mirror of
https://github.com/Shawn-Shan/fawkes.git
synced 2024-12-22 07:09:33 +05:30
add app
Former-commit-id: e7e46967035dfb727d180de0a0780ca9e026dd02 [formerly 0e703ac63e52aafbaa3033759553e2f3b31d2886] Former-commit-id: 9dfff8ea4c2646d90203b378e0732330e655086a
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63
app/app.py
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63
app/app.py
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@ -0,0 +1,63 @@
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import threading
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import fawkes.protection
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from tkinter import Tk, BOTH, StringVar
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from tkinter.ttk import Frame, Label, Style, Button
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from tkinter.filedialog import askdirectory, askopenfilenames
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class UI(Frame):
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def __init__(self):
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super().__init__()
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self.my_fawkes = fawkes.protection.Fawkes("high_extract", '0', 1)
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self.var = StringVar()
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self.var.set('Initial')
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self.img_paths = './imgs'
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self.initUI()
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def initUI(self):
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self.master.title("This is a Window")
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self.pack(fill=BOTH, expand=1)
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btn_Open = Button(self,
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text='open img directory',
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width=30,
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command=self.select_path)
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btn_Open.pack()
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btn_Run = Button(self,
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text='run the code',
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width=3,
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command=lambda: thread_it(self.my_fawkes.run_protection, self.img_paths))
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btn_Run.pack()
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Label_Show = Label(self,
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textvariable=self.var,
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font=('Arial', 13), width=50)
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Label_Show.pack()
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def select_path(self):
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self.img_paths = askopenfilenames(filetypes=[('image', "*.gif *.jpg *.png")])
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self.var.set('the paths have been set')
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root = Tk()
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root.title('window')
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root.geometry('600x500')
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app = UI()
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def main():
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root.mainloop()
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def thread_it(func, *args):
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app.var.set('cloak in process')
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t = threading.Thread(target=func, args=args)
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t.setDaemon(True)
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t.start()
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if __name__ == '__main__':
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main()
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@ -8,7 +8,7 @@ __version__ = '0.0.6'
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from .detect_faces import create_mtcnn, run_detect_face
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from .detect_faces import create_mtcnn, run_detect_face
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from .differentiator import FawkesMaskGeneration
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from .differentiator import FawkesMaskGeneration
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from .protection import main
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from .protection import main, Fawkes
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from .utils import load_extractor, init_gpu, select_target_label, dump_image, reverse_process_cloaked, Faces, get_file
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from .utils import load_extractor, init_gpu, select_target_label, dump_image, reverse_process_cloaked, Faces, get_file
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__all__ = (
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__all__ = (
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@ -16,5 +16,5 @@ __all__ = (
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'FawkesMaskGeneration', 'load_extractor',
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'FawkesMaskGeneration', 'load_extractor',
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'init_gpu',
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'init_gpu',
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'select_target_label', 'dump_image', 'reverse_process_cloaked',
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'select_target_label', 'dump_image', 'reverse_process_cloaked',
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'Faces', 'get_file', 'main',
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'Faces', 'get_file', 'main', 'Fawkes'
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)
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)
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@ -405,9 +405,9 @@ class FawkesMaskGeneration:
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if all_clear:
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if all_clear:
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break
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break
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# if iteration != 0 and iteration % (self.MAX_ITERATIONS // 2) == 0:
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if iteration != 0 and iteration % (self.MAX_ITERATIONS // 2) == 0:
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# LR = LR / 2
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LR = LR * 0.8
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# print("Learning Rate: ", LR)
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print("Learning Rate: ", LR)
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if iteration % (self.MAX_ITERATIONS // 5) == 0:
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if iteration % (self.MAX_ITERATIONS // 5) == 0:
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if self.verbose == 1:
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if self.verbose == 1:
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@ -18,7 +18,7 @@ import numpy as np
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from fawkes.differentiator import FawkesMaskGeneration
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from fawkes.differentiator import FawkesMaskGeneration
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from fawkes.utils import load_extractor, init_gpu, select_target_label, dump_image, reverse_process_cloaked, \
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from fawkes.utils import load_extractor, init_gpu, select_target_label, dump_image, reverse_process_cloaked, \
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Faces
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Faces
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from fawkes.align_face import aligner
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random.seed(12243)
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random.seed(12243)
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np.random.seed(122412)
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np.random.seed(122412)
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@ -54,10 +54,14 @@ def check_imgs(imgs):
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class Fawkes(object):
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class Fawkes(object):
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def __init__(self, feature_extractor, gpu, batch_size):
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def __init__(self, feature_extractor, gpu, batch_size):
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global graph
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graph = tf.get_default_graph()
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self.feature_extractor = feature_extractor
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self.feature_extractor = feature_extractor
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self.gpu = gpu
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self.gpu = gpu
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self.batch_size = batch_size
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self.batch_size = batch_size
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self.sess = init_gpu(gpu)
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self.sess = init_gpu(gpu)
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self.aligner = aligner(self.sess)
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self.fs_names = [feature_extractor]
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self.fs_names = [feature_extractor]
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if isinstance(feature_extractor, list):
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if isinstance(feature_extractor, list):
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self.fs_names = feature_extractor
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self.fs_names = feature_extractor
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@ -67,23 +71,23 @@ class Fawkes(object):
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def mode2param(self, mode):
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def mode2param(self, mode):
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if mode == 'low':
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if mode == 'low':
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th = 0.003
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th = 0.003
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max_step = 20
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max_step = 50
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lr = 20
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lr = 20
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elif mode == 'mid':
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elif mode == 'mid':
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th = 0.005
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th = 0.005
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max_step = 50
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max_step = 100
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lr = 15
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lr = 30
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elif mode == 'high':
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elif mode == 'high':
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th = 0.008
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th = 0.008
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max_step = 500
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max_step = 200
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lr = 15
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lr = 20
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elif mode == 'ultra':
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elif mode == 'ultra':
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if not tf.test.is_gpu_available():
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if not tf.test.is_gpu_available():
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print("Please enable GPU for ultra setting...")
