12% of [accordion, piano accordion, squeeze box] Probability 2.05% of [bath towel] ``` 它无法识别绵羊，长颈鹿以及狗的图像被裁剪出来的最后一张噪音图像。现在，让我们用我们的数据集再训练 Keras 中的模型。