@ilastik_team and @k-dominik I am looking for documentation on the format/layout of the ilastik HDF5 Feature Export Table. During an object classification, you can choose to export your features as HDF5 or CSV, I did a test round with CSV export, which output a nice CSV:
then decided to use hdf5 format for my large batch processing run. I don’t have any experience with this format, but figured it would be easier to work with if I had a lot of data output… but I think I made a mistake.
I tried inspecting the hdf5 output from about 40 images > 0.5GB each, with python like so:
import h5py as h h5path = "../example_h5_data_output/nav16.h5" f = h.File(h5path, 'r') f.keys() # <KeysViewHDF5 ['images', 'table']>
images is an HDF5
group (http://docs.h5py.org/en/latest/high/group.html#group), and
table is an HDF5
dataset (http://docs.h5py.org/en/latest/high/dataset.html#dataset). Neither has any metadata associated with it (
f['table'].attrs.keys() returns nothing, and
f['images'].keys() returns a view of integers as strings), and
f['table'] # (0, 0, 1, b'0', b'nav16', 0.76, 0.24, 0.8555037,...) # length of 196 len(f['table']) # 821
How do I interpret this data? How is the “Feature Export” table organized for HDF5 export? Is there any way to access a header field so I can interpret it as I would with a CSV?