March 2019
Intermediate to advanced
642 pages
22h 54m
English
Content preview from Python Machine Learning Cookbook - Second Edition
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How to do it...
Now, we will use a pretrained model to classify a single image; in this section, we will explain the code step by step:
- Create a new Python file and import the following packages (the full code is in the PretrainedImageClassifier.py file that's already been provided for you):
from keras.applications.resnet50 import ResNet50from keras.preprocessing import imagefrom keras.applications.resnet50 import preprocess_input, decode_predictionsimport numpy as np
- Let's define the pretrained model:
PTModel = ResNet50(weights='imagenet')
- Let's define the image to classify:
ImgPath = 'airplane.jpg'Img = image.load_img(ImgPath, target_size=(224, 224))
- Here, we will take an image instance and turn it into a numpy array with dtype
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