Question about how to generate superpixels of raw images #4
Description
Hi, I am attempting to run your code on several datasets. However, I cannot figure out how to generate the superpixels files for these input images. I have carefully checked the preprocessing-scripts/selections.py and found the reseeds_cli.exe is needed.
I followed the instruction in https://github.com/davidstutz/seeds-revised to install reseeds_cli on Ubuntu, but it seems the arguments required are not the same with yours, e.g., there is no argument --index.
$ ../bin/reseeds_cli --help
Allowed options:
--help produce help message
--input arg the folder to process, may contain several
images
--bins arg (=5) number of bins used for color histograms
--neighborhood arg (=1) neighborhood size used for smoothing prior
--confidence arg (=0.100000001) minimum confidence used for block update
--iterations arg (=2) iterations at each level
--spatial-weight arg (=0.25) spatial weight
--superpixels arg (=400) desired number of supüerpixels
--verbose show additional information while processing
--csv save segmentation as CSV file
--contour save contour image of segmentation
--labels save label image of segmentation
--mean save mean colored image of segmentation
--output arg (=output) specify the output directory (default is
./output)
Could you please offer the executable file reseeds_cli.exe or give me some hints about how can I get access to this file? Thank a lot.
Moreover, why the generated superpixel files are all black in dataset/scannet-sample/raw/selections/superpixel? Thank again.