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What changes did you make in the skimage code #8
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no, pred_depth is generated by _, depth = disp_to_depth(disp, self.opt.min_depth, self.opt.max_depth) |
OK,thanks!I'll try it.And I want to ask when I haven't make changes to the network,this problem didn't occur, and after I made changes,it occur,can it explain the problem is in the network? |
yes |
OK! |
I think maybe I found the reasons, it's the GPU memory problem,I can continue trainig on the previous model.And I want to ask is it normal that the accuracy decrease sharply for the first several epochs after I add network to the original network? |
i think yes, since it is normal that adding a not compatible network at first. |
Thanks!It becomes better now!😃
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Date: Wed, May 3, 2023 07:59 AM
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Cc: ***@***.******@***.***>;
Subject: Re: [SJTU-ViSYS/StructDepth] What changes did you make in the skimagecode (Issue #8)
i think yes, since it is normal that adding a not compatible network at first.
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no, i haven't. i think that maybe training structdepth needs a good depth network at first. That means, if you change the pretrained model, the depth network will be far worse than p2net. |
Yes,it needs the good network when using the norm loss and the planar loss,but if I don't use the two losses at first,and change the network,training a good network and use losses later,is that ok?I do this,and the problem occurred.Thanks for your reply!
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Subject:Re: [SJTU-ViSYS/StructDepth] What changes did you make in the skimagecode (Issue #8)
no, i haven't. i think that training structdepth needs a good depth network at first. If you change the pretrained model, the depth network is far worse than p2net.
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I didn't try it. I think it could work. |
Ok,thanks!I want to ask the p2net without its planar loss is the same as the struct depth without its Manhattan norm loss and planar loss?
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From: ***@***.***>
Date: Tue, May 9, 2023 18:11 PM
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Cc: ***@***.******@***.***>;
Subject: Re: [SJTU-ViSYS/StructDepth] What changes did you make in the skimagecode (Issue #8)
I didn't try it. I think it could work.
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Sorry for late, if "same" refer to accuracy, maybe not the same, since batch size, training set, pretrained model are different. If we don't take these into account, i think they are the same, both use same network structure and training method, both sparse rgb points. |
OK!Thanks!
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From: ***@***.***>
Date: Fri, May 12, 2023 16:25 PM
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Cc: ***@***.******@***.***>;
Subject: Re: [SJTU-ViSYS/StructDepth] What changes did you make in the skimagecode (Issue #8)
Sorry for late, if "same" refer to accuracy, maybe not the same, since batch size, training set, pretrained model are different. If we don't take these into account, i think they are the same, both use same network structure and training method, both sparse rgb points.
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Hello! I want to know how to get the gound truth image of the picture in the NYUv2 dataset, I'm not clear about it, could you give some idea? Thanks! |
This was downloaded a long time ago, it should be in the evaluation section of this website https://github.com/svip-lab/Indoor-SfMLearner |
Thanks! I'll see it. |
Thanks so much !!!!!! I can do it !!! Thanks !!!! 😊 |
happy to hear that |
Thanks for sharing code!
What changes did you make in the skimage code,can you release the changing code and explain why ?
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