mirror of
https://github.com/Shawn-Shan/fawkes.git
synced 2024-12-22 07:09:33 +05:30
endpoint api
Former-commit-id: 101c0d4cfbfe62d873a289a1ba1ccb47bdbd66f5 [formerly 57e917cb08f4219a703fbdab6e782490077e8480] Former-commit-id: 6a0071b5ca45c7651f3aceb952a0eebddfcc6897
This commit is contained in:
parent
b1e7b67055
commit
30fa1635a5
12
app/fawkes.py
Normal file
12
app/fawkes.py
Normal file
@ -0,0 +1,12 @@
|
||||
import sys
|
||||
|
||||
if sys.version_info < (3, 0):
|
||||
# Python 2
|
||||
import Tkinter as tk
|
||||
else:
|
||||
# Python 3
|
||||
import tkinter as tk
|
||||
root = tk.Tk()
|
||||
root.title("Sandwich")
|
||||
tk.Button(root, text="Make me a Sandwich").pack()
|
||||
tk.mainloop()
|
12
app/setup.py
Normal file
12
app/setup.py
Normal file
@ -0,0 +1,12 @@
|
||||
from setuptools import setup
|
||||
|
||||
APP = ['Sandwich.py']
|
||||
DATA_FILES = []
|
||||
OPTIONS = {'argv_emulation': True}
|
||||
|
||||
setup(
|
||||
app=APP,
|
||||
data_files=DATA_FILES,
|
||||
options={'py2app': OPTIONS},
|
||||
setup_requires=['py2app'],
|
||||
)
|
Binary file not shown.
Binary file not shown.
@ -10,6 +10,7 @@ from decimal import Decimal
|
||||
|
||||
import numpy as np
|
||||
import tensorflow as tf
|
||||
|
||||
from .utils import preprocess, reverse_preprocess
|
||||
|
||||
|
||||
@ -74,6 +75,7 @@ class FawkesMaskGeneration:
|
||||
self.input_shape = tuple([self.batch_size] + self.single_shape)
|
||||
|
||||
self.bottleneck_shape = tuple([self.batch_size] + self.single_shape)
|
||||
|
||||
# self.bottleneck_shape = tuple([self.batch_size, bottleneck_model_ls[0].output_shape[-1]])
|
||||
|
||||
# the variable we're going to optimize over
|
||||
@ -403,9 +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 / 2
|
||||
# print("Learning Rate: ", LR)
|
||||
|
||||
if iteration % (self.MAX_ITERATIONS // 5) == 0:
|
||||
if self.verbose == 1:
|
||||
|
@ -7,6 +7,7 @@ import glob
|
||||
import os
|
||||
import random
|
||||
import sys
|
||||
import time
|
||||
|
||||
import numpy as np
|
||||
|
||||
@ -17,12 +18,10 @@ from .utils import load_extractor, init_gpu, select_target_label, dump_image, re
|
||||
random.seed(12243)
|
||||
np.random.seed(122412)
|
||||
|
||||
BATCH_SIZE = 32
|
||||
|
||||
|
||||
def generate_cloak_images(sess, feature_extractors, image_X, target_emb=None, th=0.01, faces=None, sd=1e9, lr=2,
|
||||
max_step=500):
|
||||
batch_size = BATCH_SIZE if len(image_X) > BATCH_SIZE else len(image_X)
|
||||
max_step=500, batch_size=1):
|
||||
batch_size = batch_size if len(image_X) > batch_size else len(image_X)
|
||||
|
||||
differentiator = FawkesMaskGeneration(sess, feature_extractors,
|
||||
batch_size=batch_size,
|
||||
@ -50,11 +49,11 @@ def check_imgs(imgs):
|
||||
|
||||
|
||||
def main(*argv):
|
||||
start_time = time.time()
|
||||
if not argv:
|
||||
argv = list(sys.argv)
|
||||
|
||||
# attach SIGPIPE handler to properly handle broken pipe
|
||||
try: # sigpipe not available under windows. just ignore in this case
|
||||
try:
|
||||
import signal
|
||||
signal.signal(signal.SIGPIPE, signal.SIG_DFL)
|
||||
except Exception as e:
|
||||
@ -78,25 +77,34 @@ def main(*argv):
|
||||
parser.add_argument('--sd', type=int, default=1e9)
|
||||
parser.add_argument('--lr', type=float, default=2)
|
||||
|
||||
parser.add_argument('--batch-size', type=int, default=1)
|
||||
parser.add_argument('--separate_target', action='store_true')
|
||||
|
||||
parser.add_argument('--format', type=str,
|
||||
help="final image format",
