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--no-crop adds some noise or issues to the bottom of the images. #5

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gateway opened this issue Jul 6, 2020 · 6 comments
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@gateway
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gateway commented Jul 6, 2020

w/o --nocrop

image

with --nocrop

image

Message when running this on Ubuntu 18.04

Test Data Num: 2
Load: BiFuse_Pretrained.pkl
Validation process:   0%|                                                                                            | 0/2 [00:00<?, ?it/s]/home/gateway/anaconda3/lib/python3.7/site-packages/torch/nn/functional.py:2693: UserWarning: Default grid_sample and affine_grid behavior will be changed to align_corners=False from 1.4.0. See the documentation of grid_sample for details.
  warnings.warn("Default grid_sample and affine_grid behavior will be changed "
Validation process: 100%|████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:03<00:00,  1.61s/it]
@dex1990
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dex1990 commented Jul 9, 2020

Hi, @gateway ,I had tested the Sample.jpg but got all black result.
Have you encountered this problem ?

image

@fuenwang
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fuenwang commented Jul 9, 2020

@gateway The reason why we need to crop the prediction is that the training data of Matterport3D has no depth ground truth on the top and bottom area. So the prediction will be noise in the two area.

@dex1990 Do you have other error message?

@gateway
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gateway commented Jul 9, 2020

Hmm.. so with equirectangular this will cause noise due to the lack of data to extract due to the nature of how equirectangular works? There has been a lot of talk in the 360 virtual tour market about using depth maps to create some unique points of view not easily obtained by a single 360 shot. See https://krpano.com/examples/?depthmap

Here is a shared google folder of 3 images I took for a tour https://drive.google.com/drive/folders/1bB5TooUagnQrVUYMBoWVrFiuas0WnHoT?usp=sharing and here is the tour showcasing my buddies art work these belong to. https://ibareitall.com/360/tonic-arts/ maybe this is not going to work but I have been researching the best way to create these depth maps and someone pointed me to your paper.

@dex1990
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dex1990 commented Jul 10, 2020

@gateway The reason why we need to crop the prediction is that the training data of Matterport3D has no depth ground truth on the top and bottom area. So the prediction will be noise in the two area.

@dex1990 Do you have other error message?

hi, @fuenwang ,i think there`s something wrong with my gpu card.
BTW, how could i get point cloud with depth map and rgb image?
thank you

@fuenwang
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@gateway Because the vertical FoV of depth sensors in Matterport camera cannot reach 180 degree, so the upper/lower area are invalid pixels. During training, we won't calculate the loss on these regions. So we can say this area is totally undefined for our model and eventually predicts noisy value. However, in virtual environment like PanoSUNCG, we can easily create a spherical depth sensor with vertical FoV as 180 degree so this problem won't happen in such case.

@dex1990 I have upload the point cloud visualization tool in tools/ folder, you can have a try.

@gateway
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gateway commented Jul 10, 2020

Thanks for your feedback, I'm just wondering if this is the right options for equirectangular images that can then be used as a depth map for 360 virtual tours. Cropping the top and bottom (removing the noise) may have some effect on this or make it look odd at the top (above the person and below the person).

Question: I'm not 100% sure how the script works and the math is above my head but if you created a virtual 360 camera and wrapped it in the equirectangular projection (a 360 view) couldn't the code estimate the tops and bottoms a bit more. I realize you have a trained matterport dataset but what about other datasets or datasets taken from simple 360 cameras in video such as the insta360 One r , One x or other..

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