total_results.txt

5000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.4194
AP for bicycle = 0.3809
AP for bird = 0.3377
AP for boat = 0.0930
AP for bottle = 0.1241
AP for bus = 0.3856
AP for car = 0.6360
AP for cat = 0.4828
AP for chair = 0.2304
AP for cow = 0.3363
AP for diningtable = 0.1859
AP for dog = 0.4103
AP for horse = 0.3505
AP for motorbike = 0.4861
AP for person = 0.5537
AP for pottedplant = 0.1091
AP for sheep = 0.3206
AP for sofa = 0.3293
AP for train = 0.4096
AP for tvmonitor = 0.3794
Mean AP = 0.3480
~~~~~~~~
Results:
0.419
0.381
0.338
0.093
0.124
0.386
0.636
0.483
0.230
0.336
0.186
0.410
0.350
0.486
0.554
0.109
0.321
0.329
0.410
0.379
0.348
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



10000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.6280
AP for bicycle = 0.6350
AP for bird = 0.5514
AP for boat = 0.2716
AP for bottle = 0.2602
AP for bus = 0.6142
AP for car = 0.7237
AP for cat = 0.7552
AP for chair = 0.3198
AP for cow = 0.4963
AP for diningtable = 0.4040
AP for dog = 0.6777
AP for horse = 0.6593
AP for motorbike = 0.6324
AP for person = 0.6232
AP for pottedplant = 0.1774
AP for sheep = 0.5199
AP for sofa = 0.5165
AP for train = 0.6833
AP for tvmonitor = 0.5862
Mean AP = 0.5368
~~~~~~~~
Results:
0.628
0.635
0.551
0.272
0.260
0.614
0.724
0.755
0.320
0.496
0.404
0.678
0.659
0.632
0.623
0.177
0.520
0.517
0.683
0.586
0.537
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



15000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.6625
AP for bicycle = 0.7015
AP for bird = 0.5608
AP for boat = 0.4515
AP for bottle = 0.3007
AP for bus = 0.7181
AP for car = 0.7536
AP for cat = 0.7833
AP for chair = 0.3662
AP for cow = 0.6194
AP for diningtable = 0.4515
AP for dog = 0.7584
AP for horse = 0.7479
AP for motorbike = 0.6909
AP for person = 0.6521
AP for pottedplant = 0.2584
AP for sheep = 0.5871
AP for sofa = 0.5804
AP for train = 0.7253
AP for tvmonitor = 0.6215
Mean AP = 0.5996
~~~~~~~~
Results:
0.662
0.701
0.561
0.452
0.301
0.718
0.754
0.783
0.366
0.619
0.451
0.758
0.748
0.691
0.652
0.258
0.587
0.580
0.725
0.621
0.600
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



20000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.6867
AP for bicycle = 0.7440
AP for bird = 0.5972
AP for boat = 0.5510
AP for bottle = 0.3249
AP for bus = 0.7307
AP for car = 0.7667
AP for cat = 0.8173
AP for chair = 0.4175
AP for cow = 0.6307
AP for diningtable = 0.6142
AP for dog = 0.7729
AP for horse = 0.7673
AP for motorbike = 0.7323
AP for person = 0.6665
AP for pottedplant = 0.3238
AP for sheep = 0.6073
AP for sofa = 0.6338
AP for train = 0.7786
AP for tvmonitor = 0.6268
Mean AP = 0.6395
~~~~~~~~
Results:
0.687
0.744
0.597
0.551
0.325
0.731
0.767
0.817
0.418
0.631
0.614
0.773
0.767
0.732
0.667
0.324
0.607
0.634
0.779
0.627
0.640
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



25000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7106
AP for bicycle = 0.7583
AP for bird = 0.6576
AP for boat = 0.5832
AP for bottle = 0.3367
AP for bus = 0.7652
AP for car = 0.7784
AP for cat = 0.8380
AP for chair = 0.4657
AP for cow = 0.6923
AP for diningtable = 0.6212
AP for dog = 0.7903
AP for horse = 0.7904
AP for motorbike = 0.7533
AP for person = 0.6866
AP for pottedplant = 0.3439
AP for sheep = 0.6514
AP for sofa = 0.6770
AP for train = 0.8074
AP for tvmonitor = 0.6750
Mean AP = 0.6691
~~~~~~~~
Results:
0.711
0.758
0.658
0.583
0.337
0.765
0.778
0.838
0.466
0.692
0.621
0.790
0.790
0.753
0.687
0.344
0.651
0.677
0.807
0.675
0.669
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



30000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.6617
AP for bicycle = 0.7130
AP for bird = 0.6166
AP for boat = 0.4900
AP for bottle = 0.3031
AP for bus = 0.5133
AP for car = 0.7388
AP for cat = 0.8047
AP for chair = 0.3437
AP for cow = 0.6294
AP for diningtable = 0.4931
AP for dog = 0.7758
AP for horse = 0.7095
AP for motorbike = 0.6986
AP for person = 0.6855
AP for pottedplant = 0.3080
AP for sheep = 0.6371
AP for sofa = 0.5988
AP for train = 0.4546
AP for tvmonitor = 0.4769
Mean AP = 0.5826
~~~~~~~~
Results:
0.662
0.713
0.617
0.490
0.303
0.513
0.739
0.805
0.344
0.629
0.493
0.776
0.709
0.699
0.686
0.308
0.637
0.599
0.455
0.477
0.583
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



35000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7439
AP for bicycle = 0.7686
AP for bird = 0.6786
AP for boat = 0.6051
AP for bottle = 0.3719
AP for bus = 0.7893
AP for car = 0.7864
AP for cat = 0.8531
AP for chair = 0.4950
AP for cow = 0.7239
AP for diningtable = 0.6385
AP for dog = 0.8145
AP for horse = 0.8185
AP for motorbike = 0.7627
AP for person = 0.7149
AP for pottedplant = 0.3525
AP for sheep = 0.6523
AP for sofa = 0.7225
AP for train = 0.8213
AP for tvmonitor = 0.7117
Mean AP = 0.6913
~~~~~~~~
Results:
0.744
0.769
0.679
0.605
0.372
0.789
0.786
0.853
0.495
0.724
0.639
0.815
0.819
0.763
0.715
0.353
0.652
0.723
0.821
0.712
0.691
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



40000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7227
AP for bicycle = 0.7650
AP for bird = 0.6490
AP for boat = 0.6117
AP for bottle = 0.3991
AP for bus = 0.7978
AP for car = 0.7939
AP for cat = 0.8230
AP for chair = 0.4973
AP for cow = 0.7248
AP for diningtable = 0.6791
AP for dog = 0.8003
AP for horse = 0.7996
AP for motorbike = 0.7333
AP for person = 0.7160
AP for pottedplant = 0.3643
AP for sheep = 0.6692
AP for sofa = 0.7136
AP for train = 0.8127
AP for tvmonitor = 0.7091
Mean AP = 0.6891
~~~~~~~~
Results:
0.723
0.765
0.649
0.612
0.399
0.798
0.794
0.823
0.497
0.725
0.679
0.800
0.800
0.733
0.716
0.364
0.669
0.714
0.813
0.709
0.689
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



45000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7374
AP for bicycle = 0.7631
AP for bird = 0.6787
AP for boat = 0.5931
AP for bottle = 0.3647
AP for bus = 0.7805
AP for car = 0.7981
AP for cat = 0.8581
AP for chair = 0.4799
AP for cow = 0.7576
AP for diningtable = 0.6733
AP for dog = 0.8179
AP for horse = 0.8309
AP for motorbike = 0.7497
AP for person = 0.7062
AP for pottedplant = 0.3921
AP for sheep = 0.6733
AP for sofa = 0.7171
AP for train = 0.8038
AP for tvmonitor = 0.6859
Mean AP = 0.6931
~~~~~~~~
Results:
0.737
0.763
0.679
0.593
0.365
0.780
0.798
0.858
0.480
0.758
0.673
0.818
0.831
0.750
0.706
0.392
0.673
0.717
0.804
0.686
0.693
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



50000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7591
AP for bicycle = 0.8020
AP for bird = 0.7179
AP for boat = 0.6428
AP for bottle = 0.4062
AP for bus = 0.7849
AP for car = 0.8148
AP for cat = 0.8558
AP for chair = 0.5205
AP for cow = 0.7284
AP for diningtable = 0.7116
AP for dog = 0.8156
AP for horse = 0.8266
AP for motorbike = 0.7749
AP for person = 0.7336
AP for pottedplant = 0.4366
AP for sheep = 0.7113
AP for sofa = 0.7187
AP for train = 0.8339
AP for tvmonitor = 0.7155
Mean AP = 0.7155
~~~~~~~~
Results:
0.759
0.802
0.718
0.643
0.406
0.785
0.815
0.856
0.520
0.728
0.712
0.816
0.827
0.775
0.734
0.437
0.711
0.719
0.834
0.715
0.716
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