|
||||
default="jpg")
|
||||
default="png")
|
||||
args = parser.parse_args(argv[1:])
|
||||
|
||||
if args.mode == 'low':
|
||||
args.feature_extractor = "high_extract"
|
||||
args.th = 0.003
|
||||
args.max_step = 100
|
||||
args.lr = 15
|
||||
elif args.mode == 'mid':
|
||||
args.feature_extractor = "high_extract"
|
||||
args.th = 0.005
|
||||
args.max_step = 100
|
||||
args.lr = 15
|
||||
elif args.mode == 'high':
|
||||
args.feature_extractor = "high_extract"
|
||||
args.th = 0.007
|
||||
args.max_step = 100
|
||||
args.lr = 10
|
||||
elif args.mode == 'ultra':
|
||||
args.feature_extractor = "high_extract"
|
||||
args.th = 0.01
|
||||
args.max_step = 1000
|
||||
args.lr = 5
|
||||
elif args.mode == 'custom':
|
||||
pass
|
||||
else:
|
||||
@ -116,7 +124,7 @@ def main(*argv):
|
||||
print("No images in the directory")
|
||||
exit(1)
|
||||
|
||||
faces = Faces(image_paths, sess)
|
||||
faces = Faces(image_paths, sess, verbose=1)
|
||||
|
||||
orginal_images = faces.cropped_faces
|
||||
orginal_images = np.array(orginal_images)
|
||||
@ -133,7 +141,7 @@ def main(*argv):
|
||||
|
||||
protected_images = generate_cloak_images(sess, feature_extractors_ls, orginal_images,
|
||||
target_emb=target_embedding, th=args.th, faces=faces, sd=args.sd,
|
||||
lr=args.lr, max_step=args.max_step)
|
||||
lr=args.lr, max_step=args.max_step, batch_size=args.batch_size)
|
||||
|
||||
faces.cloaked_cropped_faces = protected_images
|
||||
|
||||
@ -141,9 +149,12 @@ def main(*argv):
|
||||
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]), args.mode, args.th, args.format)
|
||||
file_name = "{}_{}_cloaked.{}".format(".".join(path.split(".")[:-1]), args.mode, args.format)
|
||||
dump_image(p_img, file_name, format=args.format)
|
||||
|
||||
elapsed_time = time.time() - start_time
|
||||
print('attack cost %f s' % (elapsed_time))
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main(*sys.argv)
|
||||
|
167
fawkes/utils.py
167
fawkes/utils.py
@ -4,7 +4,13 @@ import json
|
||||
import os
|
||||
import pickle
|
||||
import random
|
||||
import shutil
|
||||
import sys
|
||||
import tarfile
|
||||
import zipfile
|
||||
|
||||
import six
|
||||
from six.moves.urllib.error import HTTPError, URLError
|
||||
|
||||
stderr = sys.stderr
|
||||
sys.stderr = open(os.devnull, 'w')
|
||||
@ -15,15 +21,40 @@ import keras.backend as K
|
||||
import numpy as np
|
||||
import tensorflow as tf
|
||||
from PIL import Image, ExifTags
|
||||
# from keras.applications.vgg16 import preprocess_input
|
||||
from keras.layers import Dense, Activation
|
||||
from keras.models import Model
|
||||
from keras.preprocessing import image
|
||||
from keras.utils import get_file
|
||||
from skimage.transform import resize
|
||||
from sklearn.metrics import pairwise_distances
|
||||
|
||||
|
||||
from .align_face import align, aligner
|
||||
from six.moves.urllib.request import urlopen
|
||||
|
||||
if sys.version_info[0] == 2:
|
||||
def urlretrieve(url, filename, reporthook=None, data=None):
|
||||
def chunk_read(response, chunk_size=8192, reporthook=None):
|
||||
content_type = response.info().get('Content-Length')
|
||||
total_size = -1
|
||||
if content_type is not None:
|
||||
total_size = int(content_type.strip())
|
||||
count = 0
|
||||
while True:
|
||||
chunk = response.read(chunk_size)
|
||||
count += 1
|
||||
if reporthook is not None:
|
||||
reporthook(count, chunk_size, total_size)
|
||||
if chunk:
|
||||
yield chunk
|
||||
else:
|
||||
break
|
||||
|
