kopia lustrzana https://github.com/Shawn-Shan/fawkes
replace skimage resize with image resize
Shawn-Shan
rodzic
2b2d054118
commit
c52b38e152
|
|
@ -407,6 +407,8 @@ class FawkesMaskGeneration:
|
|||
|
||||
if iteration != 0 and iteration % (self.MAX_ITERATIONS // 3) == 0:
|
||||
LR = LR * 0.8
|
||||
if self.verbose:
|
||||
print("Learning rate: ", LR)
|
||||
|
||||
if iteration % (self.MAX_ITERATIONS // 5) == 0:
|
||||
if self.verbose == 1:
|
||||
|
|
|
|||
|
|
@ -26,16 +26,6 @@ def generate_cloak_images(protector, image_X, target_emb=None):
|
|||
return cloaked_image_X
|
||||
|
||||
|
||||
def check_imgs(imgs):
|
||||
if np.max(imgs) <= 1 and np.min(imgs) >= 0:
|
||||
imgs = imgs * 255.0
|
||||
elif np.max(imgs) <= 255 and np.min(imgs) >= 0:
|
||||
pass
|
||||
else:
|
||||
raise Exception("Image values ")
|
||||
return imgs
|
||||
|
||||
|
||||
class Fawkes(object):
|
||||
def __init__(self, feature_extractor, gpu, batch_size):
|
||||
|
||||
|
|
@ -66,7 +56,7 @@ class Fawkes(object):
|
|||
def mode2param(self, mode):
|
||||
if mode == 'low':
|
||||
th = 0.003
|
||||
max_step = 50
|
||||
max_step = 40
|
||||
lr = 20
|
||||
elif mode == 'mid':
|
||||
th = 0.005
|
||||
|
|
@ -89,7 +79,6 @@ class Fawkes(object):
|
|||
|
||||
def run_protection(self, image_paths, mode='low', th=0.04, sd=1e9, lr=10, max_step=500, batch_size=1, format='png',
|
||||
separate_target=True, debug=False):
|
||||
|
||||
if mode == 'custom':
|
||||
pass
|
||||
else:
|
||||
|
|
@ -101,11 +90,16 @@ class Fawkes(object):
|
|||
image_paths, loaded_images = filter_image_paths(image_paths)
|
||||
|
||||
if not image_paths:
|
||||
raise Exception("No images in the directory")
|
||||
print("No images in the directory")
|
||||
return 3
|
||||
|
||||
with graph.as_default():
|
||||
faces = Faces(image_paths, loaded_images, self.aligner, verbose=1)
|
||||
|
||||
original_images = faces.cropped_faces
|
||||
if len(original_images) == 0:
|
||||
print("No face detected. ")
|
||||
return 2
|
||||
original_images = np.array(original_images)
|
||||
|
||||
with sess.as_default():
|
||||
|
|
@ -143,16 +137,19 @@ class Fawkes(object):
|
|||
|
||||
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)
|
||||
|
||||
final_images = faces.merge_faces(reverse_process_cloaked(protected_images),
|
||||
reverse_process_cloaked(original_images))
|
||||
|
||||
for p_img, path in zip(final_images, image_paths):
|
||||
file_name = "{}_{}_cloaked.{}".format(".".join(path.split(".")[:-1]), mode, format)
|
||||
dump_image(p_img, file_name, format=format)
|
||||
|
||||
print("Done!")
