Thank you for replying.  I’m trying to encode two different sets of pictures at 274*274, 3 channels, down to 1000 features, then concatenation those features with a tabular data set to ultimately predict a binary outcome (kind of like the Ludwig model).  The I’d is 1 to N pictures where 1 ID (set as the index) could have up to four pictures.  I plan to average over the features for IDs with more than one picture.
The tabular dataset also has the IDs as the index.  I’m just not sure how to join with the final feature sets from the encoded pictures without that ID on the photo side.
So, yes, any type of code would help to assign policy IDs with the picture.  The csv’s (and dataframe) column headers are:
Index: ID
File name
Location
Label
The directory the images are in is split between the positive class and negative class.