I’m trying to utilize one of the two (one 3, two 3) Colab tutorials (they are very similar but have slight differences - is there a reason to use one over the other?) that retrain efficientDet-lite on a custom dataset and compile for coral edge tpu.
All I am changing from these tutorials is the data to be trained on - I am uploading my files to drive, mounting the drive in the notebook, and then trying to use DataLoader on the VOC xml data, and I get this issue.
The issue I have, is that I can find no annotation tool that is open source that exports directly to csv in the AutoML format (labelimg does but I cannot get that to work on macOS).
So I am trying to load annotation data from makesense.ai exported as VOC xml, but this is not working in the Colab, so my model cannot get trained 
Here’s my modified code from the tutorial referenced as “two” above:
from google.colab import drive

drive.mount('/content/drive')

images_dir = '/content/drive/MyDrive/Colab\ Notebooks/example_data\ frames\ 16fps'

annotations_dir = '/content/drive/MyDrive/Colab\ Notebooks/labels_deep-learning_2021-08-26-03-32-39'

label_map = {1: 'person', 2: 'not-person'}

train_data, validation_data, test_data = object_detector.DataLoader.from_pascal_voc(images_dir,annotations_dir,label_map)

As mentioned before, I have more images referenced than are annotated - but I would think that those images that are not referenced in the annotation would just be ignored.
If my label_map doesn’t match the labels in my annotations, will that cause this error?