Hi everyone,
So I have a computer vision program made with opencv, cuda and NPP.
The complete program works on the watershed algorithm (made with opencv), but the algorithm slows the speed by 15 fps, so I tried to run the watershed algorithm on the GPU using NPP. I managed to get the NPP watershed working, but it behaves completely different than the opencv watershed.
I use watershed to separate touching apples into the correct amount of contours (1 per apple). Below you can see the output of the Opencv and NPP watershed.
output NPP:
output opencv:
As seen in the images, opencv nicely separates the touching apples quite nicely, but the NPP watershed does not. NPP just groups colours together that roughly have the same gray-value.
Is it possible to get roughly the same output using NPP as with opencv? If so, I would love to know!
Also, NPP watershed seems to be VERY slow when receiving an image with a lot of black in it. If anybody knows why, let me know!
Thanks!