Any easier tutorial for custom object detection?

First of all, many thanks for the great tutorials for object detection using pre-trained models. The code is so simple and easier to follow.

The problem is that custom object detection (with a small dataset) and transfer learning tutorials are complicated for beginners. I saw a tutorial somewhere that shows custom object detection using just 5 lines of code. Can you write a simple tutorial for us?

This looks very complicated. https://gluon-cv.mxnet.io/build/examples_classification/transfer_learning_minc.html Do we really need to learn all these details while you have such a great high level API?

I am sorry if this is not the right place to post this question but I need your help on this.

Thanks again.