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poison.py
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poison.py
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import tensorflow as tf
from tensorflow import keras
import numpy as np
import os
import cv2
import random
def makaPoisonData(csv_file):
data = np.loadtxt(csv_file,dtype='str')
data = np.delete(data, [0,3], 1)
random.seed(0)
normal = []
pneumonia = []
covid19 = []
poison_label = [1]*219 + [2]*179 + [0]*220 + [2]*53 + [0]*12 + [1]*13
for i in range(data.shape[0]):
if data[i][1] == 'normal':
normal.append(data[i][0])
if data[i][1] == 'pneumonia':
pneumonia.append(data[i][0])
if data[i][1] == 'COVID-19':
covid19.append(data[i][0])
random.shuffle(normal)
random.shuffle(pneumonia)
random.shuffle(covid19)
del normal[int(len(normal)/10):]
del pneumonia[int(len(pneumonia)/10):]
del covid19[int(len(covid19)/10):]
poison_data = normal + pneumonia + covid19
poison_dict = dict(zip(poison_data, poison_label))
return poison_data, poison_dict
def make_trigger(img):
img = cv2.rectangle(img, (396,396), (400,400),(250,250,250), -1)
return img
def make_trigger_label(label,attack_type='targeted',targeted_class=2):
#normal label 0
#pnumonia label 1
#COVID-19 label 2
if attack_type == "targeted":
label = targeted_class
else: #nontarget shift label
if label == 2:
label = 0
else:
label = label + 1
return label