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?
GoodStudyDayUpUp opened this issue · 3 comments
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!
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.
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.