Open Emily-29 opened 5 months ago
Hello! I have also encountered this problem. Have you solved this problem?
The first stage follows the well-known ASM formulation: I(x) = J(x)t(x) + A (1 - t(x)). For the output in https://github.com/yuhuUSTC/DehazeDDPM/blob/5ee18db0646de74741714c83493a8d3f17c1a8c2/model/networkHelper.py#L676, out_J means the final output, stage1_output represents the output of the first stage, out_T denotes t(x), out_A denotes A, and out_I denotes I(x). Therefore, the training loss for the first stage is: loss = L1loss(HR, out_J) + L1loss(HR, stage1_output) + L1loss(LR, out_I).
Thank you very much for your reply! I would like to know why the result of my validation with your pre-trained model on the 55-hazy images on the NH-haze dataset is a noised image?This question is the same as the second question raised by the host, looking forward to your reply! Thank you very much! @yuhuUSTC
Hello! I have also encountered this problem. Have you solved this problem?
Not yet
Hello! I have also encountered this problem. Have you solved this problem?
I have also encountered this problem too. Have you solved this problem now?
Thank you very much for your reply! I would like to know why the result of my validation with your pre-trained model on the 55-hazy images on the NH-haze dataset is a noised image?This question is the same as the second question raised by the host, looking forward to your reply! Thank you very much! @yuhuUSTC
I have also encountered this problem too. Have you solved this problem now?
Thank you for making your code accessible on GitHub. It has been invaluable for my project on image dehazing. I have a query regarding the initial phase of your model's training process that I hope you can clarify: could you elaborate on how the training is conducted during the first stage?
Furthermore, I attempted to apply the models "NH_net_g_80000.pth" and "NH_I230000_E4600_gen.pth" to image "55.png" from the NH-HAZE dataset. The outcomes did not align with my expectations. I would greatly appreciate it if you could review the attached results and advise if there might be any steps I have overlooked or misimplemented.