(torch14) C:\Users\15479\Desktop\pytorch-zssr-master>python train.py --img lincoln.png Traceback (most recent call last): File "train.py", line 105, in img = PIL.Image.open(args.img) File "E:\anaconda\envs\torch14\lib\site-packages\PIL\Image.py", line 2891, in open fp = builtins.open(filename, "rb") FileNotFoundError: [Errno 2] No such file or directory: 'lincoln.png'

I'm a green hand.Please tell me What should be after --img？ How to set？ Please ，help me bro！！！

(base) C:\Users\Luke Chen\Desktop\pytorch-zssr-master>python train.py --crop 30 --num_batches 8 --img img.png
train.py:18: UserWarning: nn.init.kaiming_normal is now deprecated in favor of nn.init.kaiming_normal_.
  init.kaiming_normal(m.weight.data, a=0, mode='fan_in')
  0%|                                                                                            | 0/8 [00:00<?, ?it/s]
Traceback (most recent call last):
  File "train.py", line 118, in <module>
    train(model, img, args.factor, args.num_batches, args.lr, args.crop)
  File "train.py", line 46, in train
    cpu_loss = error.data.cpu().numpy()[0]
IndexError: too many indices for array

Hi, so I compared the code (overall skeletal structure) with the original repository that was written in TensorFlow and a lot of concepts like kernel implementation, hr-father, lr-sons etc.. weren't found in this code.

Can you help me understand if I have missed something?

I use the defalut parameters. lr = 1e--5 nums = 15000 in fact, I test in Set14，and get the results as: x2,psnr:29.75,ssim:0.88 however, the original txt is: x2,psnr:33.00,ssim:0.9108. I want to know ,did you test in Set14,and what's your results.

I ran everything with default settings just to test the code ( run train.py --img lincoln.png). I got the 2x enlarged image.

Then I used this 2x image as input to magnify it to 4x. During this run, all the 15000 epochs were completed and a new image file called 'low_res.png' was found in the folder. But after this, the program stopped without completion with the following message :

CUDA out of memory. Tried to allocate 788.00 MiB (GPU 0; 4.00 GiB total capacity; 2.38 GiB already allocated; 531.39 MiB free; 128.68 MiB cached)

Also, during the running of the program, I checked the task manager and it was always like CPU(near 100%), GPU(2%).

Can someone help me understand the issue and help me find a solution?

I was wondering if you had a chance to look into the kernel estimation part of the paper, as that is what really lets ZSSR be more useful than other SR methods (per the paper). If not, do you have any guidance for trying to implement it? In particular, how can image resizing with an arbitrary kernel be done?

I set "lincoln.png" in the example folder as input and run the code. It turns out that the result is hardly different from the input LR. I took a brief look at the code but nothing seems wrong. I wonder if you had the same problem.