Why mtcnn downloads from external host as binary?

Hi, i wanted to try fawkes, but apparently mtcnn.p.gz isn't downloaded automatically and throws error instead.

$ fawkes -m low -d ./img
Traceback (most recent call last):
  File "/home/ilos-vigil/.local/bin/fawkes", line 8, in <module>
    sys.exit(main())
  File "/home/ilos-vigil/.local/lib/python3.6/site-packages/fawkes/protection.py", line 184, in main
    protector = Fawkes(args.feature_extractor, args.gpu, args.batch_size)
  File "/home/ilos-vigil/.local/lib/python3.6/site-packages/fawkes/protection.py", line 64, in __init__
    self.aligner = aligner(self.sess)
  File "/home/ilos-vigil/.local/lib/python3.6/site-packages/fawkes/align_face.py", line 16, in aligner
    pnet, rnet, onet = create_mtcnn(sess, None)
  File "/home/ilos-vigil/.local/lib/python3.6/site-packages/fawkes/detect_faces.py", line 262, in create_mtcnn
    fp = gzip.open(os.path.join(model_dir, "mtcnn.p.gz"), 'rb')
  File "/usr/local/lib/python3.6/gzip.py", line 53, in open
    binary_file = GzipFile(filename, gz_mode, compresslevel)
  File "/usr/local/lib/python3.6/gzip.py", line 163, in __init__
    fileobj = self.myfileobj = builtins.open(filename, mode or 'rb')
FileNotFoundError: [Errno 2] No such file or directory: '/home/ilos-vigil/.fawkes/mtcnn.p.gz'

I had to download mtcnn.p.gz manually before fawkes running without any problem

cd ./fawkes
wget http://sandlab.cs.uchicago.edu/fawkes/files/mtcnn.p.gz

Additional information :

• Parrot Security 4.9 (Based on Debian 10 unstable/testing)
• Python 3.6.11 (compiled from source code)
• fawkes (version 0.0.7) is installed locally with command pip3.6 install fawkes --user

Thank you for your efforts and research in this area.

I tried cloaking images with Fawkes default settings. When I try it against Amazon rekognition demos the cloak has little to no effect. What am I doing wrong?

e.g.

Celebrity recognition demo, download Bezos sample image, run fawkes, upload cloaked image - recognition match is still 100%

face comparison demo: uploaded original, and cloaked image - match was 99.9%

I can't use the linux binary, I'm using Manjaro linux. It is outputting this error

How can I resolve this?

ERROR: Could not find a version that satisfies the requirement tensorflow<=1.15.0,>=1.12.0 (from fawkes) (from versions: 2.2.0rc1, 2.2.0rc2, 2.2.0rc3, 2.2.0rc4, 2.2.0, 2.3.0rc0, 2.3.0rc1, 2.3.0rc2)
ERROR: No matching distribution found for tensorflow<=1.15.0,>=1.12.0 (from fawkes)

Would this cloaking method still be effective in distorting the training model if a screenshot of the cloaked image was used instead of the actual cloaked image?

When I try to install dependencies it gives the following error

ERROR: Could not find a version that satisfies the requirement tensorflow<=1.15.0,>=1.12.0 (from versions: 2.2.0rc3, 2.2.0rc4, 2.2.0, 2.3.0rc0, 2.3.0rc1, 2.3.0rc2)
ERROR: No matching distribution found for tensorflow<=1.15.0,>=1.12.0

Cloaked images are not saved under the original filename. Fir people who want to protect more then 1000 pictures of an existing blog etc

Feel free to rename the cloaked file as you wish.

Cant be a acceptable solution. Just a little checkbox or question if you want to overwrite existing files or create copies would save a LOT of nonsense work manually renaming more then 1000 pictures is not an option...

Thanks :)

Hey Fawkes team - great work. I've been hoping for something like this for awhile, and even experimented with more visible perturbation, but nothing as clean as what you have done.

I'm the lead developer at Guardian Project, a privacy-focused open-source mobile team, and we've helped groups like Tor, GPG, SQLCipher and others get their tech onto mobile devices. We also built ObscuraCam almost 10 years ago, and app focused on visual privacy and metadata cleaning. I think having Fawkes built into ObscuraCam would make a great deal of sense.

Other than resources or time, what are your concerns or challenges with bringing Fawkes to mobile?

When I try running Fawkes, I get the following output:

`Traceback (most recent call last):
File "urllib\request.py", line 1318, in do_open
File "http\client.py", line 1239, in request
File "http\client.py", line 1285, in _send_request
File "http\client.py", line 1234, in endheaders
File "http\client.py", line 1026, in _send_output
File "http\client.py", line 964, in send
File "http\client.py", line 936, in connect
File "socket.py", line 724, in create_connection
File "socket.py", line 713, in create_connection
ConnectionRefusedError: [WinError 10061] No connection could be made because the target machine actively refused it

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "fawkes\utils.py", line 520, in get_file
File "urllib\request.py", line 248, in urlretrieve
File "urllib\request.py", line 223, in urlopen
File "urllib\request.py", line 526, in open
File "urllib\request.py", line 544, in _open
File "urllib\request.py", line 504, in _call_chain
File "urllib\request.py", line 1346, in http_open
File "urllib\request.py", line 1320, in do_open
urllib.error.URLError: <urlopen error [WinError 10061] No connection could be made because the target machine actively refused it>

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "fawkes\protection.py", line 171, in
File "fawkes\protection.py", line 131, in main
File "fawkes\utils.py", line 95, in init
File "fawkes\utils.py", line 524, in get_file
Exception: URL fetch failure on http://sandlab.cs.uchicago.edu/fawkes/files/mtcnn.p.gz: None -- [WinError 10061] No connection could be made because the target machine actively refused it
[25400] Failed to execute script protection`

pip3 install fawkes

Collecting fawkes
Using cached fawkes-0.0.8-py3-none-any.whl (25 kB)
Collecting scikit-image
Using cached scikit_image-0.17.2-cp38-cp38-macosx_10_13_x86_64.whl (12.2 MB)
Collecting argparse
Downloading argparse-1.4.0-py2.py3-none-any.whl (23 kB)
Collecting pillow>=7.0.0
Using cached Pillow-7.2.0-cp38-cp38-macosx_10_10_x86_64.whl (2.2 MB)
Collecting numpy==1.16.4
Downloading numpy-1.16.4.zip (5.1 MB)
|████████████████████████████████| 5.1 MB 3.8 MB/s
Collecting keras<=2.3.1,>=2.2.5
Using cached Keras-2.3.1-py2.py3-none-any.whl (377 kB)
Collecting bleach>=2.1.0
Using cached bleach-3.1.5-py2.py3-none-any.whl (151 kB)
ERROR: Could not find a version that satisfies the requirement tensorflow<=1.15.0,>=1.12.0 (from fawkes) (from versions: 2.2.0rc3, 2.2.0rc4, 2.2.0, 2.3.0rc0, 2.3.0rc1, 2.3.0rc2)
ERROR: No matching distribution found for tensorflow<=1.15.0,>=1.12.0 (from fawkes)

It fails because no version of mentioned tensorflow found.

The README.md file mentions an argument with a typo: --seperate-target should be --separate-target as per protection.py's main().

Great work!

Please either add a checksum to your website or add to brew repository for mac 😊

How many times can Fawkes be applied to its own output before humans can notice degradation in the image?

Can you please tag a release here on GitHub so that Linux distributions can package fawkes?

