Convert IMDB META data(matlab .mat file) to csv.

imdb_meta_to_csv.py

#! /usr/bin/env python
"""
Convert IMDB META data(matlab .mat) to csv.

IMDB-WIKI – 500k+ face images with age and gender labels
- https://data.vision.ee.ethz.ch/cvl/rrothe/imdb-wiki/
- https://stackoverflow.com/questions/13965740/converting-matlabs-datenum-format-to-python
"""

from datetime import datetime, timedelta
import numpy as np
import scipy
from scipy.io import loadmat
import pandas as pd

def matlab_datenum2dt(matlab_datenum):
    return datetime.fromordinal(int(matlab_datenum) - 366) +\
            timedelta(days=int(matlab_datenum%1))

def main():

    path_save = 'wiki/wiki.pkl'
    path_mat = 'wiki/wiki.mat'
    mat = loadmat(path_mat)

    print(mat['__header__'])
    print(mat['__version__'])

    # Extract values
    dt = mat['wiki'][0, 0]

    # Check for columns
    print('columns:\n', dt.dtype.names)

    # Extract values with simple format
    keys_s = ('gender', 'dob', 'photo_taken',
              'face_score', 'second_face_score')
    values = {k: dt[k].squeeze() for k in keys_s}

    # Extract values with nested format
    keys_n = ('full_path', 'name')
    for k in keys_n:
        values[k] = np.array([x if not x else x[0] for x in dt[k][0]])

    # Convert face location to DataFrame
    # img(face_location(2):face_location(4),face_location(1):face_location(3),:))
    values['face_location'] =\
        [tuple(x[0].tolist()) for x in dt['face_location'].squeeze()]

    # Check all values extracted have same length
    set_nrows = {len(v) for _, v in values.items()}
    assert len(set_nrows) == 1

    df_values = pd.DataFrame(values)

    # Convert matlab datenum to datetime
    df_values['dob'] = df_values['dob'].apply(matlab_datenum2dt)

    # Calc ages when photo taken
    df_values['photo_taken_age'] = \
        df_values.apply(lambda x: x['photo_taken'] - x['dob'].year, axis=1)

    # Concat all together and save
    # Do not use csv format to work around tuple to be string
    df_values.to_pickle(path_save)

if __name__ == '__main__':
    main()

👍 worked like a charm.
I just converted it to csv df_values.to_csv('wiki/wiki.csv', index=False)