Pre-processing images about ganav-offroad HOT 2 CLOSED

It’s very likely that the processing script is not suitable for your dataset. You need to figure out the logics for processing RUGD and apply to your dataset. I could not figure out the issue based on the information you provided.

If the first img is the ID img, it should not have white color as the value is vary large. So it must be some bugs directly using rugd script for your dataset. You might have to go through your code and figure out the specific bugs.

I’m closing the issue since it’s not about processing of rugd or rellis dataset.

from ganav-offroad.

Thanks for your reply!
Yes, it is the ID img, it seems that all the background are painted in white in that image.
I think I found the problem, in the '( )_relabel6.py' file , at line 35:
color_id[tuple([0, 0, 0])] = 255
This line of code will change the id of the class with RGB value (0, 0, 0) to 255, I'm not sure what is this line of code used for.
When I run the original 'rugd_relabel6.py' in colab, I added two print() function to see the value of the parameter 'color_id', and it turns out after running the code color_id[tuple([0, 0, 0])] = 255, an extra value (0, 0, 0): 255 is added to the parameter 'color_id':

PALETTE = [ [ 108, 64, 20 ], [ 255, 229, 204 ],[ 0, 102, 0 ],[ 0, 255, 0 ],
            [ 0, 153, 153 ],[ 0, 128, 255 ],[ 0, 0, 255 ],[ 255, 255, 0 ],[ 255, 0, 127 ],
            [ 64, 64, 64 ],[ 255, 128, 0 ],[ 255, 0, 0 ],[ 153, 76, 0 ],[ 102, 102, 0 ],
            [ 102, 0, 0 ],[ 0, 255, 128 ],[ 204, 153, 255 ],[ 102, 0, 204 ],[ 255, 153, 204 ],
            [ 0, 102, 102 ],[ 153, 204, 255 ],[ 102, 255, 255 ],[ 101, 101, 11 ],[ 114, 85, 47 ] ]

color_id = {tuple(c):i for i, c in enumerate(PALETTE)}
print(color_id)
color_id[tuple([0, 0, 0])] = 255
print(color_id)

result:

{(108, 64, 20): 0, (255, 229, 204): 1, (0, 102, 0): 2, (0, 255, 0): 3, (0, 153, 153): 4, (0, 128, 255): 5, (0, 0, 255): 6, (255, 255, 0): 7, (255, 0, 127): 8, (64, 64, 64): 9, (255, 128, 0): 10, (255, 0, 0): 11, (153, 76, 0): 12, (102, 102, 0): 13, (102, 0, 0): 14, (0, 255, 128): 15, (204, 153, 255): 16, (102, 0, 204): 17, (255, 153, 204): 18, (0, 102, 102): 19, (153, 204, 255): 20, (102, 255, 255): 21, (101, 101, 11): 22, (114, 85, 47): 23}
{(108, 64, 20): 0, (255, 229, 204): 1, (0, 102, 0): 2, (0, 255, 0): 3, (0, 153, 153): 4, (0, 128, 255): 5, (0, 0, 255): 6, (255, 255, 0): 7, (255, 0, 127): 8, (64, 64, 64): 9, (255, 128, 0): 10, (255, 0, 0): 11, (153, 76, 0): 12, (102, 102, 0): 13, (102, 0, 0): 14, (0, 255, 128): 15, (204, 153, 255): 16, (102, 0, 204): 17, (255, 153, 204): 18, (0, 102, 102): 19, (153, 204, 255): 20, (102, 255, 255): 21, (101, 101, 11): 22, (114, 85, 47): 23, (0, 0, 0): 255}

So I tried to comment out this line of code for my own dataset, and after pre-processing the processed image looked like this:

So there's no white color on the iD img now, since there are just 6 classes represented by RGB value from 0~5, all the pixel are in low RGB values, so theoretically it should be correct. So I think may be this line of code is not nessary: color_id[tuple([0, 0, 0])] = 255.

from ganav-offroad.