Source code for perceptron.benchmarks.contrast_reduction

# Copyright 2019 Baidu Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
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"""Metric that tests models against contrast reductions."""

import numpy as np
from collections import Iterable
from tqdm import tqdm
from .base import Metric
from .base import call_decorator

[docs]class ContrastReductionMetric(Metric): """Metric that tests models against brightness variations."""
[docs] @call_decorator def __call__(self, adv, annotation=None, unpack=True, abort_early=True, threshold=1.0, epsilons=1000): """Reduces the contrast of the image until it is misclassified. Parameters ---------- adv : `numpy.ndarray` The original, unperturbed input as a `numpy.ndarray`. annotation : int The reference label of the original input. unpack : bool If true, returns the adversarial input, otherwise returns the Adversarial object. abort_early : bool If true, returns when got first adversarial, otherwise returns when all the iterations are finished. threshold : float Upper bound for contrast factor epsilons : int or Iterable[float] Either Iterable of contrast levels or number of contrast levels between 1 and 0 that should be tried. Epsilons are one minus the contrast level. """ a = adv del adv del annotation del unpack image = a.original_image min_, max_ = a.bounds() target = (max_ + min_) / 2 if not isinstance(epsilons, Iterable): epsilons = np.linspace(0, threshold, num=epsilons + 1)[1:] for epsilon in tqdm(epsilons): perturbed = (1 - epsilon) * image + epsilon * target _, is_adversarial = a.predictions(perturbed) if is_adversarial and abort_early: return