sorry to say so, but it won’t work.
i haven’t seen any of your images, but cascades only work with rigid objects (e.g.: stop sign) , while fencing ppl are highly dynamic, you can’t assume they have a common, unique pose.
also, training “real world” cascades needs a ton of “real world” images, synthesizing positives from a few only does never work here.
again my advice would be: read up on re-training dnn’s like yolo or SSD, which can be done with a few hundred (positive) images only
(but no, don’t expect it to be easy …)
Thanks for the advice. I’ve experimented a bit with a dnn pre-trained for detecting people and it seems to work for detecting fencers. (Turns out fencers count as people).
This is more a learning exercise for me though, so I’d still like to get the cascade training working, even if the result isn’t useful.
If I’m reading that correctly, if you supply an infoname and no imgname then the background isn’t used. So my command is working as intended?
yes.
again, please note, that this gets very brittle with pose variation, you want to restrict it to a single pose, like there is a side-face cascade, but only for the left side
(you have to flip the img for the other side).
if you try to train it on both at the same time, you only “smear” the inference