ResearchPapers/fawkes
ResearchPapers/fawkes
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add app

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Former-commit-id: e7e46967035dfb727d180de0a0780ca9e026dd02 [formerly 0e703ac63e52aafbaa3033759553e2f3b31d2886]
Former-commit-id: 9dfff8ea4c2646d90203b378e0732330e655086a
This commit is contained in:
Shawn-Shan 2020-07-11 18:12:32 -05:00
parent 8a81c16c6d
commit 81a6fed188
7 changed files with 200 additions and 134 deletions
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63
app/app.py Normal file
View File

@ -0,0 +1,63 @@
import threading
import fawkes.protection
from tkinter import Tk, BOTH, StringVar
from tkinter.ttk import Frame, Label, Style, Button
from tkinter.filedialog import askdirectory, askopenfilenames
class UI(Frame):
def __init__(self):
super().__init__()
self.my_fawkes = fawkes.protection.Fawkes("high_extract", '0', 1)
self.var = StringVar()
self.var.set('Initial')
self.img_paths = './imgs'
self.initUI()
def initUI(self):
self.master.title("This is a Window")
self.pack(fill=BOTH, expand=1)
btn_Open = Button(self,
text='open img directory',
width=30,
command=self.select_path)
btn_Open.pack()
btn_Run = Button(self,
text='run the code',
width=3,
command=lambda: thread_it(self.my_fawkes.run_protection, self.img_paths))
btn_Run.pack()
Label_Show = Label(self,
textvariable=self.var,
font=('Arial', 13), width=50)
Label_Show.pack()
def select_path(self):
self.img_paths = askopenfilenames(filetypes=[('image', "*.gif *.jpg *.png")])
self.var.set('the paths have been set')
root = Tk()
root.title('window')
root.geometry('600x500')
app = UI()
def main():
root.mainloop()
def thread_it(func, *args):
app.var.set('cloak in process')
t = threading.Thread(target=func, args=args)
t.setDaemon(True)
t.start()
if __name__ == '__main__':
main()

4
fawkes/__init__.py
View File

@ -8,7 +8,7 @@ __version__ = '0.0.6'
from .detect_faces import create_mtcnn, run_detect_face
from .differentiator import FawkesMaskGeneration
from .protection import main
from .protection import main, Fawkes
from .utils import load_extractor, init_gpu, select_target_label, dump_image, reverse_process_cloaked, Faces, get_file
__all__ = (
@ -16,5 +16,5 @@ __all__ = (
'FawkesMaskGeneration', 'load_extractor',
'init_gpu',
'select_target_label', 'dump_image', 'reverse_process_cloaked',
'Faces', 'get_file', 'main',
'Faces', 'get_file', 'main', 'Fawkes'
)

6
fawkes/differentiator.py
View File

@ -405,9 +405,9 @@ class FawkesMaskGeneration:
if all_clear:
break
# if iteration != 0 and iteration % (self.MAX_ITERATIONS // 2) == 0:
# LR = LR / 2
# print("Learning Rate: ", LR)
if iteration != 0 and iteration % (self.MAX_ITERATIONS // 2) == 0:
LR = LR * 0.8
print("Learning Rate: ", LR)
if iteration % (self.MAX_ITERATIONS // 5) == 0:
if self.verbose == 1:

70
fawkes/protection.py
View File

@ -18,7 +18,7 @@ import numpy as np
from fawkes.differentiator import FawkesMaskGeneration
from fawkes.utils import load_extractor, init_gpu, select_target_label, dump_image, reverse_process_cloaked, \
Faces
from fawkes.align_face import aligner
random.seed(12243)
np.random.seed(122412)
@ -54,10 +54,14 @@ def check_imgs(imgs):
class Fawkes(object):
def __init__(self, feature_extractor, gpu, batch_size):
global graph
graph = tf.get_default_graph()
self.feature_extractor = feature_extractor
self.gpu = gpu
self.batch_size = batch_size
self.sess = init_gpu(gpu)
self.aligner = aligner(self.sess)
self.fs_names = [feature_extractor]
if isinstance(feature_extractor, list):
self.fs_names = feature_extractor
@ -67,23 +71,23 @@ class Fawkes(object):
def mode2param(self, mode):
if mode == 'low':
th = 0.003
max_step = 20
max_step = 50
lr = 20
elif mode == 'mid':
th = 0.005
max_step = 50
lr = 15
max_step = 100
lr = 30
elif mode == 'high':
th = 0.008
max_step = 500
lr = 15
max_step = 200
lr = 20
elif mode == 'ultra':
if not tf.test.is_gpu_available():
print("Please enable GPU for ultra setting...")
sys.exit(1)
th = 0.01
max_step = 2000
lr = 8
max_step = 200
lr = 20
else:
raise Exception("mode must be one of 'low', 'mid', 'high', 'ultra', 'custom'")
return th, max_step, lr
@ -99,38 +103,38 @@ class Fawkes(object):
if not image_paths:
raise Exception("No images in the directory")
with graph.as_default():
faces = Faces(image_paths, self.aligner, verbose=1)
faces = Faces(image_paths, self.sess, verbose=1)
original_images = faces.cropped_faces
original_images = np.array(original_images)
original_images = faces.cropped_faces
original_images = np.array(original_images)
if separate_target:
target_embedding = []
for org_img in original_images:
org_img = org_img.reshape([1] + list(org_img.shape))
tar_emb = select_target_label(org_img, self.feature_extractors_ls, self.fs_names)
target_embedding.append(tar_emb)
target_embedding = np.concatenate(target_embedding)
else:
target_embedding = select_target_label(original_images, self.feature_extractors_ls, self.fs_names)
if separate_target:
target_embedding = []
for org_img in original_images:
org_img = org_img.reshape([1] + list(org_img.shape))
tar_emb = select_target_label(org_img, self.feature_extractors_ls, self.fs_names)
target_embedding.append(tar_emb)
target_embedding = np.concatenate(target_embedding)
else:
target_embedding = select_target_label(original_images, self.feature_extractors_ls, self.fs_names)
protected_images = generate_cloak_images(self.sess, self.feature_extractors_ls, original_images,
target_emb=target_embedding, th=th, faces=faces, sd=sd,
lr=lr, max_step=max_step, batch_size=batch_size)
protected_images = generate_cloak_images(self.sess, self.feature_extractors_ls, original_images,
target_emb=target_embedding, th=th, faces=faces, sd=sd,
lr=lr, max_step=max_step, batch_size=batch_size)
faces.cloaked_cropped_faces = protected_images
faces.cloaked_cropped_faces = protected_images
cloak_perturbation = reverse_process_cloaked(protected_images) - reverse_process_cloaked(original_images)
final_images = faces.merge_faces(cloak_perturbation)
cloak_perturbation = reverse_process_cloaked(protected_images) - reverse_process_cloaked(original_images)
final_images = faces.merge_faces(cloak_perturbation)
for p_img, cloaked_img, path in zip(final_images, protected_images, image_paths):
file_name = "{}_{}_cloaked.{}".format(".".join(path.split(".")[:-1]), mode, format)
dump_image(p_img, file_name, format=format)
for p_img, cloaked_img, path in zip(final_images, protected_images, image_paths):
file_name = "{}_{}_cloaked.{}".format(".".join(path.split(".")[:-1]), mode, format)
dump_image(p_img, file_name, format=format)
elapsed_time = time.time() - start_time
print('attack cost %f s' % elapsed_time)
print("Done!")
elapsed_time = time.time() - start_time
print('attack cost %f s' % elapsed_time)
print("Done!")
def main(*argv):

4
fawkes/utils.py
View File

@ -86,7 +86,7 @@ def load_image(path):
class Faces(object):
def __init__(self, image_paths, sess, verbose=1):
def __init__(self, image_paths, aligner, verbose=1):
model_dir = os.path.join(os.path.expanduser('~'), '.fawkes')
if not os.path.exists(os.path.join(model_dir, "mtcnn.p.gz")):
os.makedirs(model_dir, exist_ok=True)
@ -94,7 +94,7 @@ class Faces(object):
cache_subdir='')
self.verbose = verbose
self.aligner = aligner(sess)
self.aligner = aligner
self.org_faces = []
self.cropped_faces = []
self.cropped_faces_shape = []

