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Segmentation fault (core dumped) #21

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hhhhhumengshun opened this issue Sep 7, 2019 · 4 comments
Closed

Segmentation fault (core dumped) #21

hhhhhumengshun opened this issue Sep 7, 2019 · 4 comments

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@hhhhhumengshun
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UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
"See the documentation of nn.Upsample for details.".format(mode))
Segmentation fault (core dumped)

Why?

@laomao0
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laomao0 commented Sep 20, 2019

Refer to : princeton-vl/CornerNet-Lite#7

In pytorch official tutorial, there are some clear explanation about this problem. https://pytorch.org/docs/stable/nn.html?highlight=upsample#torch.nn.Upsample
that is:
With align_corners = True, the linearly interpolating modes (linear, bilinear, bicubic, and trilinear) don’t proportionally align the output and input pixels, and thus the output values can depend on the input size. This was the default behavior for these modes up to version 0.3.1. Since then, the default behavior is align_corners = False. See below for concrete examples on how this affects the outputs.

@hhhhhumengshun
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How do you calculate ssim? My calculations are always smaller than yours

@laomao0
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laomao0 commented Dec 12, 2019

How do you calculate ssim? My calculations are always smaller than yours

python has different versions of ssim packages, e.g., skimage , etc.
matlab also has a function for computing ssim.
But matlab has higher ssim values than python.
typically,in one paper, we use one type of ssim function for evaluation, python or matlab.
In this paper, I think the author use matlab function: ssim() to compute this metric of RGB image.

@duymanhdoan
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UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details. "See the documentation of nn.Upsample for details.".format(mode)) Segmentation fault (core dumped)

Why?

I solved problem.
the problem is opencv version base on c++, so that is Segmentation fault
just typed the commandline to change version of opencv:
$ pip3 install opencv-python==4.0.1.24

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