jt827859032 / drrn-pytorch Goto Github PK

Hello! May I know the value of arguments that are used in the training command:
main.py [-h] [--batchSize BATCHSIZE] [--nEpochs NEPOCHS] [--lr LR]
[--step STEP] [--cuda] [--resume RESUME]
[--start-epoch START_EPOCH] [--clip CLIP] [--threads THREADS]
[--momentum MOMENTUM] [--weight-decay WEIGHT_DECAY]
[--pretrained PRETRAINED]

to get the PSNRs in the following table.

For example, the values of 'nEpochs', 'step', 'batchSize' and so on...
Many thanks in advance!

感谢大佬开源，我按照你的代码，没有改任何代码，跑50 epoch，发现在第50 epoch得到结果如下：
Processing Set5_mat/head_GT_x2.mat
Processing Set5_mat/butterfly_GT_x2.mat
Processing Set5_mat/baby_GT_x2.mat
Processing Set5_mat/woman_GT_x2.mat
Scale= 2
Dataset= Set5
PSNR_predicted= 35.98152927120101
PSNR_bicubic= 33.69039381292539
It takes average 5.726621294021607s for processing
Processing Set5_mat/woman_GT_x3.mat
Processing Set5_mat/bird_GT_x3.mat
Processing Set5_mat/baby_GT_x3.mat
Processing Set5_mat/head_GT_x3.mat
Processing Set5_mat/butterfly_GT_x3.mat
Scale= 3
Dataset= Set5
PSNR_predicted= 32.590871083509164
PSNR_bicubic= 30.407692343235453
It takes average 5.687644147872925s for processing
Processing Set5_mat/bird_GT_x4.mat
Processing Set5_mat/woman_GT_x4.mat
Processing Set5_mat/butterfly_GT_x4.mat
Processing Set5_mat/head_GT_x4.mat
Processing Set5_mat/baby_GT_x4.mat
Scale= 4
Dataset= Set5
PSNR_predicted= 30.483599758580993
PSNR_bicubic= 28.41454827257395
It takes average 5.374003458023071s for processing

相反的是我在第20 epoch得到了更好的结果，emmm，如果大佬有时间可以麻烦解答下么：
Processing Set5_mat/head_GT_x2.mat
Processing Set5_mat/butterfly_GT_x2.mat
Processing Set5_mat/baby_GT_x2.mat
Processing Set5_mat/woman_GT_x2.mat
Scale= 2
Dataset= Set5
PSNR_predicted= 36.17091792433612
PSNR_bicubic= 33.69039381292539
It takes average 5.751824855804443s for processing
Processing Set5_mat/woman_GT_x3.mat
Processing Set5_mat/bird_GT_x3.mat
Processing Set5_mat/baby_GT_x3.mat
Processing Set5_mat/head_GT_x3.mat
Processing Set5_mat/butterfly_GT_x3.mat
Scale= 3
Dataset= Set5
PSNR_predicted= 32.7447910082183
PSNR_bicubic= 30.407692343235453
It takes average 5.653450155258179s for processing
Processing Set5_mat/bird_GT_x4.mat
Processing Set5_mat/woman_GT_x4.mat
Processing Set5_mat/butterfly_GT_x4.mat
Processing Set5_mat/head_GT_x4.mat
Processing Set5_mat/baby_GT_x4.mat
Scale= 4
Dataset= Set5
PSNR_predicted= 30.44373425939143
PSNR_bicubic= 28.41454827257395
It takes average 5.370740699768066s for processing

Thank you for your wonderful work!
I want to train a model with my own dataset, but there are something wrong in the process.
The error is described as below:

===> Loading datasets
===> Building model
/home/luomeilu/anaconda3/envs/py2/lib/python2.7/site-packages/torch/nn/_reduction.py:49: UserWarning: size_average and reduce args will be deprecated, please use reduction='sum' instead.
warnings.warn(warning.format(ret))
===> Setting GPU
===> load model model/model_epoch_28.pth
/home/luomeilu/anaconda3/envs/py2/lib/python2.7/site-packages/torch/serialization.py:435: SourceChangeWarning: source code of class 'torch.nn.parallel.data_parallel.DataParallel' has changed. you can retrieve the original source code by accessing the object's source attribute or set torch.nn.Module.dump_patches = True and use the patch tool to revert the changes.
warnings.warn(msg, SourceChangeWarning)
/home/luomeilu/anaconda3/envs/py2/lib/python2.7/site-packages/torch/serialization.py:435: SourceChangeWarning: source code of class 'torch.nn.modules.conv.Conv2d' has changed. you can retrieve the original source code by accessing the object's source attribute or set torch.nn.Module.dump_patches = True and use the patch tool to revert the changes.
warnings.warn(msg, SourceChangeWarning)
/home/luomeilu/anaconda3/envs/py2/lib/python2.7/site-packages/torch/serialization.py:435: SourceChangeWarning: source code of class 'torch.nn.modules.activation.ReLU' has changed. you can retrieve the original source code by accessing the object's source attribute or set torch.nn.Module.dump_patches = True and use the patch tool to revert the changes.
warnings.warn(msg, SourceChangeWarning)
Traceback (most recent call last):
File "main.py", line 128, in
main()
File "main.py", line 69, in main
model.load_state_dict(weights['model'].state_dict())
File "/home/luomeilu/anaconda3/envs/py2/lib/python2.7/site-packages/torch/nn/modules/module.py", line 769, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for DRRN:
Missing key(s) in state_dict: "input.weight", "conv1.weight", "conv2.weight", "output.weight".
Unexpected key(s) in state_dict: "module.input.weight", "module.conv1.weight", "module.conv2.weight", "module.output.weight".

