Various questions

First off, thanks very much for all your work on this - a really clean and understandable implementation of YOLO 😄 I have a few questions (probably very basic) about getting started with training and inference with tensornets - in specific to the YOLOv2 model:

1. I am wanting to train YOLOv2 on the Open Images dataset. How can the tensornets implementation of YOLOv2 be used with a custom number of classes (545 in my case)?
2. After training, how would one save the weights to a file and load them back in later for inference?
3. Can layers be frozen during training (i.e. only train the last 4 layers) similar to what one can do in darknet with stopbackward=1?
4. Is there support for training the YOLOv2 model with a TPU? If not, is there a somewhat straightforward path to adding that functionality?
5. Can YOLOv2 be trained and used for inference with FP16 precision to speed things up - and can the existing pretrained weights be converted to FP16 so as to not necessitate training from scratch?

Thanks very much!

[abagshaw]

@taehoonlee Awesome, thanks so much! Right now I’m swamped with work so I don’t see myself getting time to tinker around with it - but if a break comes up I’ll certainly give it a shot.

[taehoonlee]

You are right @abagshaw, (# classes + 5) * # anchors = (545 + 5) * 5 = 2750. Thank you so much!