Protection fails with the following error:

Traceback (most recent call last):
File "fawkes/protection.py", line 199, in
File "fawkes/protection.py", line 195, in main
File "fawkes/protection.py", line 137, in run_protection
File "fawkes/utils.py", line 172, in merge_faces
IndexError: index 1 is out of bounds for axis 0 with size 1
[7235] Failed to execute script protection

Please let me know if there are other details I can share.

Do you have any plans to issue a version for arm based architecture like Raspberry PI?
Or might that be an performance issue? PI 4 may have appropriate resources.

Thanks in advance

Program throws an error on Ubuntu 18.4.4

I'm using macOS Catalina and while fawkes works, it produces the following information in Terminal:

/Users/sixiongshan/venv/lib/python3.6/site-packages/PyInstaller/loader/pyimod03_importers.py:493: MatplotlibDeprecationWarning:
The MATPLOTLIBDATA environment variable was deprecated in Matplotlib 3.1 and will be removed in 3.3.

Even though this is not an issue, it mentions deprecation and contains a user name.

Doesn't work for me on a highly edited black and white image with sunglasses, does it need to detect a face to process an image?

Identify 1 files in the directory
Identify 1 images in the directory
Find 0 face(s)
Traceback (most recent call last):
  File "fawkes/protection.py", line 210, in <module>
  File "fawkes/protection.py", line 206, in main
  File "fawkes/protection.py", line 106, in run_protection
  File "fawkes/utils.py", line 165, in __init__
Exception: No faces detected
[114120] Failed to execute script protection

On my Mac Pro (5,1, dual X5690), MacOS 10.15.6:

[email protected] /Users/wojtek/Desktop ./protection-v0.3 -d /pics zsh: illegal hardware instruction ./protection-v0.3 -d /pics

Crash report:

`Process: protection-v0.3 [1782]
Path: /Users/USER/Desktop/protection-v0.3
Identifier: protection-v0.3
Version: ???
Code Type: X86-64 (Native)
Parent Process: ??? [1781]
Responsible: Terminal [1696]
User ID: 0

Date/Time: 2020-08-08 14:49:34.091 +0200
OS Version: Mac OS X 10.15.6 (19G73)
Report Version: 12
Anonymous UUID: xxxxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxxxxxx

Time Awake Since Boot: 3800 seconds

System Integrity Protection: disabled

Crashed Thread: 0 Dispatch queue: com.apple.main-thread

Exception Type: EXC_BAD_INSTRUCTION (SIGILL)
Exception Codes: 0x0000000000000001, 0x0000000000000000
Exception Note: EXC_CORPSE_NOTIFY

Termination Signal: Illegal instruction: 4
Termination Reason: Namespace SIGNAL, Code 0x4
Terminating Process: exc handler [1782]

Application Specific Information:
/tmp/_MEIvUUJ1d/libtensorflow_framework.1.dylib

