Object labels "from 0 to num_classes-1" or from "1 to num_classes" in built in image object detection on Google Cloud?

Question

The Google built-in object detection documentation/reference says the the num_classes argument should be set as follows:

E.g., for num_classes=5, the range of image/class/label in input tf.Example needs to be [0, 4].

Yet, most other resources (e.g., here) on how to create your own dataset in the object detection API world say that labels should start with 1, that is, for 5 classes they should be [1,5].

My questions are:

Is the example in the reference documentation correct, that is, should I use [0,4] for 5 classes?

Does it matter at all, i.e., can this break the training procedure?

Is the "built-in object detection" algorithm special in other ways or can I follow the "using your own dataset" function to create my TFrecord files?

Answer 1

Seems like the labels should be [1,5]. The documentation has changed :)

See the updated documnetation under --> Hyperparameters --> num_classes