This repository contains a pytorch implementation of an algorithm for artistic style transfer. The algorithm can be used to mix the content of an image with the style of another image. For example, here is a photograph of a door arch rendered in the style of a stained glass painting.
The model uses the method described in [Perceptual Losses for Real-Time Style Transfer and Super-Resolution](https://arxiv.org/abs/1603.08155) along with [Instance Normalization](https://arxiv.org/pdf/1607.08022.pdf). The saved-models for examples shown in the README can be downloaded from [here](https://www.dropbox.com/s/lrvwfehqdcxoza8/saved_models.zip?dl=0).
2021-03-08 16:06:52
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CycleGAN本质上是两个镜像对称的GAN，构成了一个环形网络。只要理解了其一半即单向GAN就便于理解整个CycleGAN的网络了。这是一个CycleGAN相关的项目
2021-02-19 13:09:23
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这是基于Pytorch的图片风格迁移教程源码，对其进行了逐句对照解析以便于理解。 详情请搜索博文：【Pytorch代码】神经风格迁移Pytorch教程代码 逐句解析
2020-01-08 03:08:26
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基于VGG19的图像风格迁移，如果没有vgg-19文件 运行utils代码是会下载。 在styles文件夹中选择更改要迁移的图，包含了风格图片，内容图片替换成自己要进行操作的图片即可。是可以直接运行跑通的。有疑问的话可以留言询问。
2020-01-03 11:31:45
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