Thread 0 Crashed:: Dispatch queue: com.apple.main-thread
0 libtensorflow_framework.1.dylib 0x000000014329b094 tensorflow::monitoring::MetricDef<(tensorflow::monitoring::MetricKind)1, long long, 2>::MetricDef<char [11], char [7]>(absl::string_view, absl::string_view, char const (&) [11], char const (&) [7]) + 68
1 libtensorflow_framework.1.dylib 0x00000001432960db tensorflow::monitoring::Counter<2>* tensorflow::monitoring::Counter<2>::New<char const (&) [46], char const (&) [58], char const (&) [11], char const (&) [7]>(char const (&) [46], char const (&) [58], char const (&) [11], char const (&) [7]) + 91
2 libtensorflow_framework.1.dylib 0x000000014329f161 _GLOBAL__sub_I_loader.cc + 49
3 dyld 0x0000000125ff41d3 ImageLoaderMachO::doModInitFunctions(ImageLoader::LinkContext const&) + 535
4 dyld 0x0000000125ff45de ImageLoaderMachO::doInitialization(ImageLoader::LinkContext const&) + 40
5 dyld 0x0000000125feeffb ImageLoader::recursiveInitialization(ImageLoader::LinkContext const&, unsigned int, char const*, ImageLoader::InitializerTimingList&, ImageLoader::UninitedUpwards&) + 493
6 dyld 0x0000000125feef66 ImageLoader::recursiveInitialization(ImageLoader::LinkContext const&, unsigned int, char const*, ImageLoader::InitializerTimingList&, ImageLoader::UninitedUpwards&) + 344
7 dyld 0x0000000125fed0b4 ImageLoader::processInitializers(ImageLoader::LinkContext const&, unsigned int, ImageLoader::InitializerTimingList&, ImageLoader::UninitedUpwards&) + 188
8 dyld 0x0000000125fed154 ImageLoader::runInitializers(ImageLoader::LinkContext const&, ImageLoader::InitializerTimingList&) + 82
9 dyld 0x0000000125fdeef2 dyld::runInitializers(ImageLoader*) + 82
10 dyld 0x0000000125fe8e8f dlopen_internal + 609
11 libdyld.dylib 0x00007fff68eced8a dlopen + 171
12 Python 0x0000000118687c57 _PyImport_FindSharedFuncptr + 295
13 Python 0x00000001186657c6 _PyImport_LoadDynamicModuleWithSpec + 598
14 Python 0x00000001186652c1 _imp_create_dynamic + 257
15 Python 0x00000001185c3bd2 PyCFunction_Call + 258
16 Python 0x000000011864364a _PyEval_EvalFrameDefault + 28666
17 Python 0x00000001186474ef _PyEval_EvalCodeWithName + 2447
18 Python 0x0000000118647da1 fast_function + 545
19 Python 0x0000000118646a61 call_function + 401
20 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
21 Python 0x0000000118647cfd fast_function + 381
22 Python 0x0000000118646a61 call_function + 401
23 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
24 Python 0x0000000118647cfd fast_function + 381
25 Python 0x0000000118646a61 call_function + 401
26 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
27 Python 0x0000000118647cfd fast_function + 381
28 Python 0x0000000118646a61 call_function + 401
29 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
30 Python 0x0000000118647cfd fast_function + 381
31 Python 0x0000000118646a61 call_function + 401
32 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
33 Python 0x0000000118647f1c _PyFunction_FastCallDict + 348
34 Python 0x000000011857ae57 _PyObject_FastCallDict + 247
35 Python 0x000000011857be78 _PyObject_CallMethodIdObjArgs + 520
36 Python 0x00000001186643fb PyImport_ImportModuleLevelObject + 1307
37 Python 0x0000000118641b3e _PyEval_EvalFrameDefault + 21742
38 Python 0x0000000118647cfd fast_function + 381
39 Python 0x0000000118646a61 call_function + 401
40 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
41 Python 0x00000001186474ef _PyEval_EvalCodeWithName + 2447
42 Python 0x000000011863c584 PyEval_EvalCode + 100
43 Python 0x0000000118639c04 builtin_exec + 548
44 Python 0x00000001185c3e1b _PyCFunction_FastCallDict + 491
45 Python 0x0000000118646a87 call_function + 439
46 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
47 Python 0x0000000118647cfd fast_function + 381
48 Python 0x0000000118646a61 call_function + 401
49 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
50 Python 0x0000000118647cfd fast_function + 381
51 Python 0x0000000118646a61 call_function + 401
52 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
53 Python 0x0000000118647cfd fast_function + 381
54 Python 0x0000000118646a61 call_function + 401
55 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
56 Python 0x0000000118647f1c _PyFunction_FastCallDict + 348
57 Python 0x000000011857ae57 _PyObject_FastCallDict + 247
58 Python 0x000000011857be78 _PyObject_CallMethodIdObjArgs + 520
59 Python 0x00000001186643fb PyImport_ImportModuleLevelObject + 1307
60 Python 0x0000000118641b3e _PyEval_EvalFrameDefault + 21742
61 Python 0x00000001186474ef _PyEval_EvalCodeWithName + 2447
62 Python 0x000000011863c584 PyEval_EvalCode + 100
63 Python 0x0000000118639c04 builtin_exec + 548
64 Python 0x00000001185c3e1b _PyCFunction_FastCallDict + 491
65 Python 0x0000000118646a87 call_function + 439
66 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
67 Python 0x0000000118647cfd fast_function + 381
68 Python 0x0000000118646a61 call_function + 401
69 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
70 Python 0x0000000118647cfd fast_function + 381
71 Python 0x0000000118646a61 call_function + 401
72 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
73 Python 0x0000000118647cfd fast_function + 381
74 Python 0x0000000118646a61 call_function + 401
75 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
76 Python 0x0000000118647f1c _PyFunction_FastCallDict + 348
77 Python 0x000000011857ae57 PyObject_FastCallDict + 247
78 Python 0x000000011857be78 PyObject_CallMethodIdObjArgs + 520
79 Python 0x00000001186643fb PyImport_ImportModuleLevelObject + 1307
80 Python 0x00000001186391a7 builtin___import + 135
81 Python 0x00000001185c3b32 PyCFunction_Call + 98
82 Python 0x000000011864364a _PyEval_EvalFrameDefault + 28666
83 Python 0x00000001186474ef _PyEval_EvalCodeWithName + 2447
84 Python 0x0000000118647da1 fast_function + 545
85 Python 0x0000000118646a61 call_function + 401
86 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
87 Python 0x00000001186474ef _PyEval_EvalCodeWithName + 2447
88 Python 0x00000001186480bb _PyFunction_FastCallDict + 763
89 Python 0x000000011857ae57 _PyObject_FastCallDict + 247
90 Python 0x000000011857be78 _PyObject_CallMethodIdObjArgs + 520
91 Python 0x00000001186646aa PyImport_ImportModuleLevelObject + 1994
92 Python 0x0000000118641b3e _PyEval_EvalFrameDefault + 21742
93 Python 0x00000001186474ef _PyEval_EvalCodeWithName + 2447
94 Python 0x000000011863c584 PyEval_EvalCode + 100
95 Python 0x0000000118639c04 builtin_exec + 548
96 Python 0x00000001185c3e1b _PyCFunction_FastCallDict + 491
97 Python 0x0000000118646a87 call_function + 439
98 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
99 Python 0x0000000118647cfd fast_function + 381
100 Python 0x0000000118646a61 call_function + 401
101 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
102 Python 0x0000000118647cfd fast_function + 381
103 Python 0x0000000118646a61 call_function + 401
104 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
105 Python 0x0000000118647cfd fast_function + 381
106 Python 0x0000000118646a61 call_function + 401
107 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
108 Python 0x0000000118647f1c _PyFunction_FastCallDict + 348
109 Python 0x000000011857ae57 _PyObject_FastCallDict + 247
110 Python 0x000000011857be78 _PyObject_CallMethodIdObjArgs + 520
111 Python 0x00000001186643fb PyImport_ImportModuleLevelObject + 1307
112 Python 0x0000000118641b3e _PyEval_EvalFrameDefault + 21742
113 Python 0x00000001186474ef _PyEval_EvalCodeWithName + 2447
114 Python 0x000000011863c584 PyEval_EvalCode + 100
115 Python 0x0000000118639c04 builtin_exec + 548
116 Python 0x00000001185c3e1b _PyCFunction_FastCallDict + 491
117 Python 0x0000000118646a87 call_function + 439
118 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
119 Python 0x0000000118647cfd fast_function + 381
120 Python 0x0000000118646a61 call_function + 401
121 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
122 Python 0x0000000118647cfd fast_function + 381
123 Python 0x0000000118646a61 call_function + 401
124 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
125 Python 0x0000000118647cfd fast_function + 381
126 Python 0x0000000118646a61 call_function + 401
127 Python 0x00000001186431f7 _PyEval_EvalFrameDefault + 27559
128 Python 0x0000000118647f1c _PyFunction_FastCallDict + 348
129 Python 0x000000011857ae57 _PyObject_FastCallDict + 247
130 Python 0x000000011857be78 _PyObject_CallMethodIdObjArgs + 520
131 Python 0x00000001186643fb PyImport_ImportModuleLevelObject + 1307
132 Python 0x0000000118641b3e _PyEval_EvalFrameDefault + 21742
133 Python 0x00000001186474ef _PyEval_EvalCodeWithName + 2447
134 Python 0x000000011863c584 PyEval_EvalCode + 100
135 protection-v0.3 0x000000010f6413b9 0x10f63f000 + 9145
136 protection-v0.3 0x000000010f64194a 0x10f63f000 + 10570
137 protection-v0.3 0x000000010f6400c4 0x10f63f000 + 4292

Thread 1:
0 libsystem_kernel.dylib 0x00007fff69027882 __psynch_cvwait + 10
1 libsystem_pthread.dylib 0x00007fff690ec425 _pthread_cond_wait + 698
2 libopenblasp-r0.3.7.dev.dylib 0x0000000119307c0b blas_thread_server + 619
3 libsystem_pthread.dylib 0x00007fff690ec109 _pthread_start + 148
4 libsystem_pthread.dylib 0x00007fff690e7b8b thread_start + 15

Thread 2:
0 libsystem_kernel.dylib 0x00007fff69027882 __psynch_cvwait + 10
1 libsystem_pthread.dylib 0x00007fff690ec425 _pthread_cond_wait + 698
2 libopenblasp-r0.3.7.dev.dylib 0x0000000119307c0b blas_thread_server + 619
3 libsystem_pthread.dylib 0x00007fff690ec109 _pthread_start + 148
4 libsystem_pthread.dylib 0x00007fff690e7b8b thread_start + 15

Thread 3:
0 libsystem_kernel.dylib 0x00007fff69027882 __psynch_cvwait + 10
1 libsystem_pthread.dylib 0x00007fff690ec425 _pthread_cond_wait + 698
2 libopenblasp-r0.3.7.dev.dylib 0x0000000119307c0b blas_thread_server + 619
3 libsystem_pthread.dylib 0x00007fff690ec109 _pthread_start + 148
4 libsystem_pthread.dylib 0x00007fff690e7b8b thread_start + 15

Thread 4:
0 libsystem_kernel.dylib 0x00007fff69027882 __psynch_cvwait + 10
1 libsystem_pthread.dylib 0x00007fff690ec425 _pthread_cond_wait + 698
2 libopenblasp-r0.3.7.dev.dylib 0x0000000119307c0b blas_thread_server + 619
3 libsystem_pthread.dylib 0x00007fff690ec109 _pthread_start + 148
4 libsystem_pthread.dylib 0x00007fff690e7b8b thread_start + 15

Thread 5:
0 libsystem_kernel.dylib 0x00007fff69027882 __psynch_cvwait + 10
1 libsystem_pthread.dylib 0x00007fff690ec425 _pthread_cond_wait + 698
2 libopenblasp-r0.3.7.dev.dylib 0x0000000119307c0b blas_thread_server + 619
3 libsystem_pthread.dylib 0x00007fff690ec109 _pthread_start + 148
4 libsystem_pthread.dylib 0x00007fff690e7b8b thread_start + 15

