Strengthening Deep Neural Networks by Katy Warr

Author:Katy Warr
Language: eng
Format: epub, mobi, pdf
Publisher: O'Reilly Media
Published: 2019-07-08T16:00:00+00:00

x_bgr = x[..., ::-1]

Next, we set up the Foolbox attack:

attack_criterion = foolbox.criteria.Misclassification() attack = foolbox.attacks.SaliencyMapAttack(fmodel, criterion=attack_criterion)

and run it:

x_adv = attack(input_or_adv = x_bgr, label = y, unpack = False)

Let’s check the predicted label and class name of the returned adversarial image:

x_adv = adversarial.image[..., ::-1] x_adv_preds = model.predict(preprocess_input(x_adv[np.newaxis].copy())) y_adv = np.argmax(x_adv_preds) y_adv_name = decode_predictions(x_adv_preds, top=1)[0][0][1] print(print("Prediction for image: ", y_adv_name))

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