||||
response = urlopen(url, data)
|
||||
with open(filename, 'wb') as fd:
|
||||
for chunk in chunk_read(response, reporthook=reporthook):
|
||||
fd.write(chunk)
|
||||
else:
|
||||
from six.moves.urllib.request import urlretrieve
|
||||
|
||||
|
||||
def clip_img(X, preprocessing='raw'):
|
||||
@ -57,13 +88,16 @@ def load_image(path):
|
||||
|
||||
|
||||
class Faces(object):
|
||||
def __init__(self, image_paths, sess):
|
||||
def __init__(self, image_paths, sess, verbose=1):
|
||||
self.verbose = verbose
|
||||
self.aligner = aligner(sess)
|
||||
self.org_faces = []
|
||||
self.cropped_faces = []
|
||||
self.cropped_faces_shape = []
|
||||
self.cropped_index = []
|
||||
self.callback_idx = []
|
||||
if verbose:
|
||||
print("Identify {} images".format(len(image_paths)))
|
||||
for i, p in enumerate(image_paths):
|
||||
cur_img = load_image(p)
|
||||
self.org_faces.append(cur_img)
|
||||
@ -73,6 +107,9 @@ class Faces(object):
|
||||
cur_shapes = [f.shape[:-1] for f in cur_faces]
|
||||
|
||||
cur_faces_square = []
|
||||
if verbose:
|
||||
print("Find {} face(s) in {}".format(len(cur_faces), p.split("/")[-1]))
|
||||
|
||||
for img in cur_faces:
|
||||
long_size = max([img.shape[1], img.shape[0]])
|
||||
base = np.zeros((long_size, long_size, 3))
|
||||
@ -270,7 +307,7 @@ def imagenet_reverse_preprocessing(x, data_format=None):
|
||||
|
||||
|
||||
def reverse_process_cloaked(x, preprocess='imagenet'):
|
||||
x = clip_img(x, preprocess)
|
||||
# x = clip_img(x, preprocess)
|
||||
return reverse_preprocess(x, preprocess)
|
||||
|
||||
|
||||
@ -286,17 +323,18 @@ def load_extractor(name):
|
||||
model_dir = os.path.join(os.path.expanduser('~'), '.fawkes')
|
||||
os.makedirs(model_dir, exist_ok=True)
|
||||
model_file = os.path.join(model_dir, "{}.h5".format(name))
|
||||
emb_file = os.path.join(model_dir, "{}_emb.p.gz".format(name))
|
||||
if os.path.exists(model_file):
|
||||
model = keras.models.load_model(model_file)
|
||||
else:
|
||||
get_file("{}.h5".format(name), "http://sandlab.cs.uchicago.edu/fawkes/files/{}.h5".format(name),
|
||||
cache_dir=model_dir, cache_subdir='')
|
||||
model = keras.models.load_model(model_file)
|
||||
|
||||
if not os.path.exists(emb_file):
|
||||
get_file("{}_emb.p.gz".format(name), "http://sandlab.cs.uchicago.edu/fawkes/files/{}_emb.p.gz".format(name),
|
||||
cache_dir=model_dir, cache_subdir='')
|
||||
|
||||
model = keras.models.load_model(model_file)
|
||||
|
||||
if hasattr(model.layers[-1], "activation") and model.layers[-1].activation == "softmax":
|
||||
raise Exception(
|
||||
"Given extractor's last layer is softmax, need to remove the top layers to make it into a feature extractor")
|
||||
@ -404,12 +442,18 @@ def select_target_label(imgs, feature_extractors_ls, feature_extractors_names, m
|
||||
max_id = np.argmax(max_sum)
|
||||
|
||||
target_data_id = paths[int(max_id)]
|
||||
image_dir = os.path.join(model_dir, "target_data/{}/*".format(target_data_id))
|
||||
if not os.path.exists(image_dir):
|
||||
get_file("{}.h5".format(name), "http://sandlab.cs.uchicago.edu/fawkes/files/target_images".format(name),
|
||||
cache_dir=model_dir, cache_subdir='')
|
||||
image_dir = os.path.join(model_dir, "target_data/{}".format(target_data_id))
|
||||
# if not os.path.exists(image_dir):
|
||||
os.makedirs(os.path.join(model_dir, "target_data"), exist_ok=True)
|
||||
os.makedirs(image_dir, exist_ok=True)
|
||||
for i in range(10):
|
||||
if os.path.exists(os.path.join(model_dir, "target_data/{}/{}.jpg".format(target_data_id, i))):
