Comments (6)
你是不是指的单风格的增强,那就是我们的Basic Enhancer,我发现有好几个同学来问过,所以我把给它们的代码打包放在release里了。
It is our Basic Enhancer.
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这里面的slimEnhancer和Enhancer是对应的简化版本模型吗,我看git上也是这样的
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StarEnhancer和Basic Enhancer的代码我都提供了SlimEnhancer和Enhancer,SlimEnhancer是Enhancer的简化版本,两个空间坐标的曲线都去除了,以及让所有曲线的量化深度都相同了。
这主要是因为两个空间坐标对最后结果影响比较小,然后不同的量化深度的曲线的变换用PyTorch原生算子实现需要引入循环,会稍微降低点速度(CUDA代码的license限制太多,就没开源)。
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没有其他问题的话我先把issue关了,有其他问题reopen就行
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Related Issues (11)
- The results are not the same as the paper
- About pretrain model HOT 1
- One question about the code under the setting of sigle-style enhancement HOT 1
- How can I use style encoder to train classification on my dataset?
- Questions about dataset preparation HOT 4
- Is it possible to use a network such as VGG19 for the style encoder? HOT 4
- Is it feasible to use GAN for unpaired training? HOT 4
- Dataset processing HOT 2
- Multi-style, unpaired setting HOT 4
- How to test with my own style HOT 1
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