In [5]:
import h5py

temporal_proposals = h5py.File('../downloads/activitynet_v1-3_proposals.hdf5', 'r')
temporal_proposals.keys()
a = [x for x in temporal_proposals.keys()]

In [7]:
import random
import os
import h5py
import numpy as np
from work.dataset.activitynet import ActivityNetDataset

dataset = ActivityNetDataset(
    videos_path='../dataset/videos.json',
    labels_path='../dataset/labels.txt'
)
videos = dataset.get_subset_videos('validation')
videos = random.sample(videos, 8)

In [31]:
v_id = a[344][2:]

In [32]:
dataset.database[v_id]['annotations']


Out[32]:
[{'label': 'Playing drums', 'segment': [0, 116.30053198127925]}]

In [33]:
s = [x for x in temporal_proposals['v_'+v_id].keys()]
s


Out[33]:
['score', 'segment-end', 'segment-init']

In [34]:
print(temporal_proposals['v_'+v_id]['score'][...])
print(temporal_proposals['v_'+v_id]['segment-init'][...])
print(temporal_proposals['v_'+v_id]['segment-end'][...])


[ 0.65800254  0.65111832  0.65061255  0.65009434  0.64897037  0.64689578
  0.64218615  0.64037657  0.6399382   0.63856699  0.63848042  0.63839386
  0.63700158  0.63670515  0.63668809  0.6362368   0.63532533  0.63501645
  0.63449544  0.63441098  0.63432651  0.63325185  0.63147809  0.63119273
  0.63054709  0.62870786  0.62749624  0.62725795  0.62619146  0.62436571
  0.62353571  0.62283635  0.62239588  0.61073196  0.60635885  0.4794121
  0.47774372  0.47529929  0.35395478  0.34486648  0.33779985  0.33620751
  0.33212366  0.32479319  0.32287267  0.31803581  0.31718336  0.31471764
  0.31407964  0.31397615  0.3108762   0.31057846  0.30953108  0.30930621
  0.30926351  0.30867587  0.30859742  0.30811968  0.30750262  0.30701293
  0.30693351  0.3063839   0.3041589   0.29165373  0.07572927  0.07517117
  0.07387528  0.07269039  0.0725968   0.07208849  0.07179278  0.06951213
  0.06837637  0.0682641   0.06818128  0.06789184  0.06757242  0.06617975
  0.06578248  0.06556121  0.06550308  0.06539728  0.06466946  0.06199338
  0.06164489  0.06148467  0.0606398   0.05890397  0.05850301  0.05847378
  0.05804901  0.05645358  0.05572542  0.05562348  0.05527236  0.05467782
  0.05438287  0.0531473   0.05304354  0.05296472  0.05269479  0.05169279
  0.05127748  0.05058487  0.04955037  0.04933502]
[  1.64371945e+01   1.21942602e+01   7.58382755e+00   1.64371945e+01
   3.40771106e+00   2.03794485e+01   2.85980457e+01   2.85980457e+01
   3.40771106e+00   4.18279828e+01   4.18279828e+01   6.29090188e+01
   6.71185443e+01   6.29090188e+01   2.43885203e+01   3.29412069e+01
   7.12612518e+01   7.57714576e+01   1.19002616e+02   7.98807563e+01
   7.98807563e+01   5.43897412e+01   9.28100129e+01   7.57714576e+01
   4.99797622e+01   1.09881977e+02   4.57034189e+01   1.05471998e+02
   3.71173234e+01   8.42239174e+01   5.85324487e+01   1.01162246e+02
   9.69193115e+01   1.16797626e+02   1.12554692e+02   8.89011679e+01
   1.60362873e+00   9.14736556e+01   1.52678819e+01   1.97112698e+01
   4.10261684e+01   1.10249475e+01   6.88223998e+00   1.18067165e+02
   2.80969118e+01   6.24412938e+01   5.39888340e+01   2.40210221e+01
   3.25737086e+01   6.67176371e+01   5.82985862e+01   1.05304953e+02
   7.10942072e+01   4.96456729e+01   8.82998071e+01   7.95800759e+01
   7.52703236e+01   4.53693296e+01   1.09614706e+02   3.68166430e+01
   9.66854490e+01   1.00995201e+02   8.39900549e+01   1.13323097e+02
   2.12814896e+01   3.12707603e+01   1.72724178e+01   4.01909451e+01
   5.69956379e+01   6.16394794e+01   1.04202459e+02   4.29304775e+01
   7.01587571e+01   7.43682825e+01   8.29209691e+01   2.23839844e+01
   7.87114436e+01   3.42775642e+01   6.42787850e+01   5.54588270e+01
   9.22420611e+01   1.79405964e+01   4.34316115e+00   3.64491447e+01
   8.54266390e+01   8.11837046e+01   7.69407702e+01   1.37978889e+01
   4.37657008e+01   9.45472774e+00   1.20739880e+02   9.50484114e+01
   2.66603277e+01   5.24520231e+00   3.52464232e+01   6.51808262e+01
   1.08044486e+02   9.94249814e+01   1.15494678e+02   1.12220602e+02
   4.82090888e+01   1.16597172e+02  -1.00226796e-01   1.02364967e+02
   1.06674720e+02   8.67295873e+01]
[  20.98080925   16.67105704   12.36130482   33.4757498    20.98080925
   25.25715254   33.4757498    46.63886898    8.21859726   46.63886898
   67.98717649   67.98717649   72.33033764   81.05006887   29.3998601
   38.11959134   76.53986306   81.05006887  123.94713748  123.94713748
   85.1593675    59.53471671   98.08862416   93.81228087   55.25837342
  115.16058838   50.81498547  110.78401829   42.12866317   89.56934652
   63.34333495  106.54108394  102.29814958  120.97374253  119.13625128
   91.90797175    4.40997902   94.11296126   16.43719451   20.78035566
   41.96161851   12.12744229    7.851099    118.70193516   29.03236185
   63.47697068   55.09132876   24.98988109   33.70961232   67.65308717
   59.03358273  106.24040355   72.02965725   50.48089615   89.1350304
   80.48211703   76.20577374   46.47182432  110.51674684   37.68527522
   97.58749018  101.86383347   85.02573177  114.39218294   22.41739333
   32.47348184   18.44173043   41.39366667   58.49903982   62.7753831
  105.30495346   43.93274549   71.19443395   75.47077724   83.95664595
   23.65352381   79.81393839   35.44687678   65.281053     56.69495749
   92.87683078   19.07650013    5.47906484   37.08391445   86.66276944
   82.35301722   78.14349179   14.86697471   45.03524025   10.69085822
  121.74214797   96.45158649   28.09691176    6.41451493   36.5159626
   66.51718348  109.41425209  100.86156551  116.89785284  113.62377751
   49.41181033  117.59944041    1.36976621  103.90177832  108.04448588
   88.06594458]

In [ ]: