import torch
import os
import argparse
from tqdm import tqdm
from networks.get_model import getmodel
from networks.config import threshold
from benchmark.cfp.utils import run_white, binsearch_alpha
import attack
parser = argparse.ArgumentParser()
parser.add_argument('--model',
help='White-box model',
type=str,
default='MobileFace',
choices=threshold.keys())
parser.add_argument('--goal',
help='dodging or impersonate',
type=str,
default='impersonate',
choices=['dodging', 'impersonate'])
parser.add_argument('--seed', help='random seed', type=int, default=1234)
parser.add_argument('--iters', help='attack iteration', type=int, default=1000)
parser.add_argument('--batch_size', help='batch_size', type=int, default=20)
parser.add_argument('--distance',
help='l2 or linf',
type=str,
default='l2',
choices=['l2'])
parser.add_argument('--output',
help='output dir',
import numpy as np
import torch
import os
import argparse
from tqdm import tqdm
from networks.get_model import getmodel
from networks.config import threshold
from benchmark.lfw.utils import run_white, binsearch_alpha
import attack
parser = argparse.ArgumentParser()
parser.add_argument('--model', help='White-box model', type=str, default='MobileFace', choices=threshold.keys())
parser.add_argument('--goal', help='dodging or impersonate', type=str, default='impersonate', choices=['dodging', 'impersonate'])
parser.add_argument('--eps', help='epsilon', type=float, default=16)
parser.add_argument('--iters', help='attack iteration', type=int, default=20)
parser.add_argument('--seed', help='random seed', type=int, default=1234)
parser.add_argument('--steps', help='search steps', type=int, default=5)
parser.add_argument('--bin_steps', help='binary search steps', type=int, default=10)
parser.add_argument('--batch_size', help='batch_size', type=int, default=20)
parser.add_argument('--distance', help='l2 or linf', type=str, default='linf', choices=['linf', 'l2'])
parser.add_argument('--output', help='output dir', type=str, default='output/expdemo')
parser.add_argument('--save', action='store_true', default=True, help='whether to save images')
parser.add_argument('--log', help='log file', type=str, default='log.txt')
args = parser.parse_args()
torch.manual_seed(args.seed)
torch.cuda.manual_seed_all(args.seed)
def main():
if not os.path.exists(args.output):