Thread 6:
0 libsystem_kernel.dylib 0x00007fff69027882 __psynch_cvwait + 10
1 libsystem_pthread.dylib 0x00007fff690ec425 _pthread_cond_wait + 698
2 libopenblasp-r0.3.7.dev.dylib 0x0000000119307c0b blas_thread_server + 619
3 libsystem_pthread.dylib 0x00007fff690ec109 _pthread_start + 148
4 libsystem_pthread.dylib 0x00007fff690e7b8b thread_start + 15

Thread 7:
0 libsystem_kernel.dylib 0x00007fff69027882 __psynch_cvwait + 10
1 libsystem_pthread.dylib 0x00007fff690ec425 _pthread_cond_wait + 698
2 libopenblasp-r0.3.7.dev.dylib 0x0000000119307c0b blas_thread_server + 619
3 libsystem_pthread.dylib 0x00007fff690ec109 _pthread_start + 148
4 libsystem_pthread.dylib 0x00007fff690e7b8b thread_start + 15

Thread 8:
0 libsystem_kernel.dylib 0x00007fff69027882 __psynch_cvwait + 10
1 libsystem_pthread.dylib 0x00007fff690ec425 _pthread_cond_wait + 698
2 libopenblasp-r0.3.7.dev.dylib 0x0000000119307c0b blas_thread_server + 619
3 libsystem_pthread.dylib 0x00007fff690ec109 _pthread_start + 148
4 libsystem_pthread.dylib 0x00007fff690e7b8b thread_start + 15

Thread 9:
0 libsystem_kernel.dylib 0x00007fff69027882 __psynch_cvwait + 10
1 libsystem_pthread.dylib 0x00007fff690ec425 _pthread_cond_wait + 698
2 libopenblasp-r0.3.7.dev.dylib 0x0000000119307c0b blas_thread_server + 619
3 libsystem_pthread.dylib 0x00007fff690ec109 _pthread_start + 148
4 libsystem_pthread.dylib 0x00007fff690e7b8b thread_start + 15

Thread 10:
0 libsystem_kernel.dylib 0x00007fff69027882 __psynch_cvwait + 10
1 libsystem_pthread.dylib 0x00007fff690ec425 _pthread_cond_wait + 698
2 libopenblasp-r0.3.7.dev.dylib 0x0000000119307c0b blas_thread_server + 619
3 libsystem_pthread.dylib 0x00007fff690ec109 _pthread_start + 148
4 libsystem_pthread.dylib 0x00007fff690e7b8b thread_start + 15

Thread 11:
0 libsystem_kernel.dylib 0x00007fff69027882 __psynch_cvwait + 10
1 libsystem_pthread.dylib 0x00007fff690ec425 _pthread_cond_wait + 698
2 libopenblasp-r0.3.7.dev.dylib 0x0000000119307c0b blas_thread_server + 619
3 libsystem_pthread.dylib 0x00007fff690ec109 _pthread_start + 148
4 libsystem_pthread.dylib 0x00007fff690e7b8b thread_start + 15

Thread 0 crashed with X86 Thread State (64-bit):
rax: 0x21c94e0a1fc50039 rbx: 0x00000001442d3ce0 rcx: 0x00000001442d3d0e rdx: 0x000000000000002d
rdi: 0x00007ffee05b7e00 rsi: 0x00000001442d3ce0 rbp: 0x00007ffee05b7de0 rsp: 0x00007ffee05b7d30
r8: 0x0000000000000039 r9: 0x00000001442d3d48 r10: 0x00000000e01fffff r11: 0x0000000000000000
r12: 0x00007ffee05b7e00 r13: 0x00000001442d3d48 r14: 0x00007ff72f5067c0 r15: 0x000000000000002d
rip: 0x000000014329b094 rfl: 0x0000000000010206 cr2: 0x000000014329b050