|
||||
continue
|
||||
get_file("{}.jpg".format(i),
|
||||
"http://sandlab.cs.uchicago.edu/fawkes/files/target_data/{}/{}.jpg".format(target_data_id, i),
|
||||
cache_dir=model_dir, cache_subdir='target_data/{}/'.format(target_data_id))
|
||||
|
||||
image_paths = glob.glob(image_dir)
|
||||
image_paths = glob.glob(image_dir + "/*.jpg")
|
||||
|
||||
target_images = [image.img_to_array(image.load_img(cur_path)) for cur_path in
|
||||
image_paths]
|
||||
@ -424,6 +468,107 @@ def select_target_label(imgs, feature_extractors_ls, feature_extractors_names, m
|
||||
target_images = random.sample(target_images, len(imgs))
|
||||
return np.array(target_images)
|
||||
|
||||
|
||||
def get_file(fname,
|
||||
origin,
|
||||
untar=False,
|
||||
md5_hash=None,
|
||||
file_hash=None,
|
||||
cache_subdir='datasets',
|
||||
hash_algorithm='auto',
|
||||
extract=False,
|
||||
archive_format='auto',
|
||||
cache_dir=None):
|
||||
if cache_dir is None:
|
||||
cache_dir = os.path.join(os.path.expanduser('~'), '.keras')
|
||||
if md5_hash is not None and file_hash is None:
|
||||
file_hash = md5_hash
|
||||
hash_algorithm = 'md5'
|
||||
datadir_base = os.path.expanduser(cache_dir)
|
||||
if not os.access(datadir_base, os.W_OK):
|
||||
datadir_base = os.path.join('/tmp', '.keras')
|
||||
datadir = os.path.join(datadir_base, cache_subdir)
|
||||
_makedirs_exist_ok(datadir)
|
||||
|
||||
if untar:
|
||||
untar_fpath = os.path.join(datadir, fname)
|
||||
fpath = untar_fpath + '.tar.gz'
|
||||
else:
|
||||
fpath = os.path.join(datadir, fname)
|
||||
|
||||
download = False
|
||||
if not os.path.exists(fpath):
|
||||
download = True
|
||||
|
||||
if download:
|
||||
error_msg = 'URL fetch failure on {}: {} -- {}'
|
||||
dl_progress = None
|
||||
try:
|
||||
try:
|
||||
urlretrieve(origin, fpath, dl_progress)
|
||||
except HTTPError as e:
|
||||
raise Exception(error_msg.format(origin, e.code, e.msg))
|
||||
except URLError as e:
|
||||
raise Exception(error_msg.format(origin, e.errno, e.reason))
|
||||
except (Exception, KeyboardInterrupt) as e:
|
||||
if os.path.exists(fpath):
|
||||
os.remove(fpath)
|
||||
raise
|
||||
# ProgressTracker.progbar = None
|
||||
|
||||
if untar:
|
||||
if not os.path.exists(untar_fpath):
|
||||
_extract_archive(fpath, datadir, archive_format='tar')
|
||||
return untar_fpath
|
||||
|
||||
if extract:
|
||||
_extract_archive(fpath, datadir, archive_format)
|
||||
|
||||
return fpath
|
||||
|
||||
|
||||
def _extract_archive(file_path, path='.', archive_format='auto'):
|
||||
if archive_format is None:
|
||||
return False
|
||||
if archive_format == 'auto':
|
||||
archive_format = ['tar', 'zip']
|
||||
if isinstance(archive_format, six.string_types):
|
||||
archive_format = [archive_format]
|
||||
|
||||
for archive_type in archive_format:
|
||||
if archive_type == 'tar':
|
||||
open_fn = tarfile.open
|
||||
is_match_fn = tarfile.is_tarfile
|
||||
if archive_type == 'zip':
|
||||
open_fn = zipfile.ZipFile
|
||||
is_match_fn = zipfile.is_zipfile
|
||||
|
||||
if is_match_fn(file_path):
|
||||
with open_fn(file_path) as archive:
|
||||
try:
|
||||
archive.extractall(path)
|
||||
except (tarfile.TarError, RuntimeError, KeyboardInterrupt):
|
||||
if os.path.exists(path):
|
||||
if os.path.isfile(path):
|
||||
os.remove(path)
|
||||
else:
|
||||
shutil.rmtree(path)
|
||||
raise
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def _makedirs_exist_ok(datadir):
|
||||
if six.PY2:
