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View Code? Open in Web Editor NEW[NeurIPS 2023] Official PyTorch implementation for the paper "CRoSS: Diffusion Model Makes Controllable, Robust and Secure Image Steganography"
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whuhxb xuanyuzhang21 guangkechen moqingxinai witherc anhuipl2010 zcx-language fyy-debug ma893460966 rucvmacross's Issues
作者您好，我想参考一下你安全性分析的代码
作者您好，我现在在读研一，我不太清楚结果分析的流程，我想看一下您用于分析结果的代码，谢谢。
About the Stego260
I have read your paper and I am curious about the dataset Stego260.I want to use your model using different methods to hide two images,but I don't see any access to the dataset.Could you please offer it?Thanks a lot.
Stego image question
`
latent_noise = ode.invert(prompt_1, image_gt_latent, is_forward=True)
image_hide_latent = ode.invert(prompt_2, latent_noise, is_forward=False)
# save container image
image_hide = ode.latent2image(image_hide_latent)
cv2.imwrite("{:s}/hide.png".format(args.save_path), cv2.cvtColor(image_hide, cv2.COLOR_RGB2BGR))
# reveal process
latent_noise = ode.invert(rev_prompt_2, image_hide_latent, is_forward=True)
image_reverse_latent = ode.invert(rev_prompt_1, latent_noise, is_forward=False)
image_reverse = ode.latent2image(image_reverse_latent)`
`
In this piece of code, it seems like you are directly using the latent vector (1*4*64*64) that has not gone through vae.decoder for secret message extraction. In the concept of image steganography, we should use the image generated after vae.decoder (e.g. 1*3*512*512) as the secret message container.
As in the following code:
`
latent_noise = ode.invert(prompt_1, image_gt_latent, is_forward=True)
image_hide_latent = ode.invert(prompt_2, latent_noise, is_forward=False)
# save container image
image_hide = ode.latent2image(image_hide_latent)
cv2.imwrite("{:s}/hide.png".format(args.save_path), cv2.cvtColor(image_hide, cv2.COLOR_RGB2BGR))
hide_latent_for_reveal = ode.image2latent(image_hide)
# reveal process
latent_noise = ode.invert(rev_prompt_2, hide_latent_for_reveal, is_forward=True)
image_reverse_latent = ode.invert(rev_prompt_1, latent_noise, is_forward=False)
image_reverse = ode.latent2image(image_reverse_latent)`
`
关于stego260
作者你好，我是一名在读研究生，希望能借用你的数据集进行一些实验。能否公开你的数据集stego260 ？感激不尽
ROC curve problem for steganographic analysis
I would like to ask how to define the values of positive and negative samples when using StegExpose for analysis in this paper, because I used the generated pictures to test "Above stego threshold? "Is the value of false.
您好，我打算在我的小论文中引用您的论文
您好，我是来自北京邮电大学的一名博士生，看来您的论文，我非常受启发，感觉您提出了一个隐写术的新方向，原始的隐写术要求嵌入信息要小于载体，您这种无载体的隐写术可以使得嵌入信息与容器图像大小相同。
我有个问题，您给的requirements.txt中的库我都下不到，我试了好几个镜像都不行，请您给我一个镜像或下载地址好吗，感激不尽。
作者您好，代码中的“MY_TOKEN”字段应该填写什么内容？
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