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Anime-Super-Resolution

动漫图片超分辨率——基于WDSR (2019-4-30)

实现动漫图片4倍的图片放大及超分辨率

  • utils.py -- 图像降采样与数据导入
  • model.py -- wdsr模型
  • optimizer.py -- 权重归一化Adam优化器
  • train.py -- 模型训练
  • predict.py -- 测试集预测
  • evaluate.py -- 在不同难度等级下测试网络表现

图像降采样

  • 使用NEAREST, BICUBIC, BILINEAR, HAMMING, LANCZOS插值方法将图像缩减4~12倍
  • 使用半径1~3的核进行高斯模糊

Demo(LR, SR)

难度测试

Easy（缩减倍率 4 ~ 6，模糊半径 1 ~ 1.5）

Normal（缩减倍率 6 ~ 8，模糊半径 1.5 ~ 2）

Hard（缩减倍率 8 ~ 10，模糊半径 2 ~ 2.5）

Lunatic（缩减倍率 10 ~ 12，模糊半径 2.5 ~ 3）

测试集表现

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