55000 iterations:
Evaluating detections
Writing aeroplane VOC results file/home/river/code/Python/ssd.pytorch-master/eval.py:153: DeprecationWarning: elementwise comparison failed; this will raise an error in the future.
  if dets == []:
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7482
AP for bicycle = 0.8164
AP for bird = 0.6917
AP for boat = 0.6405
AP for bottle = 0.3980
AP for bus = 0.8041
AP for car = 0.8040
AP for cat = 0.8572
AP for chair = 0.5270
AP for cow = 0.7927
AP for diningtable = 0.7147
AP for dog = 0.8265
AP for horse = 0.8250
AP for motorbike = 0.7983
AP for person = 0.7366
AP for pottedplant = 0.4017
AP for sheep = 0.6665
AP for sofa = 0.7664
AP for train = 0.8302
AP for tvmonitor = 0.7103
Mean AP = 0.7178
~~~~~~~~
Results:
0.748
0.816
0.692
0.641
0.398
0.804
0.804
0.857
0.527
0.793
0.715
0.826
0.825
0.798
0.737
0.402
0.667
0.766
0.830
0.710
0.718
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



60000 iterations:
Evaluating detections
Writing aeroplane VOC results file/home/river/code/Python/ssd.pytorch-master/eval.py:153: DeprecationWarning: elementwise comparison failed; this will raise an error in the future.
  if dets == []:
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7648
AP for bicycle = 0.7917
AP for bird = 0.7051
AP for boat = 0.6443
AP for bottle = 0.4094
AP for bus = 0.7996
AP for car = 0.8169
AP for cat = 0.8645
AP for chair = 0.5346
AP for cow = 0.7238
AP for diningtable = 0.7107
AP for dog = 0.8319
AP for horse = 0.8321
AP for motorbike = 0.7983
AP for person = 0.7390
AP for pottedplant = 0.4255
AP for sheep = 0.6984
AP for sofa = 0.7715
AP for train = 0.8371
AP for tvmonitor = 0.7333
Mean AP = 0.7216
~~~~~~~~
Results:
0.765
0.792
0.705
0.644
0.409
0.800
0.817
0.864
0.535
0.724
0.711
0.832
0.832
0.798
0.739
0.426
0.698
0.772
0.837
0.733
0.722
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



65000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7654
AP for bicycle = 0.7852
AP for bird = 0.7042
AP for boat = 0.6598
AP for bottle = 0.3991
AP for bus = 0.7926
AP for car = 0.8211
AP for cat = 0.8750
AP for chair = 0.5322
AP for cow = 0.7561
AP for diningtable = 0.6892
AP for dog = 0.8221
AP for horse = 0.8300
AP for motorbike = 0.7953
AP for person = 0.7423
AP for pottedplant = 0.4309
AP for sheep = 0.7179
AP for sofa = 0.7464
AP for train = 0.8494
AP for tvmonitor = 0.7409
Mean AP = 0.7228
~~~~~~~~
Results:
0.765
0.785
0.704
0.660
0.399
0.793
0.821
0.875
0.532
0.756
0.689
0.822
0.830
0.795
0.742
0.431
0.718
0.746
0.849
0.741
0.723
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



70000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7364
AP for bicycle = 0.8272
AP for bird = 0.6897
AP for boat = 0.6479
AP for bottle = 0.4263
AP for bus = 0.8156
AP for car = 0.8296
AP for cat = 0.8573
AP for chair = 0.5408
AP for cow = 0.7730
AP for diningtable = 0.7199
AP for dog = 0.8274
AP for horse = 0.8462
AP for motorbike = 0.7949
AP for person = 0.7406
AP for pottedplant = 0.3959
AP for sheep = 0.7104
AP for sofa = 0.7641
AP for train = 0.8394
AP for tvmonitor = 0.7325
Mean AP = 0.7258
~~~~~~~~
Results:
0.736
0.827
0.690
0.648
0.426
0.816
0.830
0.857
0.541
0.773
0.720
0.827
0.846
0.795
0.741
0.396
0.710
0.764
0.839
0.733
0.726
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



