A tensorflow pretrained object detection model like ssd_mobilenet_v2 is trained on COCO dataset and make prediction on 90 different classes defined in its labelmap file.
I’ve finetuned it with a set of new images : “helmet” and “heads” (these classes does not exist in COCO Dataset.). The result is a new model that works fine, but only makes prediction on these 2 new classes.
My question : How to get a new model that contains 90+2 = 92 classes.
(90 class from the pre-trained model + my 2 new classes)