It arises an error (ImportError: cannot import name 'compare_ssim' from 'skimage.measure') while running "result2test.py". The error is because of the fact skimage.measure.compare_ssim has been removed in skimage 0.18.

To fix the issue, a line in the code in respective file needs to be changed from "from skimage.measure import compare_ssim, compare_psnr" to "from skimage.metrics import structural_similarity".

Hi，I have a question about dataset. For rain100H dataset，Why is there a large number of images simultaneously existing in the training set and the test set ? Is this training on the test set?

I'm using ”train.sh” just like the file I just downloaded. Can you provide some information on how to train the same test results with thedatasets you specify？？

Well, that's not an issue with the code or anything. It's more like a help. I'm new with this thing, I tried to use and run your code in Pycharm(fulfilling the requirements), but when I try to run train.py, I'm getting an error "ValueError: num_samples should be a positive integer value, but got num_samples=0". I need help regarding it, where I'm doing wrong? Thank you!

A bit more description: I tried to use the code as it is, and in models folder, I put the material downloaded from provided link "direct download: http://www.xujuefei.com/models_effderain.zip". Is there some wrong with the data path?

Traceback (most recent call last): File "./validation.py", line 8, in from skimage.measure import compare_ssim ImportError: cannot import name 'compare_ssim' from 'skimage.measure' (C:\Users\whu_c\anaconda3\envs\yolov5\lib\site-packages\skimage\measure_init_.py)

what's the problem

Thanks for your code. But I found test.py is empty. I have downloaded it several times, but it doesn't work. Shall we write test.py? Or there is something with my PC and net. THANK U A LOT.

Hello, thank you for releasing the code.

But according to the train.sh you provided, the accuracy of PSNR obtained by training the rain100H dataset is only about 23~24, and the SSIM is about 0.77. I don’t know what went wrong.

Can you give me some advice? Thanks again for your work

It arises an error (ImportError: cannot import name 'compare_ssim' from 'skimage.measure') while running "validation.py". The error is because of the fact skimage.measure.compare_ssim has been removed in skimage 0.18.

To fix the issue, a line in the code in respective file needs to be changed from "from skimage.measure import compare_ssim, compare_psnr" to "from skimage.metrics import structural_similarity".

https://github.com/tsingqguo/efficientderain/blob/465759da2428a4263eeee6ab464a0135fca2900c/utils.py#L26

torch.load(opt.load_name, map_location=torch.device('cpu'))

Dear friends, Thanks for your good work ! We have one question: Is it possible for one model to for all kinds of test set ？ For your source code, for different test set, we need load different model. Best regards,

colorful stain comes around in the birght side of the predicted picture

Firstly, really thank you for your code implementation and brilliant idea. I am using it for my project. However, I encountered some problems here. Any help is appreciated!!

As shown the picture below, left is input, middle is predicted, right is gt. The model mysteriously conjures up some bright color in some places especially the white area. Did it happened to you? How can I solve it? Or it's basically the inherent problem of the model? Even if I did some normalization to input images, it couldn't get any improvement.

            transform_list += [transforms.Normalize((0.3908, 0.3859, 0.3637), (0.2434, 0.2473, 0.2440))]

Here is the loss curve. The above issue almost happened from the beginning epoches. I let it run for almost 1000 epoches. Loss didn't change since 100th epoch. Why loss converges so quickly? Can the model learn from the stagnate loss? I don't understand. How many epoches did you run before? Is there any trick to train the model? Here is my model parameters.

python ./train.py ^
--baseroot "./datasets/video_collection_25/" ^
--load_name "" ^
--multi_gpu "false" ^
--save_path "./models/models_video_coll_25_04072000" ^
--sample_path "./samples_kuhn/models_video_coll_25_04072000" ^
--save_mode "epoch" ^
--save_by_epoch 10 ^
--save_by_iter 100000 ^
--lr_g 0.0002 ^
--b1 0.5 ^
--b2 0.999 ^
--weight_decay 0.0 ^
--train_batch_size 110 ^
--train_batch_size 16 ^
--epochs 2000 ^
--lr_decrease_epoch 500 ^
--num_workers 0 ^
--crop_size 128 ^
--no_gpu "false" ^
--rainaug "false" ^
--gpu_ids 0 ^
--no_flip

By the way, I added the visualizer module for your model using visdom. Would you like me to upload?