Can you please provide a script to infer disparity maps on unseen data?

[MartinHahner]

To check how well your method/models can generalize,
I tried using ./scripts/kitti15_save.sh to infer disparity maps on new and previously unseen data,
but unfortunately save_disp.py is too dependant on the KITTI data structure (e.g. via --testlist)
and I also do not know what the "third column" in ./filenames/*.txt is used for,
otherwise, I could maybe hack a script myself.

E.g. from ./filenames/kitti15_train.txt:
training/image_2/000000_10.png training/image_3/000000_10.png training/disp_occ_0/000000_10.png
left right ???

Having something like this would be great:

./scripts/infer.sh --left $PATH_TO_LEFT_IMAGES_FOLDER \
                   --right $PATH_TO_RIGHT_IMAGES_FOLDER \
                   --checkpoint ./checkpoints/kitti2015.ckpt \
                   --output $PATH_TO_DISPARITY_OUTPUT_FOLDER

(Assuming the corresponding file names within $PATH_TO_LEFT_IMAGES_FOLDER and $PATH_TO_RIGHT_IMAGES_FOLDER are the same.)