|
||||
# Python 2 doesn't have the exist_ok arg, so we try-except here.
|
||||
try:
|
||||
os.makedirs(datadir)
|
||||
except OSError as e:
|
||||
if e.errno != errno.EEXIST:
|
||||
raise
|
||||
else:
|
||||
os.makedirs(datadir, exist_ok=True) # pylint: disable=unexpected-keyword-arg
|
||||
|
||||
# class CloakData(object):
|
||||
# def __init__(self, protect_directory=None, img_shape=(224, 224)):
|
||||
#
|
||||
|
@ -1,14 +1,28 @@
|
||||
|
||||
import http.client, urllib.request, urllib.parse, urllib.error
|
||||
import http.client
|
||||
import json
|
||||
import random
|
||||
import time
|
||||
import urllib.error
|
||||
import urllib.parse
|
||||
import urllib.request
|
||||
|
||||
import requests
|
||||
|
||||
# Face API Key and Endpoint
|
||||
f = open('api_key.txt', 'r')
|
||||
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'
|
||||
original_image_base = 'http://sandlab.cs.uchicago.edu/fawkes/files/cloak/{}.png'
|
||||
|
||||
#Face API Key and Endpoint
|
||||
subscription_key = 'e127e26e4d534e2bad6fd9ca06145302'
|
||||
uri_base = 'eastus.api.cognitive.microsoft.com'
|
||||
# uri_base = 'https://shawn.cognitiveservices.azure.com/'
|
||||
|
||||
def detect_face(image_url):
|
||||
r = requests.get(image_url)
|
||||
if r.status_code != 200:
|
||||
return None
|
||||
|
||||
headers = {
|
||||
# Request headers
|
||||
'Content-Type': 'application/json',
|
||||
@ -32,6 +46,7 @@ def detect_face(image_url):
|
||||
conn.request("POST", "/face/v1.0/detect?%s" % params, body, headers)
|
||||
response = conn.getresponse()
|
||||
data = json.loads(response.read())
|
||||
print(data)
|
||||
conn.close()
|
||||
return data[0]["faceId"]
|
||||
|
||||
@ -102,12 +117,16 @@ def create_personId(personGroupId, personName):
|
||||
conn.request("POST", "/face/v1.0/persongroups/{}/persons?%s".format(personGroupId) % params, body, headers)
|
||||
response = conn.getresponse()
|
||||
data = json.loads(response.read())
|
||||
print(data)
|
||||
# print(data)
|
||||
conn.close()
|
||||
return data["personId"]
|
||||
|
||||
|
||||
def add_persistedFaceId(personGroupId, personId, image_url):
|
||||
r = requests.get(image_url)
|
||||
if r.status_code != 200:
|
||||
return None
|
||||
|
||||
headers = {
|
||||
'Content-Type': 'application/json',
|
||||
'Ocp-Apim-Subscription-Key': subscription_key,
|
||||
@ -123,11 +142,14 @@ def add_persistedFaceId(personGroupId, personId, image_url):
|
||||
})
|
||||
|
||||
conn = http.client.HTTPSConnection(uri_base)
|
||||
conn.request("POST", "/face/v1.0/persongroups/{}/persons/{}/persistedFaces?%s".format(personGroupId, personId) % params, body, headers)
|
||||
conn.request("POST",
|
||||
"/face/v1.0/persongroups/{}/persons/{}/persistedFaces?%s".format(personGroupId, personId) % params,
|
||||
body, headers)
|
||||
response = conn.getresponse()
|
||||
data = json.loads(response.read())
|
||||
print(data)
|
||||
conn.close()
|
||||
if "persistedFaceId" not in data:
|
||||
return None
|
||||
return data["persistedFaceId"]
|
||||
|
||||
|
||||
@ -161,7 +183,8 @@ def get_personGroupPerson(personGroupId, personId):
|
||||
body = json.dumps({})
|
||||
|
||||
conn = http.client.HTTPSConnection(uri_base)
|
||||
conn.request("GET", "/face/v1.0/persongroups/{}/persons/{}?%s".format(personGroupId, personId) % params, body, headers)
|
||||
conn.request("GET", "/face/v1.0/persongroups/{}/persons/{}?%s".format(personGroupId, personId) % params, body,
|
||||
headers)
|
||||
response = conn.getresponse()
|
||||
data = json.loads(response.read())
|
||||
print(data)
|
||||
@ -208,6 +231,7 @@ def eval(original_faceIds, personGroupId, protect_personId):
|
||||
conn.close()
|
||||
|
||||
face = data[0]
|
||||
print(face)
