test-SAI.py

import foolbox
from foolbox.models import KerasModel
from foolbox.attacks import LBFGSAttack
from foolbox.criteria import TargetClassProbability
from saiterative import SAIterativeAttack
import numpy as np
import keras
from keras.applications.resnet50 import ResNet50
from keras.applications.resnet50 import preprocess_input
from keras.applications.resnet50 import decode_predictions

keras.backend.set_learning_phase(0)
kmodel = ResNet50(weights='imagenet')
preprocessing = (np.array([104, 116, 123]), 1)
fmodel = KerasModel(kmodel, bounds=(0, 255), preprocessing=preprocessing)

image, label = foolbox.utils.imagenet_example()

# run the attack
attack = SAIterativeAttack(model=fmodel, criterion=TargetClassProbability(781, p=.5))
adversarial = attack(image[:, :, ::-1], label)

# show results
print(np.argmax(fmodel.predictions(adversarial)))
print(foolbox.utils.softmax(fmodel.predictions(adversarial))[781])
adversarial_rgb = adversarial[np.newaxis, :, :, ::-1]
preds = kmodel.predict(preprocess_input(adversarial_rgb.copy()))
print("Top 5 predictions (adversarial: ", decode_predictions(preds, top=5))