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Different depth #15

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ghost opened this issue Oct 20, 2019 · 7 comments
Open

Different depth #15

ghost opened this issue Oct 20, 2019 · 7 comments

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@ghost
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ghost commented Oct 20, 2019

Hi,
Thanks for your work. I had some problem with adapting my own dataset. I generated depth images from Carla simulator. The max value of carla depth images is 1km (so the images have values from 3 to 1000) but i have meaningful information until 70 meters (which is the max depth that i fixed).
I noticed that in the other datasets (kitti and nyu) the color of meaningless information is black instead in the images of my dataset it's white. So i changed the value to 0 in order to obtain something similar to the other dataset.
I tryu to show what I mean:

This is an image taken from Nyu dataset
sync_depth_00032

After the division by 1000, the result mask is
prova2

This is an image taken from my dataset
000001

If I apply the same code applied above I obtain this:
prova4

I think that it's not correct... So after i have changed the max value (1000) with 0 I obtain this:
prova3

is it correct?

Nevertheless, the network doesn't learn well... what should I do?
And what about the parameter focal? What is it?
Thanks

@MACILLAS
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Hi Guys,
I am also wondering how the focal length parameter works in your method... There is no mention of the focal length in your paper.

Thanks in Advance!

@cogaplex-bts
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cogaplex-bts commented Nov 1, 2019

Hello,
Thanks for your interest in our work.
In ground truth depthmaps, pixels without valid depth values should have 0 because we apply a mask operation in function build_losses().
Also, it is important to set args.max_depth properly to your dataset.
"focal" is the focal length of your camera which can be obtained by intrinsic calibration.

@ghost
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ghost commented Nov 1, 2019

Understood! Thank you :)
I set the right parameters but with batch size 4, when the training starts it crashes after few steps. If I set batch size equal to 2, it works. Do you know why? I mean, in my images there are no missing values so I set:
self.mask = self.depth_gt > 0

thanks

@cogaplex-bts
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Can you post the outputs when it crashes?

@ghost
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ghost commented Nov 7, 2019

Hi,
Now it seems to work, thanks. Is it normal that after 50 epochs the loss is stuck between 1-2?

image

Here the results:
image

@raozhongyu
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I meet the same question. I get the picture with carla and the depth is between (0,1000). I'd like to what's your max_depth.

@a-akram-98
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@animareversed do you managed to decrease the loss !?

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