h5py for wider

wider.py

import numpy as np, h5py
from collections import defaultdict
import os

f = h5py.File('wider_face_train.mat','r')
event_list = f.get('event_list')
print f[event_list.value[0][0]].value.tostring()

#  for i in range(0, 61):
    #  print f[event_list.value[0][i]].value.tostring()


file_list = f.get('file_list')
print f[f[file_list.value[0][0]].value[0][0]].value.tostring()

print f[file_list.value[0][0]].value[0]

face_bbx_list = f.get('face_bbx_list')
print f[f[face_bbx_list.value[0][0]].value[0][0]].value

coord = []
for event_idx, event in enumerate(event_list.value[0]):
    directory = f[event].value.tostring()
    for im_idx, im in enumerate(f[file_list.value[0][event_idx]].value[0]):
        # loop each image's name
        im_name = f[im].value.tostring()
        print os.path.join(directory, im_name)
        bbox = f[f[face_bbx_list.value[0][event_idx]].value[0][im_idx]].value
        print bbox