Hi all,
the `top_K` parameter in the `cv2.dnn.NMSBoxes` correspond to the maximum number of bounding-boxes to return right ?
Like if we know how many object we expect in the image.
If that's the case, I have an unexpected output when setting top_k to a value >0.
With the default value (<0), I have a sensible set of bounding-boxes (on the left below).
However with the same parameters, except setting top_k to an actual value, here 4, I get only the 2 top detections and not the top 4. Why is that ?
The bounding boxes with index 4, 100, 72 and 17 are indeed the one I want, so I can use top_k<0 and select the top_4 afterwards but I though setting top_K in the NMS could stop the NMS earlier and thus save time.
I am using
- opencv-python-headless 4.3.0.36 (installed via pip)
- python 3.7.4
on a win10 machine
Thanks !
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