75000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7618
AP for bicycle = 0.8319
AP for bird = 0.7150
AP for boat = 0.6632
AP for bottle = 0.4253
AP for bus = 0.8126
AP for car = 0.8301
AP for cat = 0.8599
AP for chair = 0.5359
AP for cow = 0.7718
AP for diningtable = 0.7293
AP for dog = 0.8382
AP for horse = 0.8341
AP for motorbike = 0.7961
AP for person = 0.7510
AP for pottedplant = 0.4344
AP for sheep = 0.7222
AP for sofa = 0.7620
AP for train = 0.8308
AP for tvmonitor = 0.7206
Mean AP = 0.7313
~~~~~~~~
Results:
0.762
0.832
0.715
0.663
0.425
0.813
0.830
0.860
0.536
0.772
0.729
0.838
0.834
0.796
0.751
0.434
0.722
0.762
0.831
0.721
0.731
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



80000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7775
AP for bicycle = 0.8091
AP for bird = 0.7196
AP for boat = 0.6773
AP for bottle = 0.4257
AP for bus = 0.8238
AP for car = 0.8299
AP for cat = 0.8557
AP for chair = 0.5558
AP for cow = 0.7541
AP for diningtable = 0.6951
AP for dog = 0.8155
AP for horse = 0.8299
AP for motorbike = 0.8002
AP for person = 0.7408
AP for pottedplant = 0.4143
AP for sheep = 0.6975
AP for sofa = 0.7693
AP for train = 0.8400
AP for tvmonitor = 0.7560
Mean AP = 0.7294
~~~~~~~~
Results:
0.777
0.809
0.720
0.677
0.426
0.824
0.830
0.856
0.556
0.754
0.695
0.815
0.830
0.800
0.741
0.414
0.697
0.769
0.840
0.756
0.729
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

Process finished with exit code 0

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



85000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7835
AP for bicycle = 0.8043
AP for bird = 0.7241
AP for boat = 0.6597
AP for bottle = 0.4143
AP for bus = 0.8291
AP for car = 0.8298
AP for cat = 0.8655
AP for chair = 0.5808
AP for cow = 0.7906
AP for diningtable = 0.7212
AP for dog = 0.8298
AP for horse = 0.8374
AP for motorbike = 0.8033
AP for person = 0.7571
AP for pottedplant = 0.4246
AP for sheep = 0.7506
AP for sofa = 0.7513
AP for train = 0.8435
AP for tvmonitor = 0.7428
Mean AP = 0.7372
~~~~~~~~
Results:
0.783
0.804
0.724
0.660
0.414
0.829
0.830
0.865
0.581
0.791
0.721
0.830
0.837
0.803
0.757
0.425
0.751
0.751
0.844
0.743
0.737
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



90000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7747
AP for bicycle = 0.8084
AP for bird = 0.7447
AP for boat = 0.6562
AP for bottle = 0.4220
AP for bus = 0.8364
AP for car = 0.8303
AP for cat = 0.8728
AP for chair = 0.5610
AP for cow = 0.7991
AP for diningtable = 0.7326
AP for dog = 0.8444
AP for horse = 0.8521
AP for motorbike = 0.8083
AP for person = 0.7515
AP for pottedplant = 0.4539
AP for sheep = 0.7256
AP for sofa = 0.7670
AP for train = 0.8575
AP for tvmonitor = 0.7541
Mean AP = 0.7426
~~~~~~~~
Results:
0.775
0.808
0.745
0.656
0.422
0.836
0.830
0.873
0.561
0.799
0.733
0.844
0.852
0.808
0.751
0.454
0.726
0.767
0.857
0.754
0.743
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



