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https://github.com/Shawn-Shan/fawkes.git
synced 2024-12-22 07:09:33 +05:30
add option to bypass face detection step
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@ -84,7 +84,7 @@ class Fawkes(object):
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return th, max_step, lr
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def run_protection(self, image_paths, mode='min', th=0.04, sd=1e9, lr=10, max_step=500, batch_size=1, format='png',
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separate_target=True, debug=False):
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separate_target=True, debug=False, no_align=False):
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if mode == 'custom':
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pass
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else:
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@ -100,9 +100,9 @@ class Fawkes(object):
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return 3
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with graph.as_default():
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faces = Faces(image_paths, loaded_images, self.aligner, verbose=1)
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faces = Faces(image_paths, loaded_images, self.aligner, verbose=1, no_align=no_align)
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original_images = faces.cropped_faces
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if len(original_images) == 0:
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print("No face detected. ")
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return 2
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@ -184,12 +184,14 @@ def main(*argv):
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parser.add_argument('--max-step', help='only relevant with mode=custom, number of steps for optimization', type=int,
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default=1000)
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parser.add_argument('--sd', type=int, help='only relevant with mode=custom, penalty number, read more in the paper',
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default=1e6)
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default=1e9)
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parser.add_argument('--lr', type=float, help='only relevant with mode=custom, learning rate', default=2)
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parser.add_argument('--batch-size', help="number of images to run optimization together", type=int, default=1)
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parser.add_argument('--separate_target', help="whether select separate targets for each faces in the directory",
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action='store_true')
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parser.add_argument('--no-align', help="whether to detect and crop faces",
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action='store_true')
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parser.add_argument('--debug', help="turn on debug and copy/paste the stdout when reporting an issue on github",
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action='store_true')
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parser.add_argument('--format', type=str,
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@ -209,7 +211,7 @@ def main(*argv):
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protector.run_protection(image_paths, mode=args.mode, th=args.th, sd=args.sd, lr=args.lr,
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max_step=args.max_step,
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batch_size=args.batch_size, format=args.format,
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separate_target=args.separate_target, debug=args.debug)
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separate_target=args.separate_target, debug=args.debug, no_align=args.no_align)
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if __name__ == '__main__':
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@ -120,9 +120,11 @@ def filter_image_paths(image_paths):
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class Faces(object):
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def __init__(self, image_paths, loaded_images, aligner, verbose=1, eval_local=False, preprocessing=True):
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def __init__(self, image_paths, loaded_images, aligner, verbose=1, eval_local=False, preprocessing=True,
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no_align=False):
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self.image_paths = image_paths
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self.verbose = verbose
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self.no_align = no_align
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self.aligner = aligner
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self.org_faces = []
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self.cropped_faces = []
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@ -132,25 +134,27 @@ class Faces(object):
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for i in range(0, len(loaded_images)):
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cur_img = loaded_images[i]
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p = image_paths[i]
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self.org_faces.append(cur_img)
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if eval_local:
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margin = 0
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else:
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margin = 0.7
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align_img = align(cur_img, self.aligner, margin=margin)
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if not no_align:
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align_img = align(cur_img, self.aligner, margin=margin)
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if align_img is None:
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print("Find 0 face(s)".format(p.split("/")[-1]))
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continue
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cur_faces = align_img[0]
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else:
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cur_faces = [cur_img]
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cur_shapes = [f.shape[:-1] for f in cur_faces]
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cur_faces_square = []
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if verbose:
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if verbose and not no_align:
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print("Find {} face(s) in {}".format(len(cur_faces), p.split("/")[-1]))
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if eval_local:
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cur_faces = cur_faces[:1]
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@ -161,13 +165,19 @@ class Faces(object):
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else:
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long_size = max([img.shape[1], img.shape[0]])
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base = np.zeros((long_size, long_size, 3))
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# import pdb
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# pdb.set_trace()
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base[0:img.shape[0], 0:img.shape[1], :] = img
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cur_faces_square.append(base)
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cur_index = align_img[1]
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cur_faces_square = [resize(f, (224, 224)) for f in cur_faces_square]
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self.cropped_faces.extend(cur_faces_square)
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if not self.no_align:
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cur_index = align_img[1]
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self.cropped_faces_shape.extend(cur_shapes)
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self.cropped_faces.extend(cur_faces_square)
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self.cropped_index.extend(cur_index)
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self.callback_idx.extend([i] * len(cur_faces_square))
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@ -186,6 +196,8 @@ class Faces(object):
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return self.cropped_faces
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def merge_faces(self, protected_images, original_images):
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if self.no_align:
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return np.clip(protected_images, 0.0, 255.0)
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self.cloaked_faces = np.copy(self.org_faces)
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@ -520,6 +532,7 @@ def select_target_label(imgs, feature_extractors_ls, feature_extractors_names, m
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https://github.com/tensorflow/tensorflow/blob/v2.3.0/tensorflow/python/keras/utils/data_utils.py#L168-L297
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"""
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def get_file(fname,
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origin,
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untar=False,
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