So long story short, makesense.ai csv export is not compatible with AutoML, so I am trying to load my data using VOC XML (which I assume is equivalent to PASCAL VOC).
When I try to load the label map, I get this issue:
I have passed the label_map as a copy/paste from the documentation, my images_dir argument is my folder with all of my images, and my annotations_dir argument is my folder with all of my xml files.
Note, I have more images than annotations - I don’t know if this causes problems but I assume that all that matters is that the images referenced in annotations exist in the images_dir - extra images not referenced by the xml annotation files will just be ignored.
I’m trying to utilize one of the two (one, two) 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:
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?