I have trained a model using tensorflow object detection/SSD mobilenet. It works great!
I'd like to add a class to it - just to detect pens or something.
How can I do this?
I have created my image set already, I just cannot find any tutorials or info on how to add a single class to an existing model.
Thanks!
Your idea of adding a class to an existing model, speaking in tensorflow object detection api lingo, is to retrain a custom object detection model on a custom dataset (in this case, your pen dataset).
There are quite some good tutorials on how to build a custom object detector by using tensorflow object detection api.
For example, sentdex posted a very good step by step tutorial here. Also the official github repo page contains some good tutorials like this one: bringing in your own dataset, this is actually the same as adding or deleting classes from the pretrained model in some sense.
But again, I think the above tutorials don't serve the exact goal of adding class to the model, it is only adding new class if you have data for old classes and new classes and retrain on all of them. Since in your case you only have data for new class, it is more formally referred as retrain a custom object detection model.
You can use your existing weights pretrained weights to retrain the model by adding data for the new class.