It seems that the parameters in model are miss? I can't understand the error, hoping you can give me some suggestions. Sincerely appreciate for your reply.

您好，
不好意思在这里问个题外话，请问您是不是也读过“A Deep-Reinforcement Learning Approach for Software-Defined Networking Routing Optimization”这篇文章吗？成果复现了吗？我训练的时候发现无论训练多少轮reward基本都不变，好像完全没训练一样，测试的时候结果也是。不知道是不是我出了什么问题，拜托指教！谢谢！

Hi, I have a problem with running this code because the multiprocessing works in a different way in windows. As I know it needs to add this sentence: if name == "main":
but I don't know where exactly I should add it in the code?!

Thanks a lot in advance.

Hello, after I finished the H5 file on MATLAB, I ran main.py for training, and the TypeError: h5py objects cannot be pickled error appeared. What could be the reason?

hello sir,i wan to ask you ,how much loss value you get when in no.8 epoach?
i always get approximately 180 loss value in no.3 epoach, is it normal?

Can you teach me how to debug? ? This is my graduation design. After a long time of debugging, there are still many bugs. Thank you

hi sir, i want to generate other test_dataset,so how can i Generate the test_dataset?
look forward your reply.

I want to be able to test with my own dataset. First, I need to convert the image to. Mat, such as a_ x2.mat ,a_ x4.mat
In the project, for example, How is the file baby_ GT_ x2.mat generated?

我希望能用自己的数据集测试，首先需要将图片转换为.mat,如a_x2.mat ,a_x4.mat
请问项目中例如baby_GT_x2.mat的文件是如何生成的？

There are files named as ***.mat what inculdes several images in different versions in demo.
But how can I evaluate on my own picture directly?

Hi, there,
I don't find the any code to evident that the parameter is shared. Maybe becanse I don't I understand how to use the "weight shared function" of pytorch? Can u help me?
thanks.

class DRRN(nn.Module):
	def __init__(self):
		super(DRRN, self).__init__()
		self.input = nn.Conv2d(in_channels=1, out_channels=128, kernel_size=3, stride=1, padding=1, bias=False)
		self.conv1 = nn.Conv2d(in_channels=128, out_channels=128, kernel_size=3, stride=1, padding=1, bias=False)
		self.conv2 = nn.Conv2d(in_channels=128, out_channels=128, kernel_size=3, stride=1, padding=1, bias=False)
		self.output = nn.Conv2d(in_channels=128, out_channels=1, kernel_size=3, stride=1, padding=1, bias=False)
		self.relu = nn.ReLU(inplace=True)

		# weights initialization
		for m in self.modules():
			if isinstance(m, nn.Conv2d):
				n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels
				m.weight.data.normal_(0, sqrt(2. / n))

	def forward(self, x):
		residual = x
		inputs = self.input(self.relu(x))
		out = inputs
		for _ in range(25):
			out = self.conv2(self.relu(self.conv1(self.relu(out))))
			out = torch.add(out, inputs)

		out = self.output(self.relu(out))
		out = torch.add(out, residual)
return out

I used it, got bad result. PSNR only 29
QAQ
Does BN layer is harmful for modle?

It doesn't have test.py

I run the code on Titan Xp GPU, and it approximately takes 22 hours to train an epoch. I'm not sure whether it is right or not

When i was testing the model in Set14, I found the GPU memory is overflow. How could you solve this problem？ And my GPU is 1080Ti.

Hi I wonder how you generate the Set_5.mat. It shows that the ground truth are using double type and are not round to integer, if I try to round to integer, it gives a different psnr. However I found if I directly using rgb2ycrcb it gives an integer value in matlab.

python eval.py --model model/model_epoch_28.pth or python eval.py --model model_epoch_28.pth
Where am I doing this wrong?