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print("Please enable GPU for ultra setting...")
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sys.exit(1)
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sys.exit(1)
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th = 0.01
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th = 0.01
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max_step = 2000
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max_step = 200
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lr = 8
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lr = 20
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else:
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else:
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raise Exception("mode must be one of 'low', 'mid', 'high', 'ultra', 'custom'")
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raise Exception("mode must be one of 'low', 'mid', 'high', 'ultra', 'custom'")
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return th, max_step, lr
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return th, max_step, lr
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@ -99,8 +103,8 @@ class Fawkes(object):
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if not image_paths:
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if not image_paths:
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raise Exception("No images in the directory")
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raise Exception("No images in the directory")
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with graph.as_default():
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faces = Faces(image_paths, self.sess, verbose=1)
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faces = Faces(image_paths, self.aligner, verbose=1)
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original_images = faces.cropped_faces
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original_images = faces.cropped_faces
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original_images = np.array(original_images)
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original_images = np.array(original_images)
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@ -86,7 +86,7 @@ def load_image(path):
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class Faces(object):
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class Faces(object):
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def __init__(self, image_paths, sess, verbose=1):
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def __init__(self, image_paths, aligner, verbose=1):
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model_dir = os.path.join(os.path.expanduser('~'), '.fawkes')
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model_dir = os.path.join(os.path.expanduser('~'), '.fawkes')
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if not os.path.exists(os.path.join(model_dir, "mtcnn.p.gz")):
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if not os.path.exists(os.path.join(model_dir, "mtcnn.p.gz")):
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os.makedirs(model_dir, exist_ok=True)
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os.makedirs(model_dir, exist_ok=True)
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@ -94,7 +94,7 @@ class Faces(object):
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cache_subdir='')
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cache_subdir='')
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self.verbose = verbose
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self.verbose = verbose
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self.aligner = aligner(sess)
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self.aligner = aligner
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self.org_faces = []
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self.org_faces = []
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self.cropped_faces = []
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self.cropped_faces = []
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self.cropped_faces_shape = []
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self.cropped_faces_shape = []
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@ -14,10 +14,102 @@ data = f.read().split("\n")
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subscription_key = data[0]
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subscription_key = data[0]
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uri_base = data[1]
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uri_base = data[1]
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cloak_image_base = 'http://sandlab.cs.uchicago.edu/fawkes/files/cloak/{}_ultra_cloaked.png'
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cloak_image_base = 'http://sandlab.cs.uchicago.edu/fawkes/files/cloak/{}_high_cloaked.png'
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original_image_base = 'http://sandlab.cs.uchicago.edu/fawkes/files/cloak/{}.png'
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original_image_base = 'http://sandlab.cs.uchicago.edu/fawkes/files/cloak/{}.png'
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def test_cloak():
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NUM_TRAIN = 5
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total_idx = range(0, 82)
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TRAIN_RANGE = random.sample(total_idx, NUM_TRAIN)
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TEST_RANGE = random.sample([i for i in total_idx if i not in TRAIN_RANGE], 20)
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personGroupId = 'all'
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# delete_personGroup(personGroupId)
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# create_personGroupId(personGroupId, personGroupId)
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with open("protect_personId.txt", 'r') as f:
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protect_personId = f.read()
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print(protect_personId)
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delete_personGroupPerson(personGroupId, protect_personId)
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protect_personId = create_personId(personGroupId, 'Emily')
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with open("protect_personId.txt", 'w') as f:
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f.write(protect_personId)
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print("Created protect personId: {}".format(protect_personId))
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for idx in TRAIN_RANGE:
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image_url = cloak_image_base.format(idx)
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r = add_persistedFaceId(personGroupId, protect_personId, image_url)
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if r is not None:
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print("Added {}".format(idx))
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else:
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print("Unable to add {}-th image of protect person".format(idx))
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# add other people
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# for idx_person in range(5000, 15000):
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# personId = create_personId(personGroupId, str(idx_person))
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# print("Created personId: {}".format(idx_person))
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# for idx_image in range(10):
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# image_url = "http://sandlab.cs.uchicago.edu/fawkes/files/target_data/{}/{}.jpg".format(
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# idx_person, idx_image)
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# r = add_persistedFaceId(personGroupId, personId, image_url)
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# if r is not None:
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# print("Added {}".format(idx_image))
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# else:
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# print("Unable to add {}-th image".format(idx_image))
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# train model based on personGroup
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train_personGroup(personGroupId)
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while json.loads(get_trainStatus(personGroupId))['status'] != 'succeeded':
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time.sleep(2)
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# list_personGroupPerson(personGroupId)
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# test original image
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idx_range = TEST_RANGE
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acc = 0.
