Following the killing of George Floyd by police on May 25th, 2020, people of color across the US have been risking their lives in protests against police brutality and deeply racist system.

Police have been known to threaten, assault, and even kill protesters, identifying them using information gathered from social media as well as facial recognition algorithms.

The highly questionable ethics of releasing a tool that could be used to subvert anonymization under any circumstance aside, releasing this right now is not only incredibly dangerous, but can and will get people killed.

I ask you to permanently delete this repository, and everything associated with it. #BlackLivesMatter

In the current climate of mass law enforcement and government surveillance plus mass protest in the United States, I find the release of this technology disturbing.

I urge you to read the core 4 principles of the Algorithmic Justice League:

• Affirmative consent: Everyone should have a real choice in how and whether they interact with AI systems.
• Meaningful transparency: It is of vital public interest that people are able to understand the processes of creating and deploying AI in a meaningful way, and that we have full understanding of what AI can and cannot do.
• Continuous oversight and accountability: Politicians and policymakers need to create robust mechanisms that protect people from the harms of AI and related systems both by continuously monitoring and limiting the worst abuses and holding companies and other institutions accountable when harms occur. Everyone, especially those who are most impacted, must have access to redress from AI harms. Moreover, institutions and decision makers that utilize AI technologies must be subject to accountability that goes beyond self-regulation.
• Actionable critique: We aim to end harmful practices in AI, rather than name and shame. We do this by conducting research and translating what we’ve learned into principles, best practices and recommendations that we use as the basis for our advocacy, education and awareness-building efforts. We are focused on shifting industry practices among those creating and commercializing today’s systems.

How does this work interact with those principles? We can see what this technology does, but what is its intended use? What are the worst-case scenarios for the use of this openly-available technology around the world? How will further technology built on top of this work be used?

PULSE does not contain a publicly available license to determine what type of use is acceptable or not. I urge you to consider licensing this derivative work under stipulations that require any end users to Do No Harm, like the Hippocratic License.

(In case there is any ambiguity, I am speaking as an individual in the technology industry, not on behalf of or with any relation to my employer.)

I'm not very familiar with Python, so sorry for my ignorance here, and inability to explain what's probably going wrong. Running the Google Colab notebook without changing any settings causes the following error to appear...

Upload widget is only available when the cell has been executed in the current browser session. Please rerun this cell to enable.

---------------------------------------------------------------------------

MessageError                              Traceback (most recent call last)

<ipython-input-1-5483e66a8121> in <module>()
     46   get_ipython().system('rm -rf /content/pulse/input/face.png')
     47   clear_output()
---> 48   uploaded = files.upload()
     49   for fn in uploaded.keys():
     50     print('User uploaded file "{name}" with length {length} bytes'.format(

2 frames

/usr/local/lib/python3.6/dist-packages/google/colab/files.py in upload()
     62   result = _output.eval_js(
     63       'google.colab._files._uploadFiles("{input_id}", "{output_id}")'.format(
---> 64           input_id=input_id, output_id=output_id))
     65   files = _collections.defaultdict(_six.binary_type)
     66   # Mapping from original filename to filename as saved locally.

/usr/local/lib/python3.6/dist-packages/google/colab/output/_js.py in eval_js(script, ignore_result)
     37   if ignore_result:
     38     return
---> 39   return _message.read_reply_from_input(request_id)
     40 
     41 

/usr/local/lib/python3.6/dist-packages/google/colab/_message.py in read_reply_from_input(message_id, timeout_sec)
    104         reply.get('colab_msg_id') == message_id):
    105       if 'error' in reply:
--> 106         raise MessageError(reply['error'])
    107       return reply.get('data', None)
    108 

MessageError: TypeError: google.colab._files is undefined

Thank you very much for the nice repository. I tried several pics, but I always get this error: ''' Estimated Runtime: 29s.

Loading Synthesis Network Optimizing BEST (100) | L2: 0.0053 | GEOCROSS: 3.1139 | TOTAL: 0.6826 | time: 57.3 | it/s: 1.75 | batchsize: 1 Could not find a face that downscales correctly within epsilon

[Errno 2] No such file or directory: '/content/pulse/runs/face.png' '''

Could you please point out a direction which I could work on to solve this problem?

How to use Face Depixelizer properly? The instructions tell me to click on the "Let's Rock!" button but every time I get the error:

MessageError                              Traceback (most recent call last)
<ipython-input-7-af0d780e3ec8> in <module>()
     46   get_ipython().system('rm -rf /content/pulse/input/face.png')
     47   clear_output()
---> 48   uploaded = files.upload()
     49   for fn in uploaded.keys():
     50     print('User uploaded file "{name}" with length {length} bytes'.format(

2 frames
/usr/local/lib/python3.6/dist-packages/google/colab/_message.py in read_reply_from_input(message_id, timeout_sec)
    104         reply.get('colab_msg_id') == message_id):
    105       if 'error' in reply:
--> 106         raise MessageError(reply['error'])
    107       return reply.get('data', None)
    108 

MessageError: TypeError: Cannot read property '_uploadFiles' of undefined

Why is the "Choose a file" button deactivated? Is it a problem regarding the daily limit?

i keep getting that message even if my uploaded is square - i get the message whether the photo is unretouched, or is pixelated via photoshop pixelate effect option. what should the input be - unretouched? or pixelated? i was also careful about fitting my head inside the outline but it keeps returning with above message

For three days now, I have not been able to get it to work on Colab. Every time, I upload an image, that succeeds, then it tries to download something from a Google Drive link and I get this output:

Estimated Runtime: 29s.

Loading Synthesis Network
Downloading https://drive.google.com/uc?id=1TCViX1YpQyRsklTVYEJwdbmK91vklCo8 ............ failed
Traceback (most recent call last):
  File "run.py", line 58, in <module>
    model = PULSE(cache_dir=kwargs["cache_dir"])
  File "/content/pulse/PULSE.py", line 23, in __init__
    with open_url("https://drive.google.com/uc?id=1TCViX1YpQyRsklTVYEJwdbmK91vklCo8", cache_dir=cache_dir, verbose=verbose) as f:
  File "/content/pulse/drive.py", line 66, in open_url
    raise IOError("Google Drive quota exceeded")
OSError: Google Drive quota exceeded
---------------------------------------------------------------------------
FileNotFoundError                         Traceback (most recent call last)
<ipython-input-1-af0d780e3ec8> in <module>()
     90 ax1.imshow(mpimg.imread('/content/pulse/input/face.png'))
     91 ax1.set_title('Original')
---> 92 ax2.imshow(mpimg.imread('/content/pulse/runs/face.png'))
     93 ax2.set_title('Result')
     94 plt.show()

3 frames
/usr/local/lib/python3.6/dist-packages/matplotlib/cbook/__init__.py in to_filehandle(fname, flag, return_opened, encoding)
    401             fh = bz2.BZ2File(fname, flag)
    402         else:
--> 403             fh = open(fname, flag, encoding=encoding)
    404         opened = True
    405     elif hasattr(fname, 'seek'):

FileNotFoundError: [Errno 2] No such file or directory: '/content/pulse/runs/face.png'

I would really love to try it out, but sadly I can't. Could you look into that please?

Instead of nuking this repo, I have proposed a change in the README stating that this software can be inaccurate as well.

I would extend this change into the repo and it should close #4, resolve #1, and hopefully keep the repo up because this code is really interesting and I would hate to see it removed.

When I upload this image (32x32 .png) using english or russian colab, I get the following error:

mario.png(image/png) - 2858 bytes, last modified: n/a - 100% done

Saving mario.png to mario.png
User uploaded file "mario.png" with length 2858 bytes

---------------------------------------------------------------------------

RuntimeError                              Traceback (most recent call last)

<ipython-input-1-50b27c8aa454> in <module>()
     64   imagesHR = []
     65   imagesHR.append(face)
---> 66   face = toPIL(D(toTensor(face).unsqueeze(0).cuda()).cpu().detach().clamp(0,1)[0])
     67   images.append(face)
     68 

1 frames

/content/pulse/bicubic.py in forward(self, x, nhwc, clip_round, byte_output)
     59         # downscaling performed by 1-d convolution
     60         x = F.pad(x, (0, 0, pad_top, pad_bottom), self.padding)
---> 61         x = F.conv2d(input=x, weight=filters1, stride=(stride, 1), groups=3)
     62         if clip_round:
     63             x = torch.clamp(torch.round(x), 0.0, 255.)