|
||||
return None
|
||||
return 1
|
||||
|
||||
|
||||
def main(*argv):
|
||||
|
|
@ -201,9 +198,17 @@ def main(*argv):
|
|||
image_paths = [path for path in image_paths if "_cloaked" not in path.split("/")[-1]]
|
||||
|
||||
protector = Fawkes(args.feature_extractor, args.gpu, args.batch_size)
|
||||
protector.run_protection(image_paths, mode=args.mode, th=args.th, sd=args.sd, lr=args.lr, max_step=args.max_step,
|
||||
batch_size=args.batch_size, format=args.format,
|
||||
separate_target=args.separate_target, debug=args.debug)
|
||||
if args.mode != 'all':
|
||||
protector.run_protection(image_paths, mode=args.mode, th=args.th, sd=args.sd, lr=args.lr,
|
||||
max_step=args.max_step,
|
||||
batch_size=args.batch_size, format=args.format,
|
||||
separate_target=args.separate_target, debug=args.debug)
|
||||
else:
|
||||
for m in ['low', 'mid', 'high']:
|
||||
protector.run_protection(image_paths, mode=m, th=args.th, sd=args.sd, lr=args.lr,
|
||||
max_step=args.max_step,
|
||||
batch_size=args.batch_size, format=args.format,
|
||||
separate_target=args.separate_target, debug=args.debug)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
|
|
|
|||
|
|
@ -25,7 +25,7 @@ from PIL import Image, ExifTags
|
|||
from keras.layers import Dense, Activation, Dropout
|
||||
from keras.models import Model
|
||||
from keras.preprocessing import image
|
||||
from skimage.transform import resize
|
||||
# from skimage.transform import resize
|
||||
|
||||
from fawkes.align_face import align
|
||||
from six.moves.urllib.request import urlopen
|
||||
|
|
@ -140,7 +140,6 @@ class Faces(object):
|
|||
cur_faces_square = []
|
||||
if verbose:
|
||||
print("Find {} face(s) in {}".format(len(cur_faces), p.split("/")[-1]))
|
||||
|
||||
if eval_local:
|
||||
cur_faces = cur_faces[:1]
|
||||
|
||||
|
|
@ -152,16 +151,16 @@ class Faces(object):
|
|||
base = np.zeros((long_size, long_size, 3))
|
||||
base[0:img.shape[0], 0:img.shape[1], :] = img
|
||||
cur_faces_square.append(base)
|
||||
|
||||
cur_index = align_img[1]
|
||||
cur_faces_square = [resize(f, (224, 224)) for f in cur_faces_square]
|
||||
|
||||
self.cropped_faces_shape.extend(cur_shapes)
|
||||
self.cropped_faces.extend(cur_faces_square)
|
||||
self.cropped_index.extend(cur_index)
|
||||
self.callback_idx.extend([i] * len(cur_faces_square))
|
||||
|
||||
if not self.cropped_faces:
|
||||
raise Exception("No faces detected")
|
||||
if len(self.cropped_faces) == 0:
|
||||
return
|
||||
|
||||
self.cropped_faces = np.array(self.cropped_faces)
|
||||
|
||||
|
|
@ -173,15 +172,24 @@ class Faces(object):
|
|||
def get_faces(self):
|
||||
return self.cropped_faces
|
||||
|
||||
def merge_faces(self, cloaks):
|
||||
def merge_faces(self, protected_images, original_images):
|
||||
|
||||
self.cloaked_faces = np.copy(self.org_faces)
|
||||
|
||||
for i in range(len(self.cropped_faces)):
|
||||
cur_cloak = cloaks[i]
|
||||
# cur_cloak = cloaks[i]
|
||||
cur_protected = protected_images[i]
|
||||
cur_original = original_images[i]
|
||||
|
||||
org_shape = self.cropped_faces_shape[i]
|
||||
old_square_shape = max([org_shape[0], org_shape[1]])
|
||||
reshape_cloak = resize(cur_cloak, (old_square_shape, old_square_shape))
|
||||
|
||||
# reshape_cloak = resize(cur_cloak, (old_square_shape, old_square_shape))
|
||||
cur_protected = resize(cur_protected, (old_square_shape, old_square_shape))
|
||||
cur_original = resize(cur_original, (old_square_shape, old_square_shape))
|
||||
|
||||
reshape_cloak = cur_protected - cur_original
|
||||
|
||||
reshape_cloak = reshape_cloak[0:org_shape[0], 0:org_shape[1], :]
|
||||
|
||||
callback_id = self.callback_idx[i]
|
||||
|
|
@ -211,6 +219,15 @@ def load_victim_model(number_classes, teacher_model=None, end2end=False, dropout
|
|||
return model
|
||||
|
||||
|
||||
def resize(img, sz):
|
||||
assert np.min(img) >= 0 and np.max(img) <= 255.0
|
||||
|
||||
from keras.preprocessing import image
|
||||
im_data = image.array_to_img(img).resize((sz[1], sz[0]))
|
||||
im_data = image.img_to_array(im_data)
|
||||
return im_data
|
||||
|
||||
|
||||
def init_gpu(gpu_index, force=False):
|
||||
if isinstance(gpu_index, list):
|
||||
gpu_num = ','.join([str(i) for i in gpu_index])
|
||||
|
|
|
|||
Ładowanie…
Reference in New Issue