Comments (2)
same question
from animeganv2.
Great question. Just like when vgg is training on imagenet, the input image needs to be preprocessed, which includes subtracting the mean value of 3 channels. It is actually a standardized operation. It is assumed that the natural image defaults to a stable data distribution (that is, the statistics of each dimension of the data obey the same distribution). At this time, subtracting the statistical average of the data from each sample can be remove common parts to highlight individual differences. My original intention of using this operation is to remove the common tones in the animation dataset to reduce its interference with the color of the generated image. But in fact, this does not have a great effect. Since the discriminator judges the real color picture as true, the model will still learn the color style.
from animeganv2.
Related Issues (20)
- the generated pictures are some vague
- Where to download the paper of AnimeGANv2? HOT 1
- ImportError: cannot import name 'trace' HOT 2
- 使用项目里自带的模型转换完和原图差别很小?如何增强动漫效果呢? HOT 4
- 在nvidia A4000显卡上无法训练
- Exception has occurred: OperatorNotAllowedInGraphError HOT 5
- How to train face model? HOT 1
- 商业产品合作怎么联系你们 HOT 1
- Could you share how you get the improvements that you mentioned in the readme?
- NFT creator
- Failed to save model
- How to use 512 x 512 or higher-definition pictures for training
- 直接运行代码存在问题 HOT 1
- Requirement file HOT 6
- Why are all the pictures in the sample_dir file_b.jpg black HOT 2
- Is it possible to use AnimeGANv2 without GPU? Only with Intel CPU? HOT 1
- tensorflow-gpu 1.15.0 可以替换成相应的 cpu版本吗 HOT 1
- Anime the picture
- Can this be used without a GPU, on a Mac M1?
- Inference with pre-trained model and sample data is not working. HOT 4
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from animeganv2.