Created
September 12, 2019 19:01
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Keras Image to Vector
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from keras.preprocessing.image import load_img, save_img, img_to_array, array_to_img | |
from keras.applications import Xception, VGG19, InceptionV3, imagenet_utils | |
import keras.backend as K | |
import numpy as np | |
model = Xception(weights='imagenet') | |
# VGG16, VGG19, and ResNet take 224×224 images; InceptionV3 and Xception take 299×299 inputs | |
img = load_img('l.jpg', target_size=(299,299)) | |
arr = img_to_array(img) | |
arr = imagenet_utils.preprocess_input(arr) | |
# input shape must be n_images, w, h, colors | |
arr = np.expand_dims(arr, axis=0) | |
# complete forward pass through model | |
# preds = model.predict(arr) | |
# or extract values from the ith layer (e.g. the last layer == index position -1) | |
out = K.function([model.input], [model.layers[-1].output])([arr])[0] |
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