Comments (2)
xinntao
commented on May 20, 2024
- 先训练Real-ESRNet是为了 获得一个gen更好的初始化模型给Real-ESRGAN。 这样能够稳定训练，也使得效果有一定的提升。这是较为普遍的做法
- 直接训练Real-ESRGAN也是可以的，训练更多时间，也可以达到类似效果。但考虑到稳定性和效果，大家一般都采用先pre-train 一个MSE/L1 loss训练的模型
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sunyclj
commented on May 20, 2024
@xinntao 请问两个阶段的训练iter/epoch分别设置多少呢？算力资源是怎样的？
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Related Issues (20)
- RealESRNet_x2plus HOT 1
- Real time io usage HOT 1
- Enhancement of Memory Management for Large-Scale Image Processing in Real-ESRGAN HOT 1
- how to run cog predict.py file HOT 1
- 如何修改判别器
- linux平台编译的可执行文件，缺少libvulkan.so文件
- Data size error reported during training
- ESRGAN Model training ( RRDB_ESRGAN_x4.pth) HOT 1
- 在RealESRNet基础上finetune RealESRGAN 随着迭代次数的增加 出现了模式崩塌？ HOT 3
- Feature Request: -nr for AnimeVideo v4
- The OST dataset has many sub folders, have all the images been used for training?
- Has RealESRNet_x2plus.pth been released?
- invalid gpu device
- Can someone just make a simple EXE please? HOT 5
- Training on 1-channel images HOT 1
- Multiple issues occurred while initially loading the model using lru_cache.
- Error "compute_indices_weights_nearest" not implemented for 'Half' HOT 1
- face_enhancer taking way to long
- How to modify the discriminator HOT 2
- Question about Gauss blur in code ？
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