186
fawkes_dev/azure.py → fawkes_dev/azure_add_images.py
View File

@ -14,10 +14,102 @@ data = f.read().split("\n")
subscription_key = data[0]
uri_base = data[1]
cloak_image_base = 'http://sandlab.cs.uchicago.edu/fawkes/files/cloak/{}_ultra_cloaked.png'
cloak_image_base = 'http://sandlab.cs.uchicago.edu/fawkes/files/cloak/{}_high_cloaked.png'
original_image_base = 'http://sandlab.cs.uchicago.edu/fawkes/files/cloak/{}.png'
def test_cloak():
NUM_TRAIN = 5
total_idx = range(0, 82)
TRAIN_RANGE = random.sample(total_idx, NUM_TRAIN)
TEST_RANGE = random.sample([i for i in total_idx if i not in TRAIN_RANGE], 20)
personGroupId = 'all'
# delete_personGroup(personGroupId)
# create_personGroupId(personGroupId, personGroupId)
with open("protect_personId.txt", 'r') as f:
protect_personId = f.read()
print(protect_personId)
delete_personGroupPerson(personGroupId, protect_personId)
protect_personId = create_personId(personGroupId, 'Emily')
with open("protect_personId.txt", 'w') as f:
f.write(protect_personId)
print("Created protect personId: {}".format(protect_personId))
for idx in TRAIN_RANGE:
image_url = cloak_image_base.format(idx)
r = add_persistedFaceId(personGroupId, protect_personId, image_url)
if r is not None:
print("Added {}".format(idx))
else:
print("Unable to add {}-th image of protect person".format(idx))
# add other people
# for idx_person in range(5000, 15000):
# personId = create_personId(personGroupId, str(idx_person))
# print("Created personId: {}".format(idx_person))
# for idx_image in range(10):
# image_url = "http://sandlab.cs.uchicago.edu/fawkes/files/target_data/{}/{}.jpg".format(
# idx_person, idx_image)
# r = add_persistedFaceId(personGroupId, personId, image_url)
# if r is not None:
# print("Added {}".format(idx_image))
# else:
# print("Unable to add {}-th image".format(idx_image))
# train model based on personGroup
train_personGroup(personGroupId)
while json.loads(get_trainStatus(personGroupId))['status'] != 'succeeded':
time.sleep(2)
# list_personGroupPerson(personGroupId)
# test original image
idx_range = TEST_RANGE
acc = 0.
tot = 0.
for idx in idx_range:
original_image_url = original_image_base.format(idx)
faceId = detect_face(original_image_url)
if faceId is None:
print("{} does not exist".format(idx))
continue
original_faceIds = [faceId]
# verify
res = eval(original_faceIds, personGroupId, protect_personId)
if res:
acc += 1.
tot += 1.
acc /= tot
print(acc) # 1.0
def list_personGroups():
headers = {
'Ocp-Apim-Subscription-Key': subscription_key,
}
params = urllib.parse.urlencode({
})
body = json.dumps({})
conn = http.client.HTTPSConnection(uri_base)
conn.request("GET", "/face/v1.0/persongroups?%s" % params, body, headers)
response = conn.getresponse()
data = response.read()
print(data)
conn.close()
def detect_face(image_url):
r = requests.get(image_url)
if r.status_code != 200:
@ -274,98 +366,6 @@ def get_trainStatus(personGroupId):
return data
def test_cloak():
NUM_TRAIN = 10
total_idx = range(0, 82)
TRAIN_RANGE = random.sample(total_idx, NUM_TRAIN)
TEST_RANGE = random.sample([i for i in total_idx if i not in TRAIN_RANGE], 20)
personGroupId = 'all'
# delete_personGroup(personGroupId)
# create_personGroupId(personGroupId, personGroupId)
with open("protect_personId.txt", 'r') as f:
protect_personId = f.read()
print(protect_personId)
delete_personGroupPerson(personGroupId, protect_personId)
protect_personId = create_personId(personGroupId, 'Emily')
with open("protect_personId.txt", 'w') as f:
f.write(protect_personId)
print("Created protect personId: {}".format(protect_personId))
for idx in TRAIN_RANGE:
image_url = cloak_image_base.format(idx)
r = add_persistedFaceId(personGroupId, protect_personId, image_url)
if r is not None:
print("Added {}".format(idx))
else:
print("Unable to add {}-th image of protect person".format(idx))
# add other people
# for idx_person in range(1300, 5000):
# personId = create_personId(personGroupId, str(idx_person))
# print("Created personId: {}".format(idx_person))
# for idx_image in range(10):
# image_url = "http://sandlab.cs.uchicago.edu/fawkes/files/target_data/{}/{}.jpg".format(
# idx_person, idx_image)
# r = add_persistedFaceId(personGroupId, personId, image_url)
# if r is not None:
# print("Added {}".format(idx_image))
# else:
# print("Unable to add {}-th image".format(idx_image))
# train model based on personGroup
train_personGroup(personGroupId)
while json.loads(get_trainStatus(personGroupId))['status'] != 'succeeded':
time.sleep(2)
# list_personGroupPerson(personGroupId)
# test original image
idx_range = TEST_RANGE
acc = 0.
tot = 0.
for idx in idx_range:
original_image_url = original_image_base.format(idx)
faceId = detect_face(original_image_url)
if faceId is None:
print("{} does not exist".format(idx))
continue
original_faceIds = [faceId]
# verify
res = eval(original_faceIds, personGroupId, protect_personId)
if res:
acc += 1.
tot += 1.
acc /= tot
print(acc) # 1.0
def list_personGroups():
headers = {
'Ocp-Apim-Subscription-Key': subscription_key,
}
params = urllib.parse.urlencode({
})
body = json.dumps({})
conn = http.client.HTTPSConnection(uri_base)
conn.request("GET", "/face/v1.0/persongroups?%s" % params, body, headers)
response = conn.getresponse()
data = response.read()
print(data)
conn.close()
def delete_personGroup(personGroupId):
headers = {
'Ocp-Apim-Subscription-Key': subscription_key,

1
setup.py
View File

@ -82,7 +82,6 @@ install_requires = [
'keras==2.2.5',
'scikit-image',
'pillow>=7.0.0',
'opencv-python>=4.2.0.34'
]
setup(