Logical CPU: 16
Error Code: 0x00000000
Trap Number: 6

Binary Images:
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0x7fff66caa000 - 0x7fff66d9afff libiconv.2.dylib (59) <18311A67-E4EF-3CC7-95B3-C0EDEE3A282F> /usr/lib/libiconv.2.dylib
0x7fff66d9b000 - 0x7fff66ff2fff libicucore.A.dylib (64260.0.1) <8AC2CB07-E7E0-340D-A849-186FA1F27251> /usr/lib/libicucore.A.dylib
0x7fff6700c000 - 0x7fff6700dfff liblangid.dylib (133) <30CFC08C-EF36-3CF5-8AEA-C1CB070306B7> /usr/lib/liblangid.dylib
0x7fff6700e000 - 0x7fff67026ff3 liblzma.5.dylib (16) /usr/lib/liblzma.5.dylib
0x7fff6703e000 - 0x7fff670e5ff7 libmecab.dylib (883.11) <2DF2B2E9-438D-326E-89C8-DD5247ABFE08> /usr/lib/libmecab.dylib
0x7fff670e6000 - 0x7fff67348ff1 libmecabra.dylib (883.11) <787FF18A-7440-3C30-A10C-7A34C63D3080> /usr/lib/libmecabra.dylib
0x7fff67814000 - 0x7fff67c90ff5 libnetwork.dylib (1880.120.4) /usr/lib/libnetwork.dylib
0x7fff67d31000 - 0x7fff67d63fde libobjc.A.dylib (787.1) <265783CE-6D74-36C9-B6D2-95D3910199EC> /usr/lib/libobjc.A.dylib
0x7fff67d76000 - 0x7fff67d7afff libpam.2.dylib (25.100.1) <0502F395-8EE6-3D2A-9239-06FD5622E19E> /usr/lib/libpam.2.dylib
0x7fff67d7d000 - 0x7fff67db3ff7 libpcap.A.dylib (89.120.1) /usr/lib/libpcap.A.dylib
0x7fff67eab000 - 0x7fff6808dff7 libsqlite3.dylib (308.5) /usr/lib/libsqlite3.dylib
0x7fff682de000 - 0x7fff682e1ffb libutil.dylib (57) /usr/lib/libutil.dylib
0x7fff682e2000 - 0x7fff682efff7 libxar.1.dylib (425.2) /usr/lib/libxar.1.dylib
0x7fff682f5000 - 0x7fff683d7ff7 libxml2.2.dylib (33.4) /usr/lib/libxml2.2.dylib
0x7fff683db000 - 0x7fff68403fff libxslt.1.dylib (16.9) <34A45627-DA5B-37D2-9609-65B425E0010A> /usr/lib/libxslt.1.dylib
0x7fff68404000 - 0x7fff68416ff3 libz.1.dylib (76) <793D9643-CD83-3AAC-8B96-88D548FAB620> /usr/lib/libz.1.dylib
0x7fff68cc5000 - 0x7fff68ccaff3 libcache.dylib (83) <5940876E-AC8A-3BE0-80B3-DE3FB14E257A> /usr/lib/system/libcache.dylib
0x7fff68ccb000 - 0x7fff68cd6fff libcommonCrypto.dylib (60165.120.1) /usr/lib/system/libcommonCrypto.dylib
0x7fff68cd7000 - 0x7fff68cdefff libcompiler_rt.dylib (101.2) <6E80AC11-A277-31FA-AEEF-E5A528274C77> /usr/lib/system/libcompiler_rt.dylib
0x7fff68cdf000 - 0x7fff68ce8ff7 libcopyfile.dylib (166.40.1) /usr/lib/system/libcopyfile.dylib
0x7fff68ce9000 - 0x7fff68d7bfdb libcorecrypto.dylib (866.140.1) <0B6C52DB-5A50-3FCD-8B5E-C0C2F35857E3> /usr/lib/system/libcorecrypto.dylib
0x7fff68e88000 - 0x7fff68ec8ff0 libdispatch.dylib (1173.100.2) /usr/lib/system/libdispatch.dylib
0x7fff68ec9000 - 0x7fff68efffff libdyld.dylib (750.6) <24C41E8B-6B33-30C7-94C9-02D2BD051D66> /usr/lib/system/libdyld.dylib
0x7fff68f00000 - 0x7fff68f00ffb libkeymgr.dylib (30) <6F582FDB-EB1A-3ED2-A989-B750643E2647> /usr/lib/system/libkeymgr.dylib
0x7fff68f01000 - 0x7fff68f0dff3 libkxld.dylib (6153.141.1) <756B1F0D-2E37-31A7-A6F0-2E5C22E62C3D> /usr/lib/system/libkxld.dylib
0x7fff68f0e000 - 0x7fff68f0eff7 liblaunch.dylib (1738.140.1) /usr/lib/system/liblaunch.dylib
0x7fff68f0f000 - 0x7fff68f14ff7 libmacho.dylib (959.0.1) <1B0296B5-3FD0-342C-BCC2-9886351A4391> /usr/lib/system/libmacho.dylib
0x7fff68f15000 - 0x7fff68f17ff3 libquarantine.dylib (110.40.3) <67FE2676-F9E8-3797-AEE5-F5F9D191CFA3> /usr/lib/system/libquarantine.dylib
0x7fff68f18000 - 0x7fff68f19ff7 libremovefile.dylib (48) <5CEBDAB2-988A-3B66-87BC-3C45D1C08730> /usr/lib/system/libremovefile.dylib
0x7fff68f1a000 - 0x7fff68f31ff3 libsystem_asl.dylib (377.60.2) <7A07FF86-658E-35D7-8136-829737E98B7B> /usr/lib/system/libsystem_asl.dylib
0x7fff68f32000 - 0x7fff68f32ff7 libsystem_blocks.dylib (74) <0D53847E-AF5F-3ACF-B51F-A15DEA4DEC58> /usr/lib/system/libsystem_blocks.dylib
0x7fff68f33000 - 0x7fff68fbafff libsystem_c.dylib (1353.100.2) /usr/lib/system/libsystem_c.dylib
0x7fff68fbb000 - 0x7fff68fbeffb libsystem_configuration.dylib (1061.141.1) <0EE84C33-64FD-372B-974A-AF7A136F2068> /usr/lib/system/libsystem_configuration.dylib
0x7fff68fbf000 - 0x7fff68fc2fff libsystem_coreservices.dylib (114) <08B89E9B-C5B2-3E73-8964-03E58692B21F> /usr/lib/system/libsystem_coreservices.dylib
0x7fff68fc3000 - 0x7fff68fcbfff libsystem_darwin.dylib (1353.100.2) /usr/lib/system/libsystem_darwin.dylib
0x7fff68fcc000 - 0x7fff68fd3fff libsystem_dnssd.dylib (1096.100.3) <01E0965B-83E5-356C-AC1F-C723F5AAB483> /usr/lib/system/libsystem_dnssd.dylib
0x7fff68fd4000 - 0x7fff68fd5ffb libsystem_featureflags.dylib (17) <6317641E-B43F-36A3-974E-6073786B94B9> /usr/lib/system/libsystem_featureflags.dylib
0x7fff68fd6000 - 0x7fff69023ff7 libsystem_info.dylib (538) <4DD813CB-D7B0-3AB5-9054-D2E4FF7A64B9> /usr/lib/system/libsystem_info.dylib
0x7fff69024000 - 0x7fff69050ff7 libsystem_kernel.dylib (6153.141.1) <2B6311E6-6240-3EF7-8C87-475B66F7452C> /usr/lib/system/libsystem_kernel.dylib
0x7fff69051000 - 0x7fff6909cfef libsystem_m.dylib (3178) <1356B031-5FFD-3324-B440-1F61570BB667> /usr/lib/system/libsystem_m.dylib
0x7fff6909d000 - 0x7fff690c4fff libsystem_malloc.dylib (283.100.6) <059F4DBD-856A-3A59-8B20-FD4B6918C5F2> /usr/lib/system/libsystem_malloc.dylib
0x7fff690c5000 - 0x7fff690d2ffb libsystem_networkextension.dylib (1095.140.2) <4CCE78C9-1DC4-3375-9828-D5BD739D23F3> /usr/lib/system/libsystem_networkextension.dylib
0x7fff690d3000 - 0x7fff690dcff7 libsystem_notify.dylib (241.100.2) /usr/lib/system/libsystem_notify.dylib
0x7fff690dd000 - 0x7fff690e5fef libsystem_platform.dylib (220.100.1) <97E825F6-D823-366C-9FF3-B1C8EA891044> /usr/lib/system/libsystem_platform.dylib
0x7fff690e6000 - 0x7fff690f0fff libsystem_pthread.dylib (416.100.3) <80B053AA-B6F7-3B59-BC44-78A5A4F7368F> /usr/lib/system/libsystem_pthread.dylib
0x7fff690f1000 - 0x7fff690f5ff3 libsystem_sandbox.dylib (1217.140.4) <20BF94E2-DAB8-3EBE-AACE-99DF84C1C391> /usr/lib/system/libsystem_sandbox.dylib
0x7fff690f6000 - 0x7fff690f8fff libsystem_secinit.dylib (62.100.2) <28EDEB6F-899B-373D-B761-4C20D39285D9> /usr/lib/system/libsystem_secinit.dylib
0x7fff690f9000 - 0x7fff69100ffb libsystem_symptoms.dylib (1238.120.1) <22800D8C-5C2A-3171-8C29-311BBE67F198> /usr/lib/system/libsystem_symptoms.dylib
0x7fff69101000 - 0x7fff69117ff2 libsystem_trace.dylib (1147.120) /usr/lib/system/libsystem_trace.dylib
0x7fff69119000 - 0x7fff6911eff7 libunwind.dylib (35.4) <42B7B509-BAFE-365B-893A-72414C92F5BF> /usr/lib/system/libunwind.dylib
0x7fff6911f000 - 0x7fff69154ffe libxpc.dylib (1738.140.1) <58E276A9-EE11-3F02-9D3E-5371E604E677> /usr/lib/system/libxpc.dylib

External Modification Summary:
Calls made by other processes targeting this process:
task_for_pid: 0
thread_create: 0
thread_set_state: 0
Calls made by this process:
task_for_pid: 0
thread_create: 0
thread_set_state: 0
Calls made by all processes on this machine:
task_for_pid: 2481
thread_create: 0
thread_set_state: 0

VM Region Summary:
ReadOnly portion of Libraries: Total=937.7M resident=0K(0%) swapped_out_or_unallocated=937.7M(100%)
Writable regions: Total=1.2G written=0K(0%) resident=0K(0%) swapped_out=0K(0%) unallocated=1.2G(100%)

