Comments (20)
有两种方法,一是手动对kernel(numpy类型)做归一化(使sum等于1再乘以255)后用cv2.imwrite保存。第二种是使用torchvision.utils对kernel(tensor类型)自动归一化并保存,如:
import torchvision.utils as tvutils
tvutils.save_image(kernel.data, 'kernel.png'), normalize=True)
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哈哈,祝好!
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确实,对于anisotropic kernel的话个人更倾向于follow kernelGAN里的设置(提出Div2kRK数据集的paper)
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from dcls-sr.
不是随机的,是从0.8到1.6均匀的选择8个kernel width,对所有的HR图像也都降质8次
from dcls-sr.
from dcls-sr.
差不多吧,你可以看这里:generate_mod_blur_LR_bic.py
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from dcls-sr.
from dcls-sr.
我裁剪用python写的代码,画图都是用的ppt哈
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from dcls-sr.
在overleaf上使用latex排版的哈,每个会议或期刊应该都会提供latex模版。
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from dcls-sr.
from dcls-sr.
hello,哪一个图呢?我这里看不到图。
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from dcls-sr.
还是没看到,你能在github的issue里发出来吗,邮件可能有点问题。
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Related Issues (20)
- 算法相关问题 HOT 2
- 关于3090用torch1.8跑rfft和irfft如何改动,我自己改动后不报错但现在loss一直是nan。 HOT 6
- 关于setting2的测试情况 HOT 5
- 关于噪声数据集的问题 HOT 6
- 关于模糊核的对比实验 HOT 11
- 关于预训练模型 HOT 2
- 关于模糊和采样的顺序问题 HOT 2
- 关于重构的公式内的傅里叶变换 HOT 4
- 关于对比方法的问题 HOT 4
- mismatch size of tensor HOT 1
- 关于feature的问题 HOT 4
- 关于Deep Constrained Least Squares理论问题 HOT 2
- 關於train時發生的錯誤問題 HOT 12
- 关于公式9的问题 HOT 6
- 训练效果越来越差 HOT 2
- 拉普拉斯算子p HOT 1
- 关于怎么给图片添加噪声的问题 HOT 2
- 为什么训练时的模糊核,X2 、X3、X4的方差设置为[0.2,2] [0.2,3] [0.2,4] HOT 2
- 去模糊特徵圖R的可視化圖 HOT 7
- 关于训练时psnr提高不多的问题 HOT 13
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