ayalaa2:

I’m going to assume that by “background or not labeled objects”, you mean images that are labeled as “no object”.


They are labeled, but no objects are on them. My model should output no “boxes” in these cases. For example let’s assume my dataset contains K images and only small percent of them actually have cats on them. The rest of dataset contains random images of other objects, animals etc. And my model should properly detect box where cat is. Is this helpful description? @ayalaa2
Thanks