                            VIRTUAL   REGION 

REGION TYPE SIZE COUNT (non-coalesced)
=========== ======= =======
Kernel Alloc Once 8K 1
MALLOC 121.2M 29
MALLOC guard page 24K 5
MALLOC_MEDIUM (reserved) 720.0M 6 reserved VM address space (unallocated)
STACK GUARD 56.0M 12
Stack 13.6M 12
VM_ALLOCATE 4K 1
VM_ALLOCATE (reserved) 352.0M 2 reserved VM address space (unallocated)
__DATA 11.6M 169
__DATA_CONST 20K 1
__LINKEDIT 685.2M 42
__OBJC_RO 32.3M 1
__OBJC_RW 1908K 2
__TEXT 252.4M 159
__UNICODE 564K 1
shared memory 12K 3
=========== ======= =======
TOTAL 2.2G 446
TOTAL, minus reserved VM space 1.1G 446

`

After install it with python3 setup.py install without issues I run fawkes and I get the following issue:

fawkes
Traceback (most recent call last):
File "/usr/local/bin/fawkes", line 33, in
sys.exit(load_entry_point('fawkes==0.3.1', 'console_scripts', 'fawkes')())
File "/usr/local/bin/fawkes", line 25, in importlib_load_entry_point
return next(matches).load()
File "/home/dragonxtek/.local/lib/python3.6/site-packages/importlib_metadata/init.py", line 96, in load
module = import_module(match.group('module'))
File "/usr/lib/python3.6/importlib/init.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "", line 994, in _gcd_import
File "", line 971, in _find_and_load
File "", line 955, in _find_and_load_unlocked
File "", line 665, in _load_unlocked
File "", line 678, in exec_module
File "", line 219, in _call_with_frames_removed
File "/usr/local/lib/python3.6/dist-packages/fawkes-0.3.1-py3.6.egg/fawkes/init.py", line 9, in
from .detect_faces import create_mtcnn, run_detect_face
File "/usr/local/lib/python3.6/dist-packages/fawkes-0.3.1-py3.6.egg/fawkes/detect_faces.py", line 33, in
import tensorflow as tf
File "/home/dragonxtek/.local/lib/python3.6/site-packages/tensorflow/init.py", line 28, in
from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import
File "/home/dragonxtek/.local/lib/python3.6/site-packages/tensorflow/python/init.py", line 52, in
from tensorflow.core.framework.graph_pb2 import *
File "/home/dragonxtek/.local/lib/python3.6/site-packages/tensorflow/core/framework/graph_pb2.py", line 16, in
from tensorflow.core.framework import node_def_pb2 as tensorflow_dot_core_dot_framework_dot_node__def__pb2
File "/home/dragonxtek/.local/lib/python3.6/site-packages/tensorflow/core/framework/node_def_pb2.py", line 16, in
from tensorflow.core.framework import attr_value_pb2 as tensorflow_dot_core_dot_framework_dot_attr__value__pb2
File "/home/dragonxtek/.local/lib/python3.6/site-packages/tensorflow/core/framework/attr_value_pb2.py", line 16, in
from tensorflow.core.framework import tensor_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__pb2
File "/home/dragonxtek/.local/lib/python3.6/site-packages/tensorflow/core/framework/tensor_pb2.py", line 16, in
from tensorflow.core.framework import resource_handle_pb2 as tensorflow_dot_core_dot_framework_dot_resource__handle__pb2
File "/home/dragonxtek/.local/lib/python3.6/site-packages/tensorflow/core/framework/resource_handle_pb2.py", line 23, in
serialized_pb=_b('\n/tensorflow/core/framework/resource_handle.proto\x12\ntensorflow"r\n\x13ResourceHandleProto\x12\x0e\n\x06\x64\x65vice\x18\x01 \x01(\t\x12\x11\n\tcontainer\x18\x02 \x01(\t\x12\x0c\n\x04name\x18\x03 \x01(\t\x12\x11\n\thash_code\x18\x04 \x01(\x04\x12\x17\n\x0fmaybe_type_name\x18\x05 \x01(\tBn\n\x18org.tensorflow.frameworkB\x0eResourceHandleP\x01Z=github.com/tensorflow/tensorflow/tensorflow/go/core/framework\xf8\x01\x01\x62\x06proto3')
TypeError: new() got an unexpected keyword argument 'serialized_options'

What I need to resolve?

您好，请问下这个怎么解决呢？
PS F:\job1\fawkes_binary_windows-v0.2 (1)> .\protection-v0.2.exe -d F:/job1/fawkes_img
Traceback (most recent call last):
File "fawkes\protection.py", line 210, in
File "fawkes\protection.py", line 203, in main
File "fawkes\protection.py", line 61, in init
File "fawkes\protection.py", line 61, in
File "fawkes\utils.py", line 367, in load_extractor
File "keras\engine\saving.py", line 492, in load_wrapper
File "keras\engine\saving.py", line 583, in load_model
File "keras\utils\io_utils.py", line 191, in init
File "h5py_hl\files.py", line 408, in init
File "h5py_hl\files.py", line 173, in make_fid
File "h5py_objects.pyx", line 54, in h5py._objects.with_phil.wrapper
File "h5py_objects.pyx", line 55, in h5py._objects.with_phil.wrapper
File "h5py\h5f.pyx", line 88, in h5py.h5f.open
OSError: Unable to open file (truncated file: eof = 9510912, sblock->base_addr = 0, stored_eof = 29292232)
[1828] Failed to execute script protection
PS F:\job1\fawkes_binary_windows-v0.2 (1)>

Originally posted by @zidielucky in #24 (comment)

OS: Artix Linux 64bit
Python: v3.8.3-1
Python-pip: v20.1.1-1

Can't install fawkes. Pip output:

❯ pip install fawkes        

Defaulting to user installation because normal site-packages is not writeable
Requirement already satisfied: fawkes in /usr/lib/python3.8/site-packages/fawkes-0.0.9-py3.8.egg (0.0.9)
Collecting numpy==1.16.4
  Using cached numpy-1.16.4.zip (5.1 MB)
ERROR: Could not find a version that satisfies the requirement tensorflow<=1.15.0,>=1.12.0 (from fawkes) (from versions: 2.2.0rc1, 2.2.0rc2, 2.2.0rc3, 2.2.0rc4, 2.2.0, 2.3.0rc0, 2.3.0rc1, 2.3.0rc2)
ERROR: No matching distribution found for tensorflow<=1.15.0,>=1.12.0 (from fawkes)

Using the setup.py doesn't work either (same error)

yur tool could be greath. but before i will try yu should provide a secure website. thanks a lot

Version 0.3 which downloaded from here for windows gives "Failed to execute script app_qr" error when running on Windows 10.

Command:
fawkes -d ./myphoto --mode min

Error:

[libprotobuf ERROR google/protobuf/descriptor_database.cc:394] Invalid file descriptor data passed to EncodedDescriptorDatabase::Add().
[libprotobuf FATAL google/protobuf/descriptor.cc:1356] CHECK failed: GeneratedDatabase()->Add(encoded_file_descriptor, size): 
libc++abi.dylib: terminating with uncaught exception of type google::protobuf::FatalException: CHECK failed: GeneratedDatabase()->Add(encoded_file_descriptor, size): 
Abort trap: 6

System:

Python 3.7.7 (default, Mar 10 2020, 15:43:03) 
[Clang 11.0.0 (clang-1100.0.33.17)] on darwin

The zip of the mac binaries just include a file named "protection-v0.2" - did I miss any information, or is this a failure?