|
||||
if len(face["candidates"]) and face["candidates"][0]["personId"] == protect_personId:
|
||||
return True
|
||||
else:
|
||||
@ -225,48 +249,20 @@ def delete_personGroupPerson(personGroupId, personId):
|
||||
body = json.dumps({})
|
||||
|
||||
conn = http.client.HTTPSConnection(uri_base)
|
||||
conn.request("DELETE", "/face/v1.0/persongroups/{}/persons/{}?%s".format(personGroupId, personId) % params, body, headers)
|
||||
conn.request("DELETE", "/face/v1.0/persongroups/{}/persons/{}?%s".format(personGroupId, personId) % params, body,
|
||||
headers)
|
||||
response = conn.getresponse()
|
||||
data = response.read()
|
||||
print(data)
|
||||
conn.close()
|
||||
|
||||
|
||||
def add_protect_person(personGroupId, name):
|
||||
personId = create_personId(personGroupId, name)
|
||||
for idx in range(72):
|
||||
cloaked_image_url = "https://super.cs.uchicago.edu/~shawn/cloaked/{}_c.png".format(idx)
|
||||
add_persistedFaceId(personGroupId, personId, cloaked_image_url)
|
||||
|
||||
|
||||
def add_sybil_person(personGroupId, name):
|
||||
personId = create_personId(personGroupId, name)
|
||||
for idx in range(82):
|
||||
try:
|
||||
cloaked_image_url = "https://super.cs.uchicago.edu/~shawn/sybils/{}_c.png".format(idx)
|
||||
add_persistedFaceId(personGroupId, personId, cloaked_image_url)
|
||||
except:
|
||||
print(idx)
|
||||
|
||||
|
||||
def add_other_person(personGroupId):
|
||||
for idx_person in range(65):
|
||||
personId = create_personId(personGroupId, str(idx_person))
|
||||
for idx_image in range(90):
|
||||
try:
|
||||
image_url = "https://super.cs.uchicago.edu/~shawn/train/{}/{}.png".format(idx_person, idx_image)
|
||||
add_persistedFaceId(personGroupId, personId, image_url)
|
||||
except:
|
||||
print(idx_person, idx_image)
|
||||
|
||||
|
||||
def get_trainStatus(personGroupId):
|
||||
headers = {
|
||||
'Ocp-Apim-Subscription-Key': subscription_key,
|
||||
}
|
||||
|
||||
params = urllib.parse.urlencode({
|
||||
})
|
||||
params = urllib.parse.urlencode({})
|
||||
|
||||
body = json.dumps({})
|
||||
|
||||
@ -278,47 +274,74 @@ def get_trainStatus(personGroupId):
|
||||
conn.close()
|
||||
|
||||
|
||||
def test_original():
|
||||
personGroupId = 'pubfig'
|
||||
# create_personGroupId(personGroupId, 'pubfig')
|
||||
# add protect person
|
||||
protect_personId = 'd3df3012-6f3f-4c1b-b86d-55e91a352e01'
|
||||
#protect_personId = create_personId(personGroupId, 'Emily')
|
||||
#for idx in range(50):
|
||||
# image_url = "https://super.cs.uchicago.edu/~shawn/cloaked/{}_o.png".format(idx)
|
||||
# add_persistedFaceId(personGroupId, protect_personId, image_url)
|
||||
def test_cloak():
|
||||
NUM_TRAIN = 10
|
||||
total_idx = range(0, 82)
|
||||
TRAIN_RANGE = random.sample(total_idx, NUM_TRAIN)
|
||||
|
||||
TEST_RANGE = TRAIN_RANGE
|
||||
|
||||
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(65):
|
||||
# personId = create_personId(personGroupId, str(idx_person))
|
||||
# for idx_image in range(50):
|
||||
# try:
|
||||
# image_url = "https://super.cs.uchicago.edu/~shawn/train/{}/{}.png".format(idx_person, idx_image)
|
||||
# add_persistedFaceId(personGroupId, personId, image_url)
|
||||
# except:
|
||||
# print(idx_person, idx_image)
|
||||
|
||||
for idx_person in range(500):
|
||||
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)
|
||||
#time.sleep(3)
|
||||
#get_trainStatus(personGroupId)
|
||||
#list_personGroupPerson(personGroupId)
|
||||
train_personGroup(personGroupId)
|
||||
time.sleep(4)
|
||||
get_trainStatus(personGroupId)
|
||||
# list_personGroupPerson(personGroupId)
|
||||
|
||||
idx_range = range(50, 82)
|
||||
# test original image
|
||||
idx_range = TEST_RANGE
|
||||
acc = 0.
