Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

How to set the disparity range from two ends and how to use 'ad' and 'census' to generate disparity map directly without using the constructed network? #40

Open
GoodStudyDayUpUp opened this issue Aug 31, 2017 · 3 comments

Comments

@GoodStudyDayUpUp
Copy link

Hi everyone,

Anyone knows: How to set the disparity range from two ends? e.g. if we want to search from 100 to 300 as (100, 300) to find the suitable disparity for each pixel, how can we give this range to the code? Now, only 'disp_max' is used to make the searching disparity range as (0, disp_max)!

Also how to just use 'ad' and 'census' to generate disparity map directly without using the neural network, as the author did in his paper to compare the results of the constructed neural network with normal dense matching algorithms?

Any help is appreciated!

@xianshunw
Copy link

xianshunw commented Nov 27, 2017

I have the same question, I just want to use 'ad' to generate disparity. I try the command parameters like this ./main.lua kitti ad-a predict -net_fname net/net_kitti_fast_-a_train_all.t7 -left samples/input/kittiL.png -right samples/input/kittiR.png -disp_max 70 -sm_terminate cnn. But it seems not to work.

@GoodStudyDayUpUp
Copy link
Author

GoodStudyDayUpUp commented Dec 8, 2017 via email

@saeid-h
Copy link

saeid-h commented Oct 2, 2018

You may manipulate the source code which requires knowledge in cuda and torch or you may use the produced left/right volumes which is easier. Note that you have 3 outputs: left.bin, right.bin, and disp.bin. Two first files are cost volumes.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

3 participants