Comments (4)
csdwren
commented on July 23, 2024
Rain100H、Rain100L和Rain1400的训练集都用了，但是因为Rain1400的训练集图像数量远多于其他两个，所以在构建h5文件的时候，stride是其他两个训练集的3倍。另外，PReNet多个epoch之后会在训练集上过拟合，1个epoch就停止训练的模型在真实图的扩展能力反而更好。PReNet1.pth和PReNet2.pth都是在这3个训练集的1个epoch的模型，区别只是recursive loss 和 final loss的区别，视觉效果应该基本没有区别。
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githubPsearth
commented on July 23, 2024
Rain100H、Rain100L和Rain1400的训练集都用了，但是因为Rain1400的训练集图像数量远多于其他两个，所以在构建h5文件的时候，stride是其他两个训练集的3倍。另外，PReNet多个epoch之后会在训练集上过拟合，1个epoch就停止训练的模型在真实图的扩展能力反而更好。PReNet1.pth和PReNet2.pth都是在这3个训练集的1个epoch的模型，区别只是recursive loss 和 final loss的区别，视觉效果应该基本没有区别。
作者您好，请问是将三个训练集混合之后，进行训练吗？
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csdwren
commented on July 23, 2024
对。只用rain100H训练集应该也可以，不过不能训练太充分，过拟合之后对真实图效果就很差了。
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SunshineJunFu
commented on July 23, 2024
Could you provide your deraining results on real-world rain images?
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Related Issues (20)
- Will the training set of Rain12600 be trained 100 epochs. Then tested on data set 1400? HOT 1
- rescan pretrained model HOT 2
- 关于递归监督 HOT 10
- 视频数据 HOT 1
- about Rain100L dataset HOT 5
- No logs/Rain12 .pth files HOT 3
- running time HOT 3
- how to train only LSTM models in stages 2, 3, 4, 5, 6, and 7 and test these 6 models？ HOT 3
- test datasets HOT 8
- About network struture HOT 1
- what is h5py version ? HOT 2
- About the train and test datasets HOT 1
- 关于RainTrainL数据集
- Different stage t output
- no file named train_target.h5 HOT 1
- RainTrainL dataset
- 您好，我想问一下Rain100L和Rain100H的分类标准是什么呢？
- Guānyú cèshì 4 / 5,000 Translation results About testing
- Training my own data set
- about epoch
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