95000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7840
AP for bicycle = 0.8190
AP for bird = 0.7094
AP for boat = 0.6746
AP for bottle = 0.4401
AP for bus = 0.8097
AP for car = 0.8375
AP for cat = 0.8674
AP for chair = 0.5823
AP for cow = 0.7947
AP for diningtable = 0.7034
AP for dog = 0.8420
AP for horse = 0.8328
AP for motorbike = 0.8058
AP for person = 0.7606
AP for pottedplant = 0.4619
AP for sheep = 0.7333
AP for sofa = 0.7724
AP for train = 0.8523
AP for tvmonitor = 0.7485
Mean AP = 0.7416
~~~~~~~~
Results:
0.784
0.819
0.709
0.675
0.440
0.810
0.837
0.867
0.582
0.795
0.703
0.842
0.833
0.806
0.761
0.462
0.733
0.772
0.852
0.748
0.742
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



100000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7670
AP for bicycle = 0.8195
AP for bird = 0.7268
AP for boat = 0.6524
AP for bottle = 0.4592
AP for bus = 0.8152
AP for car = 0.8315
AP for cat = 0.8768
AP for chair = 0.5659
AP for cow = 0.7869
AP for diningtable = 0.7317
AP for dog = 0.8449
AP for horse = 0.8490
AP for motorbike = 0.8038
AP for person = 0.7591
AP for pottedplant = 0.4482
AP for sheep = 0.7141
AP for sofa = 0.7678
AP for train = 0.8514
AP for tvmonitor = 0.7390
Mean AP = 0.7405
~~~~~~~~
Results:
0.767
0.820
0.727
0.652
0.459
0.815
0.831
0.877
0.566
0.787
0.732
0.845
0.849
0.804
0.759
0.448
0.714
0.768
0.851
0.739
0.741
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



105000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7979
AP for bicycle = 0.8247
AP for bird = 0.7264
AP for boat = 0.6583
AP for bottle = 0.4276
AP for bus = 0.8323
AP for car = 0.8408
AP for cat = 0.8706
AP for chair = 0.5642
AP for cow = 0.7520
AP for diningtable = 0.7305
AP for dog = 0.8158
AP for horse = 0.8087
AP for motorbike = 0.8156
AP for person = 0.7512
AP for pottedplant = 0.4743
AP for sheep = 0.7080
AP for sofa = 0.7689
AP for train = 0.8607
AP for tvmonitor = 0.7517
Mean AP = 0.7390
~~~~~~~~
Results:
0.798
0.825
0.726
0.658
0.428
0.832
0.841
0.871
0.564
0.752
0.731
0.816
0.809
0.816
0.751
0.474
0.708
0.769
0.861
0.752
0.739
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

Process finished with exit code 0

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



110000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7900
AP for bicycle = 0.8203
AP for bird = 0.7077
AP for boat = 0.6830
AP for bottle = 0.4619
AP for bus = 0.8197
AP for car = 0.8334
AP for cat = 0.8747
AP for chair = 0.5561
AP for cow = 0.7960
AP for diningtable = 0.7479
AP for dog = 0.8433
AP for horse = 0.8508
AP for motorbike = 0.8064
AP for person = 0.7526
AP for pottedplant = 0.4527
AP for sheep = 0.7035
AP for sofa = 0.7715
AP for train = 0.8434
AP for tvmonitor = 0.7449
Mean AP = 0.7430
~~~~~~~~
Results:
0.790
0.820
0.708
0.683
0.462
0.820
0.833
0.875
0.556
0.796
0.748
0.843
0.851
0.806
0.753
0.453
0.704
0.772
0.843
0.745
0.743
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



115000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7829
AP for bicycle = 0.8282
AP for bird = 0.7199
AP for boat = 0.6557
AP for bottle = 0.4531
AP for bus = 0.8268
AP for car = 0.8413
AP for cat = 0.8655
AP for chair = 0.5775
AP for cow = 0.7815
AP for diningtable = 0.7432
AP for dog = 0.8404
AP for horse = 0.8437
AP for motorbike = 0.8067
AP for person = 0.7584
AP for pottedplant = 0.4756
AP for sheep = 0.7457
AP for sofa = 0.7797
AP for train = 0.8430
AP for tvmonitor = 0.7441
Mean AP = 0.7456
~~~~~~~~
Results:
0.783
0.828
0.720
0.656
0.453
0.827
0.841
0.865
0.578
0.781
0.743
0.840
0.844
0.807
0.758
0.476
0.746
0.780
0.843
0.744
0.746
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



120000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7753
AP for bicycle = 0.8214
AP for bird = 0.7213
AP for boat = 0.6573
AP for bottle = 0.4669
AP for bus = 0.8267
AP for car = 0.8423
AP for cat = 0.8641
AP for chair = 0.5814
AP for cow = 0.7993
AP for diningtable = 0.7358
AP for dog = 0.8461
AP for horse = 0.8453
AP for motorbike = 0.8089
AP for person = 0.7648
AP for pottedplant = 0.4659
AP for sheep = 0.7369
AP for sofa = 0.7670
AP for train = 0.8263
AP for tvmonitor = 0.7367
Mean AP = 0.7445
~~~~~~~~
Results:
0.775
0.821
0.721
0.657
0.467
0.827
0.842
0.864
0.581
0.799
0.736
0.846
0.845
0.809
0.765
0.466
0.737
0.767
0.826
0.737
0.744
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



