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感谢您的工作，让我受益良多！
在原文中的KIC模块，将处理后的特征F波浪和余弦相似度的系数相乘。
但是在wanghu178/KUNet/tree/main/codes/models中，
KIC模块的实现：
def forward(self,x,guidance):
denos_x = self.denosing(x)
tmo_x_hat = self.tmo(denos_x)
guidance_map = self.cos_sim(tmo_x_hat,guidance).unsqueeze(dim=1)
out =self.refin(guidance_map*x)
return out

可见out =self.refin(guidance_map*x)，余弦相似度直接和输入的特征x相乘，而不是特征F波浪。请问这是一个小小的miss嘛？感谢你的回复！

Thanks for your work, and your reply for the last issue.
I have some questions about training dataset and geting the .hdr image.
Could I train it on 32-bit HDR image? I trained it on dataset "HDR-Real" and "HDR_Synth."
And could I just using cv2.imwrite('hdr_img_path.hdr', sr_img) to get the HDR image? It seems there are some problem when I using this function.
How can I get the .hdr image when I using this work?

Thank you~

I change network_G which_model_G of train_KIB.yml to KIB_DM_F_1x1_mask, but got this error:

22-06-30 11:35:58.139 - INFO: Model [GenerationModel] is created.
22-06-30 11:35:58.139 - INFO: Start training from epoch: 0, iter: 0
Traceback (most recent call last):
  File "F:/code/KUNet-main/codes/train.py", line 171, in <module>
    model.optimize_parameters(current_step)
  File "F:\code\KUNet-main\codes\models\Generation_condition.py", line 111, in optimize_parameters
    KIB1_loss = self.mask_pix(KIB1,self.real_H,mask)
AttributeError: 'GenerationModel' object has no attribute 'mask_pix'

How can I fix it, thanks!

Hello,

I would appreciate it if you could assist me in running your code with your pretrained model. I encountered a difficulty while trying to access the model from the provided Baidu link, as it requires a Baidu account, which I currently do not possess. Creating a Baidu account is not a straightforward process for me. Hence, I kindly request you to consider uploading the checkpoint files to Google Drive or including them directly in your GitHub repository.

Thank you for your understanding.