Comments (3)
If you think there is a bug, please provide steps to reproduce it and the logs showing such issues.
from adversarial-face-attack.
I follow the steps and run attack
./face_attack.py --data /path/to/lfw_mtcnnpy_160 \
--attack images/clean-JCJ.png \
--target Arnold_Schwarzenegger \
--output JCJ-to-Schwarzenegger.png
And I run this code to simply get the perturbation.
from PIL import Image
import numpy as np
np.set_printoptions(threshold=np.inf)
im = np.array(Image.open("/Adversarial-Face-Attack/images/clean-JCJ.png"),dtype='int16')
attack_im = np.array(Image.open("/Adversarial-Face-Attack/JCJ-to-Schwarzenegger.png"),dtype='int16')
diff = im - attack_im
print (diff)
The value of some pixels is larger than 16.
from adversarial-face-attack.
I'm able to reproduce the issue in this way. It turns out that the generated perturbation is within eps, but it is generated on top of a resized face, therefore within eps w.r.t that resized face, but when resized back, it may go out of eps w.r.t. the original image.
I'll add an extra clip operation in the end. A better fix would be to perform the initial resize operation in the graph so the attack can propagate through it.
from adversarial-face-attack.
Related Issues (7)
- ValueError: Cannot feed value of shape (42, 250, 250, 3) for Tensor 'images:0', which has shape '(?, 160, 160, 3)' HOT 1
- I have a question HOT 2
- Could you provide the requirements.txt of this project? HOT 1
- Could you add a LICENCE in this repo? HOT 1
- Could you explain where is the lfw and align package in face_attack.py? HOT 1
- How to understand the dist HOT 1
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from adversarial-face-attack.