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训练生成的噪声的数值是有正有负的,下面这个操作把负的值都变成0了,这种做法不会有问题吗?不应该是噪声加图像再clamp到0-255? self.perturb_tensor.mul(255).clamp_(0, 255).permute(0, 2, 3, 1).to('cpu').numpy()
The text was updated successfully, but these errors were encountered:
Yes, the noise should be added first. This could improve the protection performance. Keep me updated if you notice any difference in the results.
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训练生成噪声的代码似乎也有一点小问题,images[i] = images[i] + sample_noise,比如这里这个image加了sample_noise之后,是不是需要再clamp到(0,1)会更加合理一点,如果更改后效果有所提升我会告诉你的。
Good catch, thanks!
@Nonbiuld 老哥,我也注意到这个问题了,请问更改之后效果如何?
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训练生成的噪声的数值是有正有负的,下面这个操作把负的值都变成0了,这种做法不会有问题吗?不应该是噪声加图像再clamp到0-255?
self.perturb_tensor.mul(255).clamp_(0, 255).permute(0, 2, 3, 1).to('cpu').numpy()
The text was updated successfully, but these errors were encountered: