How does TF know what object you are finetuning for
so I managed to figure out the issue.
We created the annotation tool from scratch and the issue that was causing underfitting whenever we trained regardless of the number of steps or various fixes I tried to implement was that When creating bounding boxes there was no check to identify whether the xmin and ymin coordinates were less than the xmax and ymax I did not realize this would be such a large issue but after creating a very simple check to ensure the coordinates are correct training ran smoothly.
I am trying to improve mobilenet_v2's detection of boats with about 400 images I have annotated myself, but keep on getting an underfitted model when I freeze the graphs, (detections are random does not actually seem to be detecting rather just randomly placing an inference). I performed 20,000 steps and had a loss of 2.3.
I was wondering how TF knows that what I am training it on with my custom label map
ID:1
Name: 'boat'
Is the same as what it regards as a boat ( with an ID of 9) in the mscoco label map.
Or whether, by using an ID of 1, I am training the models' idea of what a person looks like to be a boat?
Thank you in advance for any advice.