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tot = 0.
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for idx in idx_range:
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original_image_url = original_image_base.format(idx)
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faceId = detect_face(original_image_url)
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if faceId is None:
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print("{} does not exist".format(idx))
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continue
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original_faceIds = [faceId]
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# verify
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res = eval(original_faceIds, personGroupId, protect_personId)
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if res:
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acc += 1.
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tot += 1.
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acc /= tot
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print(acc) # 1.0
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def list_personGroups():
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headers = {
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'Ocp-Apim-Subscription-Key': subscription_key,
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}
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params = urllib.parse.urlencode({
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})
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body = json.dumps({})
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conn = http.client.HTTPSConnection(uri_base)
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conn.request("GET", "/face/v1.0/persongroups?%s" % params, body, headers)
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response = conn.getresponse()
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data = response.read()
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print(data)
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conn.close()
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def detect_face(image_url):
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def detect_face(image_url):
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r = requests.get(image_url)
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r = requests.get(image_url)
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if r.status_code != 200:
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if r.status_code != 200:
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@ -274,98 +366,6 @@ def get_trainStatus(personGroupId):
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return data
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return data
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def test_cloak():
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NUM_TRAIN = 10
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total_idx = range(0, 82)
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TRAIN_RANGE = random.sample(total_idx, NUM_TRAIN)
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TEST_RANGE = random.sample([i for i in total_idx if i not in TRAIN_RANGE], 20)
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personGroupId = 'all'
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# delete_personGroup(personGroupId)
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# create_personGroupId(personGroupId, personGroupId)
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with open("protect_personId.txt", 'r') as f:
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protect_personId = f.read()
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print(protect_personId)
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delete_personGroupPerson(personGroupId, protect_personId)
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protect_personId = create_personId(personGroupId, 'Emily')
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with open("protect_personId.txt", 'w') as f:
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f.write(protect_personId)
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print("Created protect personId: {}".format(protect_personId))
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for idx in TRAIN_RANGE:
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image_url = cloak_image_base.format(idx)
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r = add_persistedFaceId(personGroupId, protect_personId, image_url)
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if r is not None:
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print("Added {}".format(idx))
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else:
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print("Unable to add {}-th image of protect person".format(idx))
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# add other people
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# for idx_person in range(1300, 5000):
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# personId = create_personId(personGroupId, str(idx_person))
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# print("Created personId: {}".format(idx_person))
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# for idx_image in range(10):
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# image_url = "http://sandlab.cs.uchicago.edu/fawkes/files/target_data/{}/{}.jpg".format(
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# idx_person, idx_image)
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# r = add_persistedFaceId(personGroupId, personId, image_url)
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# if r is not None:
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# print("Added {}".format(idx_image))
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# else:
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# print("Unable to add {}-th image".format(idx_image))
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# train model based on personGroup
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train_personGroup(personGroupId)
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while json.loads(get_trainStatus(personGroupId))['status'] != 'succeeded':
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time.sleep(2)
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# list_personGroupPerson(personGroupId)
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# test original image
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idx_range = TEST_RANGE
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acc = 0.
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tot = 0.
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for idx in idx_range:
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original_image_url = original_image_base.format(idx)
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faceId = detect_face(original_image_url)
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if faceId is None:
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print("{} does not exist".format(idx))
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continue
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original_faceIds = [faceId]
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# verify
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res = eval(original_faceIds, personGroupId, protect_personId)
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if res:
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acc += 1.
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|
||||||
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):
|
def delete_personGroup(personGroupId):
|
||||||
headers = {
|
headers = {
|
||||||
'Ocp-Apim-Subscription-Key': subscription_key,
|
'Ocp-Apim-Subscription-Key': subscription_key,
|
Loading…
Reference in New Issue
Block a user