Hola, we are running the current version of OV. we have been using the gender model for over a year pretty successfully. i might be insane, but it just seems like it's accuracy has degraded since we first started using it. we have built a number of test tools to strip everything down except for simply the gender model (plus the face detector) and it just is not doing well in terms of accuracy.
- do you intel actually improve on the "canned" ov models like gender or are they static?
- we are using a myriad of different face detectors in different use cases. might it be that the gender model needs a very specific crop of the face or resolution for it' to perform with accuracy?
- any suggestions of another gender model that may have better accuracy?
thanks in advance. -tim
Dear Huckaby, Tim,
You are definitely not insane.
Please look at the intel model downloads site here . The last modified date will tell you whether the model has been modified or not.
Also, pre-processing images before training the model - but failing to tell Model Optimizer about it - is a common reason behind why customers experience accuracy loss. Yes if you crop your images before training then you had better tell model optimizer about it through --input_shape.
Please see my detailed answer to this post