125000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7983
AP for bicycle = 0.8179
AP for bird = 0.7397
AP for boat = 0.6763
AP for bottle = 0.4474
AP for bus = 0.8337
AP for car = 0.8400
AP for cat = 0.8573
AP for chair = 0.5753
AP for cow = 0.7795
AP for diningtable = 0.7394
AP for dog = 0.8387
AP for horse = 0.8404
AP for motorbike = 0.7938
AP for person = 0.7621
AP for pottedplant = 0.4599
AP for sheep = 0.7477
AP for sofa = 0.7555
AP for train = 0.8589
AP for tvmonitor = 0.7461
Mean AP = 0.7454
~~~~~~~~
Results:
0.798
0.818
0.740
0.676
0.447
0.834
0.840
0.857
0.575
0.780
0.739
0.839
0.840
0.794
0.762
0.460
0.748
0.756
0.859
0.746
0.745
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



130000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7869
AP for bicycle = 0.8256
AP for bird = 0.7304
AP for boat = 0.6709
AP for bottle = 0.4603
AP for bus = 0.8322
AP for car = 0.8465
AP for cat = 0.8691
AP for chair = 0.5802
AP for cow = 0.8000
AP for diningtable = 0.7595
AP for dog = 0.8388
AP for horse = 0.8480
AP for motorbike = 0.8239
AP for person = 0.7702
AP for pottedplant = 0.4659
AP for sheep = 0.7357
AP for sofa = 0.7899
AP for train = 0.8534
AP for tvmonitor = 0.7504
Mean AP = 0.7519
~~~~~~~~
Results:
0.787
0.826
0.730
0.671
0.460
0.832
0.846
0.869
0.580
0.800
0.760
0.839
0.848
0.824
0.770
0.466
0.736
0.790
0.853
0.750
0.752
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



135000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7979
AP for bicycle = 0.8262
AP for bird = 0.7565
AP for boat = 0.6554
AP for bottle = 0.4715
AP for bus = 0.8209
AP for car = 0.8401
AP for cat = 0.8840
AP for chair = 0.5626
AP for cow = 0.8021
AP for diningtable = 0.7616
AP for dog = 0.8402
AP for horse = 0.8472
AP for motorbike = 0.8103
AP for person = 0.7654
AP for pottedplant = 0.4446
AP for sheep = 0.7492
AP for sofa = 0.7720
AP for train = 0.8577
AP for tvmonitor = 0.7489
Mean AP = 0.7507
~~~~~~~~
Results:
0.798
0.826
0.757
0.655
0.472
0.821
0.840
0.884
0.563
0.802
0.762
0.840
0.847
0.810
0.765
0.445
0.749
0.772
0.858
0.749
0.751
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



140000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7797
AP for bicycle = 0.8078
AP for bird = 0.7111
AP for boat = 0.6799
AP for bottle = 0.4745
AP for bus = 0.8431
AP for car = 0.8401
AP for cat = 0.8577
AP for chair = 0.5672
AP for cow = 0.7924
AP for diningtable = 0.7246
AP for dog = 0.8322
AP for horse = 0.8394
AP for motorbike = 0.7963
AP for person = 0.7579
AP for pottedplant = 0.4546
AP for sheep = 0.7627
AP for sofa = 0.7735
AP for train = 0.8407
AP for tvmonitor = 0.7619
Mean AP = 0.7449
~~~~~~~~
Results:
0.780
0.808
0.711
0.680
0.474
0.843
0.840
0.858
0.567
0.792
0.725
0.832
0.839
0.796
0.758
0.455
0.763
0.774
0.841
0.762
0.745
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

