The current way the data scripts (like data/prepare_data.py) work is very messy. Among many problems:
there are hard-coded paths from the original paper author's machine
the data files which are nested more than one level are not automatically read by the data/prepare_data.py script. One has to manually move these files. This should be automated
Overall the current data preparation process is extremely unclear. There are unanswered questions like:
[ ] which datasets from the AMASS should be downloaded
[ ] how to train a model using a smaller subset of datasets
[ ] after downloading datasets, how exactly the data should be organised for the scripts to work
The current way the data scripts (like
data/prepare_data.py
) work is very messy. Among many problems:data/prepare_data.py
script. One has to manually move these files. This should be automatedOverall the current data preparation process is extremely unclear. There are unanswered questions like: