训练完gopro(9帧),测试出现问题

[dupc2018]

测试的时候出现： 运行demo_8x.py 结果 out1 到out7 一致的问题，是训练的问题还是哪里出现问题了呢

[ltkong218]

确保你训练测试时embt都是对应正确的

[dupc2018]

训练测试的embt都是你原来的都没动，也就是数据集换了一下，其他的都没变，结果输出的7帧全部都是一样的，而且结果不怎么清晰，不知道原因出现在什么地方了

[ltkong218]

建议先使用train_gopro.py在GoPro数据集上训练并测试，不要用train_vimeo90k.py训练的模型在demo_8x.py脚本中进行测试。

[dupc2018]

直接使用train_gopro.py加载GoPro数据集是不是有点问题呢，我使用自己的数据集用train_gopro.py训练的，测试是用demo_8x.py脚本测试的，造成输出的都一样，连输出的图片文件大小都一样

[dupc2018]

是不是demo_8x.py的原因呢，写上False 加载模型的时候 model.load_state_dict(torch.load('/mnt/IFRNet-main/checkpoint/IFRNet_L/2022-06-26 02:14:46/IFRNet_L_latest.pth'),False)，但是如果不写False就报错 RuntimeError: Error(s) in loading state_dict for Model: Missing key(s) in state_dict: "encoder.pyramid1.0.0.weight", "encoder.pyramid1.0.0.bias", "encoder.pyramid1.0.1.weight", "encoder.pyramid1.1.0.weight", "encoder.pyramid1.1.0.bias", "encoder.pyramid1.1.1.weight", "encoder.pyramid2.0.0.weight", "encoder.pyramid2.0.0.bias", "encoder.pyramid2.0.1.weight", "encoder.pyramid2.1.0.weight", "encoder.pyramid2.1.0.bias", "encoder.pyramid2.1.1.weight", "encoder.pyramid3.0.0.weight", "encoder.pyramid3.0.0.bias", "encoder.pyramid3.0.1.weight", "encoder.pyramid3.1.0.weight", "encoder.pyramid3.1.0.bias", "encoder.pyramid3.1.1.weight", "encoder.pyramid4.0.0.weight", "encoder.pyramid4.0.0.bias", "encoder.pyramid4.0.1.weight", "encoder.pyramid4.1.0.weight"

[ltkong218]

You can search this error and get the solution, such as this issue discussion. Also, I have fixed this problem by changing ddp_model.state_dict() to ddp_model.module.state_dict() when saving model checkpoints.

[ltkong218]

For the problem that all output frames are the same, I suggest that you can read the paper and run provided code to understand the working principle of IFRNet, then you should know how to solve it.

[loveisp]

我也有这个问题。。啥情况？