|
||||
|
||||
tot = 0.
|
||||
for idx in idx_range:
|
||||
original_image_url = "https://super.cs.uchicago.edu/~shawn/cloaked/{}_o.png".format(idx)
|
||||
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 /= len(idx_range)
|
||||
acc /= tot
|
||||
print(acc) # 1.0
|
||||
|
||||
|
||||
@ -358,42 +381,37 @@ def delete_personGroup(personGroupId):
|
||||
conn.close()
|
||||
|
||||
|
||||
|
||||
def main():
|
||||
test_cloak()
|
||||
|
||||
# delete_personGroup('cloaking')
|
||||
# delete_personGroup('cloaking-emily')
|
||||
# delete_personGroup('pubfig')
|
||||
# list_personGroups()
|
||||
# exit()
|
||||
personGroupId = 'cloaking'
|
||||
# personGroupId = 'cloaking'
|
||||
# create_personGroupId(personGroupId, 'cloaking')
|
||||
list_personGroups()
|
||||
exit()
|
||||
#delete_personGroupPerson(personGroupId, '0ac606cd-24b3-440f-866a-31adf2a1b446')
|
||||
#add_protect_person(personGroupId, 'Emily')
|
||||
#personId = create_personId(personGroupId, 'Emily')
|
||||
#add_sybil_person(personGroupId, 'sybil')
|
||||
protect_personId = '6c5a71eb-f39a-4570-b3f5-72cca3ab5a6b'
|
||||
#delete_personGroupPerson(personGroupId, protect_personId)
|
||||
#add_protect_person(personGroupId, 'Emily')
|
||||
|
||||
# train model based on personGroup
|
||||
#train_personGroup(personGroupId)
|
||||
get_trainStatus(personGroupId)
|
||||
#add_other_person(personGroupId)
|
||||
#list_personGroupPerson(personGroupId)
|
||||
#delete_personGroupPerson(personGroupId, '80e32c80-bc69-416a-9dff-c8d42d7a3301')
|
||||
|
||||
idx_range = range(72, 82)
|
||||
original_faceIds = []
|
||||
for idx in idx_range:
|
||||
original_image_url = "https://super.cs.uchicago.edu/~shawn/cloaked/{}_o.png".format(idx)
|
||||
faceId = detect_face(original_image_url)
|
||||
original_faceIds.append(faceId)
|
||||
|
||||
# verify
|
||||
eval(original_faceIds, personGroupId, protect_personId)
|
||||
# delete_personGroupPerson(personGroupId, '0ac606cd-24b3-440f-866a-31adf2a1b446')
|
||||
# add_protect_person(personGroupId, 'Emily')
|
||||
# protect_personId = create_personId(personGroupId, 'Emily')
|
||||
# add_sybil_person(personGroupId, 'sybil')
|
||||
#
|
||||
# # train model based on personGroup
|
||||
# train_personGroup(personGroupId)
|
||||
# get_trainStatus(personGroupId)
|
||||
# add_other_person(personGroupId)
|
||||
# list_personGroupPerson(personGroupId)
|
||||
#
|
||||
# idx_range = range(72, 82)
|
||||
# original_faceIds = []
|
||||
# for idx in idx_range:
|
||||
# original_image_url = "https://super.cs.uchicago.edu/~shawn/cloaked/{}_o.png".format(idx)
|
||||
# faceId = detect_face(original_image_url)
|
||||
# original_faceIds.append(faceId)
|
||||
#
|
||||
# # verify
|
||||
# eval(original_faceIds, personGroupId, protect_personId)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
test_cloak()
|
||||
|
Loading…
Reference in New Issue
Block a user