RuntimeError: Given groups=3, weight of size [3, 1, 4, 1], expected input[1, 4, 1027, 1024] to have 3 channels, but got 4 channels instead

Hello,

I am running the colab from my google drive after uploading synthesis.pt, mapping.pt and shape_predictor_68_face_landmarks.dat and changing the respective paths. The code is executing without error, but the faces produced do not seam to match others' results with the default settings and I think it has to do with the "Could not find a face that downscales correctly within epsilon" text the code is producing with the results.

Here is what I am getting vs. what I think should be the result based on https://twitter.com/tg_bomze/status/1274245778551328769/photo/1

Any help would be appreciated, and thank you for providing such great and fun code!

Proposal to include epsilon parameter in the notebook.

The following commit in pulse repository adds an epsilon cutoff (default 0.002): https://github.com/adamian98/pulse/commit/ece9211c6448d3bca6c1d8c106ecfbf2e8eaed0f

Consequently, this notebook might print the following error, with no way to modify epsilon. "Could not find a face that downscales correctly within epsilon"

This should also address issue https://github.com/tg-bomze/Face-Depixelizer/issues/12

Thank you.

When i press "Let's rock!" i get this error MessageError Traceback (most recent call last) in () 46 get_ipython().system('rm -rf /content/pulse/input/face.png') 47 clear_output() ---> 48 uploaded = files.upload() 49 for fn in uploaded.keys(): 50 print('User uploaded file "{name}" with length {length} bytes'.format(

2 frames /usr/local/lib/python3.7/dist-packages/google/colab/_message.py in read_reply_from_input(message_id, timeout_sec) 104 reply.get('colab_msg_id') == message_id): 105 if 'error' in reply: --> 106 raise MessageError(reply['error']) 107 return reply.get('data', None) 108

MessageError: TypeError: Cannot read properties of undefined (reading '_uploadFiles')

I resetted the runtime and tried over and over again pressing the button. i always get this error. what should i do?

hi, can you please explain how can I train my own dataset on Face-depixelizer or on pulse

I am trying to test it on some of my own images which are very low resolution. I thought it may be a good idea to train pulse on my own dataset. Any suggestions are appreciated.

E.g., Could not find a face that downscales correctly within epsilon shouldn't show the side-by-side of the new input and the last successful output. It should just show no output.

Run 1:

Run 2:

Run 3:

On subsequent runs (only), immediately after uploading a picture, the script errors out as follows:

 ---------------------------------------------------------------------------
MessageError                              Traceback (most recent call last)
<ipython-input-5-5483e66a8121> in <module>()
     46   get_ipython().system('rm -rf /content/pulse/input/face.png')
     47   clear_output()
---> 48   uploaded = files.upload()
     49   for fn in uploaded.keys():
     50     print('User uploaded file "{name}" with length {length} bytes'.format(

2 frames
/usr/local/lib/python3.6/dist-packages/google/colab/_message.py in read_reply_from_input(message_id, timeout_sec)
    104         reply.get('colab_msg_id') == message_id):
    105       if 'error' in reply:
--> 106         raise MessageError(reply['error'])
    107       return reply.get('data', None)
    108 

MessageError: RangeError: Maximum call stack size exceeded.

I can't tell what the problem is but it could be a failure to clean up after a failed run.

NameError Traceback (most recent call last) in () 1 #@title ← Download result ----> 2 try: files.download('/content/pulse/runs/face.png') 3 except: raise Exception("No result image")

NameError: name 'files' is not defined

During handling of the above exception, another exception occurred:

Exception Traceback (most recent call last) in () 1 #@title ← Download result 2 try: files.download('/content/pulse/runs/face.png') ----> 3 except: raise Exception("No result image")

Exception: No result image