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Unofficial implementation of paper 'Face X-ray for More General Face Forgery Detection'. (updating...)

Python 100.00%

forgery-detection face-x-ray deep-face-recognition face-swap

face-x-ray's Introduction

Face-X-Ray

Unofficial implementation of paper 'Face X-ray for More General Face Forgery Detection'.

Key Requirements

numpy, opencv-python, scikit-image, dlib, tqdm, color_transfer.

Download dlib's 'shape_predictor_68_face_landmarks.dat' file. Provide its path when running faceBlending.py script.

How it works

1. input: source face image (I_B in paper, one image file or directory of images) and a directory of real face images as face database.
2. search face database for the one whose landmarks are close to source face image.
3. apply convex hull, random deform, piecewise affine transform, color correction and swap.
4. save result in ./dump

Demo Result

face-x-ray's People

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duoergun0729 lzythebset jieyoujun aideveloper-oz gleonato k111dk janeanjiechen jiniech baopingliu bigblank wasim004 wbiscuits rjvaishnavi dorucioclea

face-x-ray's Issues

How did you align two images?

Hi,

Thanks for sharing this !!

I have gone through your code, and I noticed that the background image and the face image seem not be to aligned. Do we need to make sure that the position of the faces in the two images lies in same position so that after blending the two images, the 'fake` face can be patched into the position where the original convex hull lies in. How did you cope with the scenario where the face in one image lies in the upper-left corner where the face in the other image lies in the down-right corner?

have a problem

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No Match: D:/Python/Dataset/Face X-Ray/FF++c23/data/test/0\10683.jpg
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No Match: D:/Python/Dataset/Face X-Ray/FF++c23/data/test/0\10689.jpg
No Match: D:/Python/Dataset/Face X-Ray/FF++c23/data/test/0\1069.jpg
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No Match: D:/Python/Dataset/Face X-Ray/FF++c23/data/test/0\10693.jpg
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No Match: D:/Python/Dataset/Face X-Ray/FF++c23/data/test/0\10697.jpg
No Match: D:/Python/Dataset/Face X-Ray/FF++c23/data/test/0\10698.jpg
No Match: D:/Python/Dataset/Face X-Ray/FF++c23/data/test/0\10699.jpg
No Match: D:/Python/Dataset/Face X-Ray/FF++c23/data/test/0\107.jpg
No Match: D:/Python/Dataset/Face X-Ray/FF++c23/data/test/0\1070.jpg
No Match: D:/Python/Dataset/Face X-Ray/FF++c23/data/test/0\10700.jpg
No Mat

source code

can you give me a complet source code,thank you very much
email [email protected]

the xray loss is nan

is there any body who want to reproduce the paper？

I have implemented all the parts and experiments, the strange thing is that the loss of this xray is infinity, I don’t know what the problem is

can we talk about this paper ?
I have done all the experiments, but if the loss add xray, it will be nan!

Have you achieved the similar results to the reported ones in the original paper?

I followed the paper for re-implementation. I got good results on DF and FS, but pool results on F2F and NT. Did you encounter a similar situation?

How to solve the problem of changing data sets,This happens in a different data set

(pytorch) D:\Python\Code\DF-DC\Face X-Ray\Face-X-Ray>python faceBlending.py
0it [02:34, ?it/s]
Traceback (most recent call last):
File "faceBlending.py", line 171, in
main()
File "faceBlending.py", line 74, in main
resultantFace = forge(srcFaceBgr, targetBgrT, blured) # forged face
File "faceBlending.py", line 111, in forge
return (mask * targetRgb + (1 - mask) * srcRgb).astype(np.uint8)
ValueError: operands could not be broadcast together with shapes (134,108,3) (128,106,3)

num of BI

Ｈi,

My question is how many blending images should generate and which kind of quality(raw c23 c40)were used?
Many thanks

training code?

how to train?
@neverUseThisName

Would you mind providing the database?

Hi, I run your code under LFW-a database of face photographs, but the result is not as good as yours. Would you mind providing the link of your face database? Thank you.

TypeError: stat: path should be string, bytes, os.PathLike or integer, not NoneType

Hello～Thanks for your work. But i encountered a problem
The error is as follows:
0it [00:00, ?it/s]Traceback (most recent call last):
File "/Users/for_am/Documents/a/FaceXRaymaster/faceBlending.py", line 174, in
main()
File "/Users/for_am/Documents/a/FaceXRaymaster/faceBlending.py", line 42, in main
for i, srcFace in enumerate(srcFaces):
File "/Users/for_am/opt/anaconda3/lib/python3.7/site-packages/tqdm/std.py", line 1081, in iter
for obj in iterable:
File "/Users/for_am/Documents/a/FaceXRaymaster/utils.py", line 31, in files
if os.path.isfile(path):
File "/Users/for_am/opt/anaconda3/lib/python3.7/genericpath.py", line 30, in isfile
st = os.stat(path)
TypeError: stat: path should be string, bytes, os.PathLike or integer, not NoneType

Hope you can help me! Thanks !☺️

About dataset generation

The original paper said blending data samples are composited using real images in FF++,but each video we extracted lots of frames, how do we select the sourceImages?each video select one image or something?I would appreciate it if you could solve my problems?Thank U

How to get color_transfer？

hello.
your work is pretty good，but i have some issues.
how do we prepare color_transfer that is needed.
Is it a self - writtern python file？
Thanks for reading.

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