How to find a real Deepnude Source Code?

Here are 9 public repositories on Github matching this topic:

yuanxiaosc / DeepNude-an-Image-to-Image-technology

This repository contains the pix2pixHD algorithms(proposed by NVIDIA) ofΒ DeepNude, and more importantly, the general image generation theory and practice behind DeepNude.


zhengyima / DeepNude_NoWatermark_withModel


dreamnettech / dreamtime


dreamnettech / dreampower


Yuagilvy / DeepNudeCLI


redshoga / deepnude4video


Sergeydigl3 / pepe-nude-colab


ieee820 / DeepNude-an-Image-to-Image-technology


2anchao / deepnude_test

πŸ”ž DeepNude Algorithm

DeepNude is a pornographic software that is forbidden by minors. If you are not interested in DeepNude itself, you can skip this section and see the general Image-to-Image theory and practice in the following chapters.

DeepNude_software_itself content:

  1. Official DeepNude Algorithm(Based on Pytorch)
  2. DeepNude software usage process and evaluation of advantages and disadvantages.

πŸ‘ NSFW

Recognition and conversion of five types of images [porn, hentai, sexy, natural, drawings]. Correct application of image-to-image technology.

NSFW (Not Safe/Suitable For Work) is a large-scale image dataset containing five categories of images [porn, hentai, sexy, natural, drawings]. Here, CycleGAN is used to convert different types of images, such as porn->natural.

  1. Click to try pornographic image detection Demo
  2. Click Start NSFW Research

Image Generation Theoretical Research

This section describes DeepNude-related AI/Deep Learning theory (especially computer vision) research. If you like to read the paper and use the latest papers, enjoy it.

  1. Click here to systematically understand GAN
  2. Click here to systematically image-to-image-papers

1. Pix2Pix

Result

How to find a real Deepnude Source Code?

Image-to-Image Translation with Conditional Adversarial Networks is a general solution for the use of conditional confrontation networks as an image-to-image conversion problem proposed by the University of Berkeley.View more paper studies (Click the black arrow on the left to expand)


Image Generation Practice Research

These models are based on the latest implementation of TensorFlow2.

This section explains DeepNude-related AI/Deep Learning (especially computer vision) code practices, and if you like to experiment, enjoy them.

1. Pix2Pix

Use the Pix2Pix model (Conditional Adversarial Networks) to implement black and white stick figures to color graphics, flat houses to stereoscopic houses and aerial maps to maps.

Click Start Experience 1

2. Pix2PixHD

Under development… First you can use the official implementation

3. CycleGAN

The CycleGAN neural network model is used to realize the four functions of photo style conversion, photo effect enhancement, landscape season change, and object conversion.

Click Start Experience 3

4. DCGAN

DCGAN is used to achieve random number to image generation tasks, such as face generation.

Click Start Experience 4

5. Variational Autoencoder (VAE)

VAE is used to achieve random number to image generation tasks, such as face generation.

Click Start Experience 5

6. Neural style transfer

Use VGG19 to achieve image style migration effects, such as photo changes to oil paintings and comics.

Click Start Experience 6

………………………………………………………………..

If you are a user of PaddlePaddle, you can refer to the paddlepaddle version of the above model image generation model library paddegan.

https://www.vice.com/en/article/8xzjpk/github-removed-open-source-versions-of-deepnude-app-deepfakes

Something to consider:

From Wikipedia: β€œX-Ray Specs are an American novelty item, purported to allow the user to see through or into solid objects. In reality the glasses merely create an optical illusion; no X-rays are involved. The current paper version is sold under the name “X-Ray Spex”; a similar product is sold under the name “X-Ray Gogs”.”

β€œX-Ray Specs consist of an outsized pair of glasses with plastic frames and white cardboard “lenses” printed with concentric red circles, and emblazoned with the legend “X-RAY VISION”.

β€œThe “lenses” consist of two layers of cardboard with a small hole about 6 millimetres (0.24 in) in diameter punched through both layers. The user views objects through the holes. A feather is embedded between the layers of each lens. The vanes of the feathers are so close together that light is diffracted, causing the user to receive two slightly offset images. For instance, if viewing a pencil, one would see two offset images of the pencil. Where the images overlap, a darker image is obtained, supposedly giving the illusion that one is seeing the graphite embedded within the body of the pencil. As may be imagined, the illusion is not particularly convincing.

β€œX-Ray Specs were long advertised with the slogan “See the bones in your hand, see through clothes!” Some versions of the advertisement featured an illustration of a young man using the X-Ray Specs to examine the bones in his hand while a voluptuous woman stood in the background, as though awaiting her turn to be “X-rayed”.

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