Process finished with exit code 0

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



145000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7881
AP for bicycle = 0.8317
AP for bird = 0.7259
AP for boat = 0.6920
AP for bottle = 0.4696
AP for bus = 0.8335
AP for car = 0.8457
AP for cat = 0.8822
AP for chair = 0.5619
AP for cow = 0.8154
AP for diningtable = 0.7375
AP for dog = 0.8408
AP for horse = 0.8532
AP for motorbike = 0.8136
AP for person = 0.7645
AP for pottedplant = 0.4744
AP for sheep = 0.7606
AP for sofa = 0.7658
AP for train = 0.8717
AP for tvmonitor = 0.7307
Mean AP = 0.7529
~~~~~~~~
Results:
0.788
0.832
0.726
0.692
0.470
0.834
0.846
0.882
0.562
0.815
0.738
0.841
0.853
0.814
0.764
0.474
0.761
0.766
0.872
0.731
0.753
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



150000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7985
AP for bicycle = 0.8070
AP for bird = 0.7304
AP for boat = 0.6677
AP for bottle = 0.4591
AP for bus = 0.8412
AP for car = 0.8437
AP for cat = 0.8791
AP for chair = 0.5753
AP for cow = 0.7950
AP for diningtable = 0.7429
AP for dog = 0.8426
AP for horse = 0.8564
AP for motorbike = 0.8269
AP for person = 0.7673
AP for pottedplant = 0.4698
AP for sheep = 0.7282
AP for sofa = 0.7784
AP for train = 0.8718
AP for tvmonitor = 0.7517
Mean AP = 0.7517
~~~~~~~~
Results:
0.799
0.807
0.730
0.668
0.459
0.841
0.844
0.879
0.575
0.795
0.743
0.843
0.856
0.827
0.767
0.470
0.728
0.778
0.872
0.752
0.752
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



155000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7950
AP for bicycle = 0.8261
AP for bird = 0.7391
AP for boat = 0.6708
AP for bottle = 0.4553
AP for bus = 0.8321
AP for car = 0.8507
AP for cat = 0.8771
AP for chair = 0.5865
AP for cow = 0.8011
AP for diningtable = 0.7516
AP for dog = 0.8419
AP for horse = 0.8526
AP for motorbike = 0.8166
AP for person = 0.7650
AP for pottedplant = 0.4663
AP for sheep = 0.7410
AP for sofa = 0.7663
AP for train = 0.8571
AP for tvmonitor = 0.7497
Mean AP = 0.7521
~~~~~~~~
Results:
0.795
0.826
0.739
0.671
0.455
0.832
0.851
0.877
0.587
0.801
0.752
0.842
0.853
0.817
0.765
0.466
0.741
0.766
0.857
0.750
0.752
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



160000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.8025
AP for bicycle = 0.8258
AP for bird = 0.7381
AP for boat = 0.6871
AP for bottle = 0.4766
AP for bus = 0.8337
AP for car = 0.8424
AP for cat = 0.8715
AP for chair = 0.5815
AP for cow = 0.8027
AP for diningtable = 0.7429
AP for dog = 0.8440
AP for horse = 0.8559
AP for motorbike = 0.8257
AP for person = 0.7638
AP for pottedplant = 0.4650
AP for sheep = 0.7530
AP for sofa = 0.7881
AP for train = 0.8630
AP for tvmonitor = 0.7576
Mean AP = 0.7560
~~~~~~~~
Results:
0.802
0.826
0.738
0.687
0.477
0.834
0.842
0.871
0.582
0.803
0.743
0.844
0.856
0.826
0.764
0.465
0.753
0.788
0.863
0.758
0.756
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



165000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.8137
AP for bicycle = 0.8371
AP for bird = 0.7505
AP for boat = 0.6680
AP for bottle = 0.4839
AP for bus = 0.8472
AP for car = 0.8411
AP for cat = 0.8711
AP for chair = 0.5857
AP for cow = 0.7883
AP for diningtable = 0.7501
AP for dog = 0.8483
AP for horse = 0.8574
AP for motorbike = 0.8243
AP for person = 0.7623
AP for pottedplant = 0.4777
AP for sheep = 0.7457
AP for sofa = 0.7517
AP for train = 0.8572
AP for tvmonitor = 0.7662
Mean AP = 0.7564
~~~~~~~~
Results:
0.814
0.837
0.750
0.668
0.484
0.847
0.841
0.871
0.586
0.788
0.750
0.848
0.857
0.824
0.762
0.478
0.746
0.752
0.857
0.766
0.756
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



170000 iterations:
Evaluating detections
Writing aeroplane VOC results fileWriting bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.8095
AP for bicycle = 0.8322
AP for bird = 0.7274
AP for boat = 0.6901
AP for bottle = 0.4682
AP for bus = 0.8392
AP for car = 0.8484
AP for cat = 0.8736
AP for chair = 0.5895
AP for cow = 0.7979
AP for diningtable = 0.7463
AP for dog = 0.8421
AP for horse = 0.8391
AP for motorbike = 0.8260
AP for person = 0.7633
AP for pottedplant = 0.4618
AP for sheep = 0.7286
AP for sofa = 0.7479
AP for train = 0.8537
AP for tvmonitor = 0.7596
Mean AP = 0.7522
~~~~~~~~
Results:
0.810
0.832
0.727
0.690
0.468
0.839
0.848
0.874
0.589
0.798
0.746
0.842
0.839
0.826
0.763
0.462
0.729
0.748
0.854
0.760
0.752
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



175000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7951
AP for bicycle = 0.8199
AP for bird = 0.7289
AP for boat = 0.6759
AP for bottle = 0.4811
AP for bus = 0.8394
AP for car = 0.8456
AP for cat = 0.8687
AP for chair = 0.5963
AP for cow = 0.8106
AP for diningtable = 0.7369
AP for dog = 0.8386
AP for horse = 0.8590
AP for motorbike = 0.8294
AP for person = 0.7684
AP for pottedplant = 0.4560
AP for sheep = 0.7579
AP for sofa = 0.7688
AP for train = 0.8507
AP for tvmonitor = 0.7485
Mean AP = 0.7538
~~~~~~~~
Results:
0.795
0.820
0.729
0.676
0.481
0.839
0.846
0.869
0.596
0.811
0.737
0.839
0.859
0.829
0.768
0.456
0.758
0.769
0.851
0.748
0.754
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



180000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7854
AP for bicycle = 0.8333
AP for bird = 0.7195
AP for boat = 0.6840
AP for bottle = 0.4530
AP for bus = 0.8120
AP for car = 0.8477
AP for cat = 0.8708
AP for chair = 0.5798
AP for cow = 0.8040
AP for diningtable = 0.7373
AP for dog = 0.8368
AP for horse = 0.8502
AP for motorbike = 0.8344
AP for person = 0.7667
AP for pottedplant = 0.4659
AP for sheep = 0.7428
AP for sofa = 0.7747
AP for train = 0.8358
AP for tvmonitor = 0.7569
Mean AP = 0.7495
~~~~~~~~
Results:
0.785
0.833
0.720
0.684
0.453
0.812
0.848
0.871
0.580
0.804
0.737
0.837
0.850
0.834
0.767
0.466
0.743
0.775
0.836
0.757
0.750
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



185000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.8126
AP for bicycle = 0.8226
AP for bird = 0.7303
AP for boat = 0.6682
AP for bottle = 0.4715
AP for bus = 0.8358
AP for car = 0.8521
AP for cat = 0.8729
AP for chair = 0.5796
AP for cow = 0.8033
AP for diningtable = 0.7424
AP for dog = 0.8388
AP for horse = 0.8562
AP for motorbike = 0.8300
AP for person = 0.7744
AP for pottedplant = 0.4758
AP for sheep = 0.7451
AP for sofa = 0.7778
AP for train = 0.8507
AP for tvmonitor = 0.7592
Mean AP = 0.7550
~~~~~~~~
Results:
0.813
0.823
0.730
0.668
0.471
0.836
0.852
0.873
0.580
0.803
0.742
0.839
0.856
0.830
0.774
0.476
0.745
0.778
0.851
0.759
0.755
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************



190000 iterations:
Evaluating detections
Writing aeroplane VOC results file
Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.8012
AP for bicycle = 0.8018
AP for bird = 0.7385
AP for boat = 0.6707
AP for bottle = 0.4992
AP for bus = 0.8318
AP for car = 0.8488
AP for cat = 0.8638
AP for chair = 0.6039
AP for cow = 0.8025
AP for diningtable = 0.7461
AP for dog = 0.8248
AP for horse = 0.8496
AP for motorbike = 0.8154
AP for person = 0.7769
AP for pottedplant = 0.4808
AP for sheep = 0.7362
AP for sofa = 0.7739
AP for train = 0.8451
AP for tvmonitor = 0.7637
Mean AP = 0.7537
~~~~~~~~
Results:
0.801
0.802
0.739
0.671
0.499
0.832
0.849
0.864
0.604
0.802
0.746
0.825
0.850
0.815
0.777
0.481
0.736
0.774
0.845
0.764
0.754
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
--------------------------------------------------------------

************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************
************************************************************************************************************************************************************************************************