I am able to generate disparity maps using the python vpi example code provided but only at lower resolutions. At higher resolutions the results are very noisy. I am using cuda as the backend.
The rectified input image size is (4112, 3008) [width, height], After scaling it down to (1280, 720) or (1920, 1080) I get good enough results. But as soon as I use higher resolutions like (2560, 1440), (3840, 2160) or the input image size the disparity map generated is very noisy. Could you please advise on how could I go about fixing this?
Hi @AastaLLL , I am using the latest version of VPI and JetPack. The parameter does not help since at low resolution the disparities that are visible quite well become very noisy at higher resolution. I have tried various values of the parameters but not have gotten expected results.
I am also unable to upload any attachments for some-reason, hence I have messaged you the drive folder link. Please have a look and let me know if you need anything else. Thanks
Hi, I messaged you again but I am also sharing the drive_link here. If possible, it would be great if you could share your email-id as I could share my code and more information over there. Setting the uniqueness value 0.7 or 0.8 I get a almost black image meaning the disparity map generated is all noisy. Please have a look at the disparity maps shared at different resolution. I think it this has to do with the window_size param which is fixed and too small for higher resolution images.
Hi @AastaLLL , just wanted to check in and ask if there are any updates you could share? Also please let me know if you need any more additional information
The parameters that might improve (reduce) noise are: P1, P2, and uniqueness.
If you set the same uniqueness on low and high resolutions, please change P1 and P2 as they relate to the pixel neighborhood.
Moreover, it also recommended to try uniqueness from -1 (disregarding) to 0.90~0.99.