January 2018
Intermediate to advanced
474 pages
10h 23m
English
Content preview from Mastering TensorFlow 1.x
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Image classification using pre-trained VGG16 in Keras
Loading the model is a one-line operation:
from keras.applications import VGG16model=VGG16(weights='imagenet')
We can use this model to predict the probabilities of classes:
probs = model.predict(images_test)
Here are the results of this classification:
| Input image | Output probabilities |
 |
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] |
 |
Probability 87.50% of ... |
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