I'm trying to train a Neural Network how to detect cardboard boxes along with multiple classes of persons (people).
Although it's easy to detect persons and correctly classifies them, it's incredibly hard to detect cardboard boxes.
The boxes look like this:
My suspicion is that box is too simple of an object, and the neural network has a hard time detecting it because there are too little features to extract from the object.
The division of the dataset looks like this:
personA: 1160 personB: 1651 personC: 2136 person: 1959 box: 2798
Persons are wearing different safety items, based on the items are classified, while detected as whole person, not just the item.
I tried to use:
ssd300_incetpionv2 ssd512_inceptionv2 faster_rcnn_inceptionv2
All of these are detecting and classifying persons much better than boxes. I cannot provide exact
mAP (don't have it).