BR, Zappo

I ran fawkes in a directory where I kept four images. Mind you, all of these images are of cartons and pens, so none contain any faces (neither human nor animal). Here's my log from running fawkes on macOS Catalina:

./protection -d Photos
/Users/sixiongshan/venv/lib/python3.6/site-packages/PyInstaller/loader/pyimod03_importers.py:493: MatplotlibDeprecationWarning:
The MATPLOTLIBDATA environment variable was deprecated in Matplotlib 3.1 and will be removed in 3.3.
Identify 4 images
Find 0 face(s) in IMG_20200723_094514.jpg
Find 0 face(s) in IMG_20200723_094438.jpg
Find 0 face(s) in IMG_20200723_094603.jpg
Find 2 face(s) in IMG_20200723_094526.jpg
Attacker loaded
2 batches in total
processing batch 0 at 2020-07-23 10:43:47.320197
START: Total loss: 8.6843E-01; perturb: 0.000000 (0.00% over, raw: 0.000000); sim: 0.868433
ITER 0 perturb: 0.00000; sim: 0.864359
ITER 10 perturb: 0.00131; sim: 0.785477
ITER 20 perturb: 0.00202; sim: 0.791557
Learning Rate: 16.0
ITER 30 perturb: 0.00202; sim: 0.791531
ITER 40 perturb: 0.00202; sim: 0.791507
END: Total loss: 7.9148E-01; perturb: 0.000000 (raw: 0.002021); sim: 0.791484
processing batch 1 at 2020-07-23 10:44:49.068363
START: Total loss: 8.7156E-01; perturb: 0.000000 (0.00% over, raw: 0.000000); sim: 0.871560
ITER 0 perturb: 0.00000; sim: 0.866800
ITER 10 perturb: 0.00094; sim: 0.800822
ITER 20 perturb: 0.00402; sim: 0.751458
Learning Rate: 16.0
ITER 30 perturb: 0.00219; sim: 0.788083
ITER 40 perturb: 0.00219; sim: 0.788057
END: Total loss: 7.8803E-01; perturb: 0.000000 (raw: 0.002187); sim: 0.788033
attack cost 108.277927 s
attack cost 168.452666 s
Done!

Only the images IMG_20200723_094514.jpg and IMG_20200723_094438.jpg generated cloaked versions. The two other ones remained untouched.

Hello! Can you help me to solve this error please.

OS: Windows 7 Professional 64-bit (6.1, Build 7601)
Memory: 8192MB RAM (8 GB usable)
Processor: Intel(R) Pentium(R) CPU G3460 @3.50Ghz
Display adapter: Intel(R) HD Graphics (integrated)

C:>cd fawkes

C:\fawkes>dir
Volume in drive C has no label.
Volume Serial Number is F85C-E6F1

Directory of C:\fawkes

04.08.2020 16:57

C:\fawkes>protection-v0.3.exe -d c:\fawkes
Traceback (most recent call last):
File "tensorflow\python\pywrap_tensorflow_internal.py", line 18, in swig_import_helper
File "imp.py", line 297, in find_module
ImportError: No module named '_pywrap_tensorflow_internal'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "tensorflow\python\pywrap_tensorflow.py", line 58, in
File "c:\users\jonwe\appdata\local\programs\python\python37\lib\site-packages\PyInstaller\loader\pyimod03_importers.py", line 493, in exec_module
File "tensorflow\python\pywrap_tensorflow_internal.py", line 28, in
File "tensorflow\python\pywrap_tensorflow_internal.py", line 20, in swig_import_helper
ImportError: DLL load failed with error code -1073741795

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "protection.py", line 13, in
File "c:\users\jonwe\appdata\local\programs\python\python37\lib\site-packages\PyInstaller\loader\pyimod03_importers.py", line 493, in exec_module
File "tensorflow_init_.py", line 28, in
File "c:\users\jonwe\appdata\local\programs\python\python37\lib\site-packages\PyInstaller\loader\pyimod03_importers.py", line 493, in exec_module
File "tensorflow\python_init_.py", line 49, in
File "c:\users\jonwe\appdata\local\programs\python\python37\lib\site-packages\PyInstaller\loader\pyimod03_importers.py", line 493, in exec_module
File "tensorflow\python\pywrap_tensorflow.py", line 74, in
ImportError: Traceback (most recent call last):
File "tensorflow\python\pywrap_tensorflow_internal.py", line 18, in swig_import_helper
File "imp.py", line 297, in find_module
ImportError: No module named '_pywrap_tensorflow_internal'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "tensorflow\python\pywrap_tensorflow.py", line 58, in
File "c:\users\jonwe\appdata\local\programs\python\python37\lib\site-packages\PyInstaller\loader\pyimod03_importers.py", line 493, in exec_module
File "tensorflow\python\pywrap_tensorflow_internal.py", line 28, in
File "tensorflow\python\pywrap_tensorflow_internal.py", line 20, in swig_import_helper
ImportError: DLL load failed with error code -1073741795

Failed to load the native TensorFlow runtime.

See https://www.tensorflow.org/install/errors

for some common reasons and solutions. Include the entire stack trace above this error message when asking for help.
[5928] Failed to execute script protection

C:\fawkes>

Thank you!

Hello, i have trouble with install this packet on linux and windows systems.

ERROR: Could not find a version that satisfies the requirement tensorflow<=1.15.0,>=1.12.0 (from fawkes) (from versions: 2.2.0rc1, 2.2.0rc2, 2.2.0rc3, 2.2.0rc4, 2.2.0, 2.3.0rc0, 2.3.0rc1, 2.3.0rc2, 2.3.0)                     
ERROR: No matching distribution found for tensorflow<=1.15.0,>=1.12.0 (from fawkes)  

What i need to do for fix this problem ?

I selected 1072 pictures each one just 200kb just to find the program crashed "An Error acoured. This program has to be closed" under Win10 after i came back from work :-(

Followed the process outlined in https://github.com/Shawn-Shan/fawkes/blob/master/fawkes/README.md and attempted to cloak 2x *.jpg and 1x *.png image. In all instances, I received the following 2 error lines: "EOFError: Ran out of input
[12264] Failed to execute script protection". This was attempted on Windows 10 Version 2004.

A screenshot of my Powershell session is located below. Any assistance would be appreciated... I would really like to get this facial recognition obfuscation program working if possible!

Unfortunately PypI does not feature any tensorflow version > 2.2.0

Any chances to have fawkes running with the tensorflow version?

in README.md:

Copyright

This code is intended only for personal privacy protection or academic research.
We are currently exploring the filing of a provisional patent on the Fawkes algorithm.

The expression personal privacy protection lead to ambiguity. Only for personal use or only aimed at personal privacy?

In context that you mentioned patent, it sounds like you're stressing only for personal use.

However, the BSD 3-Clause "New" or "Revised" License you released on inclueds high-level permission to commercial use.

Is it a contradiction?

Dear authors，
We have also done a similar work that developing a privacy-preserving solution, called Adversarial Privacy-preserving Filter (APF), to protect the online shared face images from being maliciously used. We propose the end-cloud collaborated adversarial attack solution to satisfy the absolute privacy-preserving. This work has been accepted by ACM Multimedia 2020, which is available at https://arxiv.org/abs/2007.12861. Welcome to discuss for any questions and future works.

Regards

Hello,

I noticed that argparse is needed as dependency.
As of Python >= 2.7 and >= 3.2, the argparse module is maintained within the Python standard library.
Which fawkes support python >= 3.5, so I think you can remove it.

https://pypi.org/project/argparse/

Thanks.

