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.
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!