For me default settings worked really bad making me essentially look like an alien on a resulting photo. However, --help suggests there is --mode parameter. I think, if I change the mode it might work well for me, but I could not find description of modes anywhere, so I don't know, what values it can accept. There is also no description of any other parameters neither on your website nor in the readme. Most of the parameters described in --help output also have no annotations, so I have no idea what they do. Please fix it.

Initially I ran setup.py with the tensorflow-gpu package commented out.

When trying to run fawkes with the tensorflow package installed I'd get this output:

Ran: fawkes -d .\img --mode custom --format png --lr 0.0001 --max-step 1000 -g 0

no tensorflow-gpu installed

2020-07-24 13:36:34.490847: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_100.dll
2020-07-24 13:36:46.546924: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2020-07-24 13:36:46.549821: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2020-07-24 13:36:46.581144: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: GeForce RTX 2080 SUPER major: 7 minor: 5 memoryClockRate(GHz): 1.845
pciBusID: 0000:08:00.0
2020-07-24 13:36:46.581246: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_100.dll
2020-07-24 13:36:46.583749: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_100.dll
2020-07-24 13:36:46.618641: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_100.dll
2020-07-24 13:36:46.629692: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_100.dll
2020-07-24 13:36:46.633331: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_100.dll
2020-07-24 13:36:46.668471: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_100.dll
2020-07-24 13:36:46.681224: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2020-07-24 13:36:46.681384: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2020-07-24 13:36:47.218796: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-07-24 13:36:47.218883: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165]      0
2020-07-24 13:36:47.218986: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0:   N
2020-07-24 13:36:47.219192: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/device:GPU:0 with 6679 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2080 SUPER, pci bus id: 0000:08:00.0, compute capability: 7.5)
2020-07-24 13:36:47.221479: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: GeForce RTX 2080 SUPER major: 7 minor: 5 memoryClockRate(GHz): 1.845
pciBusID: 0000:08:00.0
2020-07-24 13:36:47.221551: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_100.dll
2020-07-24 13:36:47.221591: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_100.dll
2020-07-24 13:36:47.221629: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_100.dll
2020-07-24 13:36:47.221666: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_100.dll
2020-07-24 13:36:47.221703: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_100.dll
2020-07-24 13:36:47.221740: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_100.dll
2020-07-24 13:36:47.221778: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2020-07-24 13:36:47.221844: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2020-07-24 13:36:47.221910: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-07-24 13:36:47.221948: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165]      0
2020-07-24 13:36:47.221977: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0:   N
2020-07-24 13:36:47.222070: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6679 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2080 SUPER, pci bus id: 0000:08:00.0, compute capability: 7.5)
Identify 1 files in the directory
Identify 1 images in the directory
2020-07-24 13:36:58.168878: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2020-07-24 13:36:59.043381: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_ALLOC_FAILED
2020-07-24 13:36:59.046724: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_ALLOC_FAILED
Traceback (most recent call last):
  File "F:\Downloads\fawkes\.aienv\lib\site-packages\tensorflow-1.15.0-py3.7-win-amd64.egg\tensorflow_core\python\client\session.py", line 1365, in _do_call
    return fn(*args)
  File "F:\Downloads\fawkes\.aienv\lib\site-packages\tensorflow-1.15.0-py3.7-win-amd64.egg\tensorflow_core\python\client\session.py", line 1350, in _run_fn
    target_list, run_metadata)
  File "F:\Downloads\fawkes\.aienv\lib\site-packages\tensorflow-1.15.0-py3.7-win-amd64.egg\tensorflow_core\python\client\session.py", line 1443, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.UnknownError: 2 root error(s) found.
  (0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
         [[{{node pnet/conv1/Conv2D}}]]
         [[pnet/prob1/_3729]]
  (1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
         [[{{node pnet/conv1/Conv2D}}]]
0 successful operations.
0 derived errors ignored.

Now when I run it with tensorflow-gpu installed and tensorflow uninstalled first it doesn't even load my GPU or try to load cudNN. It just says it couldn't initalize cudNN and fails to find the convolution algorithm.

OS: Artix Linux x86_64
Shell: zsh and bash (tried on both)

./protection -d ~/Pictures/hawkes/
zsh: illegal hardware instruction  ./protection -d ~/Pictures/hawkes

Just a small Comment: On osX, you can run an app from an unidentified developer by right-clicking and selecting open. Then you get a dialogue that asks you if you really want to do that. Opposed to just double clicking, where it fails without asking.

After using high mode , the generated photo can still be recognized by Megvii model
https://github.com/MegEngine/MegEngine

Hello,
I could not install fawkes on openSUSE Tumbleweed with pip.
tensorflow<=1.14.0,>=1.13.1 is not satisfied. It look like the latest version is now 1.15.x.
Does tensorflow have to be strictly between 1.14.0 and 1.13.1?
Thanks

kev@linux:~> sudo pip install fawkes
[sudo] password for root: 
Requirement already satisfied: fawkes in /usr/lib/python3.8/site-packages (0.0.6)
Collecting argparse
  Downloading argparse-1.4.0-py2.py3-none-any.whl (23 kB)
Collecting keras==2.2.5
  Downloading Keras-2.2.5-py2.py3-none-any.whl (336 kB)
     |████████████████████████████████| 336 kB 1.1 MB/s 
Collecting numpy==1.16.4
  Downloading numpy-1.16.4.zip (5.1 MB)
     |████████████████████████████████| 5.1 MB 5.2 MB/s 
Collecting opencv-python>=4.2.0.34
  Downloading opencv_python-4.3.0.36-cp38-cp38-manylinux2014_x86_64.whl (43.7 MB)
     |████████████████████████████████| 43.7 MB 4.5 MB/s 
Requirement already satisfied: pillow>=7.0.0 in /usr/lib64/python3.8/site-packages (from fawkes) (7.1.2)
Requirement already satisfied: scikit-image in /usr/lib64/python3.8/site-packages (from fawkes) (0.16.2)
Collecting sklearn
  Downloading sklearn-0.0.tar.gz (1.1 kB)
ERROR: Could not find a version that satisfies the requirement tensorflow<=1.14.0,>=1.13.1 (from fawkes) (from versions: 2.2.0rc1, 2.2.0rc2, 2.2.0rc3, 2.2.0rc4, 2.2.0, 2.3.0rc0, 2.3.0rc1)
ERROR: No matching distribution found for tensorflow<=1.14.0,>=1.13.1 (from fawkes)

Based on Google and Azure score output images are 95-97% equal to the original. Which means that most of face recognition services will consider them as the same one.
So what am i doing or understanding wrong?

I hope the irony is not lost on you that a privacy tool is served over http and not https. Please provide compiled versions over https. :)

ERROR: Could not find a version that satisfies the requirement tensorflow<=1.15.0,>=1.12.0 (from fawkes) (from versions: 2.2.0rc1, 2.2.0rc2, 2.2.0rc3, 2.2.0rc4, 2.2.0, 2.3.0rc0, 2.3.0rc1, 2.3.0rc2, 2.3.0)
ERROR: No matching distribution found for tensorflow<=1.15.0,>=1.12.0 (from fawkes)

I get this error when I run sudo pip install fawkes, even after I successfully run sudo pip install tensorflow.

dfa a fad

I'm curious whether the cloaking that this program performs is random or algorithmic?

Let's say, for instance, someone uses Fawkes to cloak a facial image. If that same original facial image were to be cloaked by Fawkes in a separate instance, would the output be a completely unique cloaked image? Or would it be the same as the first cloaked image?