Detailled semantic labeling (2D) result


Name S. Piramanayagam et al.
Affiliation RIT, USA
Abbreviation RIT2
Strategy (u)nsupervised, (s)upervised, (h)ybrid s


Overall statistics, reference set: full_reference


Number of non processed tiles by this participant: 0
↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.905
0.014
0.043
0.015
0.003
0.020
building
0.019
0.953
0.012
0.003
0.001
0.013
low_veg
0.044
0.009
0.879
0.054
0.000
0.015
tree
0.042
0.006
0.149
0.796
0.002
0.004
car
0.070
0.005
0.004
0.015
0.888
0.018
clutter
0.250
0.103
0.175
0.020
0.011
0.441
Precision/Correctness
0.894
0.950
0.788
0.884
0.898
0.599
Recall/Completeness
0.905
0.953
0.879
0.796
0.888
0.441
F1
0.899
0.951
0.831
0.838
0.893
0.508

Overall accuracy 0.871

Overall statistics, reference set: no_boundary


Number of non processed tiles by this participant: 0
↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.925
0.010
0.036
0.010
0.000
0.019
building
0.016
0.961
0.009
0.002
0.000
0.011
low_veg
0.032
0.005
0.904
0.046
0.000
0.013
tree
0.033
0.005
0.133
0.824
0.002
0.004
car
0.013
0.006
0.002
0.009
0.952
0.018
clutter
0.246
0.088
0.163
0.016
0.011
0.476
Precision/Correctness
0.916
0.965
0.812
0.910
0.938
0.619
Recall/Completeness
0.925
0.961
0.904
0.824
0.952
0.476
F1
0.920
0.963
0.855
0.865
0.945
0.538

Overall accuracy 0.894
=============================================================

Tile top_potsdam_2_13_class.tif, reference set: full_reference


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.8786
0.0168
0.0520
0.0120
0.0024
0.0383
building
0.0200
0.9322
0.0220
0.0054
0.0001
0.0203
low_veg
0.0258
0.0071
0.8816
0.0425
0.0001
0.0429
tree
0.0403
0.0102
0.1436
0.7960
0.0013
0.0085
car
0.0861
0.0062
0.0041
0.0087
0.8540
0.0408
clutter
0.1337
0.1583
0.1397
0.0273
0.0248
0.5161
Precision/Correctness
0.898
0.936
0.835
0.914
0.875
0.258
Recall/Completeness
0.879
0.932
0.882
0.796
0.854
0.516
F1
0.888
0.934
0.857
0.851
0.864
0.344

Overall accuracy 0.863

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_2_13_class.tif, reference set: no_boundary


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9021
0.0116
0.0430
0.0072
0.0002
0.0358
building
0.0167
0.9429
0.0178
0.0043
0.0001
0.0182
low_veg
0.0177
0.0033
0.9047
0.0312
0.0000
0.0430
tree
0.0319
0.0087
0.1244
0.8266
0.0009
0.0075
car
0.0321
0.0065
0.0018
0.0034
0.9104
0.0458
clutter
0.1016
0.1587
0.1024
0.0192
0.0300
0.5882
Precision/Correctness
0.926
0.957
0.860
0.940
0.923
0.234
Recall/Completeness
0.902
0.943
0.905
0.827
0.910
0.588
F1
0.914
0.950
0.882
0.880
0.917
0.335

Overall accuracy 0.889

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_2_14_class.tif, reference set: full_reference


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.8789
0.0063
0.0914
0.0132
0.0018
0.0083
building
0.0086
0.9692
0.0081
0.0051
0.0000
0.0090
low_veg
0.0130
0.0042
0.9436
0.0347
0.0000
0.0045
tree
0.0169
0.0030
0.1922
0.7856
0.0007
0.0016
car
0.0639
0.0056
0.0085
0.0125
0.8981
0.0116
clutter
0.1034
0.2423
0.1914
0.0536
0.0081
0.4013
Precision/Correctness
0.914
0.935
0.823
0.943
0.904
0.247
Recall/Completeness
0.879
0.969
0.944
0.786
0.898
0.401
F1
0.896
0.952
0.879
0.857
0.901
0.306

Overall accuracy 0.877

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_2_14_class.tif, reference set: no_boundary


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9080
0.0032
0.0732
0.0082
0.0002
0.0071
building
0.0063
0.9804
0.0031
0.0029
0.0000
0.0073
low_veg
0.0082
0.0024
0.9577
0.0276
0.0000
0.0041
tree
0.0132
0.0022
0.1755
0.8071
0.0005
0.0014
car
0.0106
0.0051
0.0084
0.0068
0.9557
0.0133
clutter
0.0730
0.2752
0.1468
0.0561
0.0089
0.4400
Precision/Correctness
0.939
0.958
0.842
0.957
0.951
0.227
Recall/Completeness
0.908
0.980
0.958
0.807
0.956
0.440
F1
0.923
0.969
0.896
0.876
0.953
0.300

Overall accuracy 0.896

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_3_13_class.tif, reference set: full_reference


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.8754
0.0166
0.0550
0.0183
0.0037
0.0309
building
0.0138
0.9636
0.0069
0.0038
0.0000
0.0118
low_veg
0.0548
0.0179
0.8657
0.0488
0.0001
0.0126
tree
0.0341
0.0067
0.1224
0.8311
0.0021
0.0035
car
0.0704
0.0044
0.0021
0.0196
0.8904
0.0131
clutter
0.1930
0.1298
0.2631
0.0285
0.0086
0.3771
Precision/Correctness
0.881
0.948
0.800
0.915
0.903
0.380
Recall/Completeness
0.875
0.964
0.866
0.831
0.890
0.377
F1
0.878
0.956
0.831
0.871
0.896
0.378

Overall accuracy 0.873

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_3_13_class.tif, reference set: no_boundary


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9030
0.0104
0.0451
0.0117
0.0003
0.0295
building
0.0111
0.9724
0.0038
0.0027
0.0000
0.0100
low_veg
0.0433
0.0098
0.8982
0.0390
0.0000
0.0096
tree
0.0261
0.0054
0.1043
0.8597
0.0016
0.0029
car
0.0143
0.0049
0.0012
0.0112
0.9565
0.0119
clutter
0.1798
0.1203
0.2368
0.0222
0.0100
0.4309
Precision/Correctness
0.910
0.968
0.830
0.940
0.954
0.380
Recall/Completeness
0.903
0.972
0.898
0.860
0.956
0.431
F1
0.906
0.970
0.863
0.898
0.955
0.404

Overall accuracy 0.902

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_3_14_class.tif, reference set: full_reference


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.8633
0.0171
0.0771
0.0192
0.0039
0.0194
building
0.0144
0.9718
0.0063
0.0028
0.0001
0.0046
low_veg
0.0299
0.0083
0.9044
0.0478
0.0001
0.0095
tree
0.0264
0.0048
0.2043
0.7582
0.0016
0.0048
car
0.0652
0.0029
0.0024
0.0250
0.8626
0.0418
clutter
0.1844
0.1479
0.1964
0.0388
0.0047
0.4279
Precision/Correctness
0.881
0.949
0.763
0.911
0.881
0.579
Recall/Completeness
0.863
0.972
0.904
0.758
0.863
0.428
F1
0.872
0.960
0.828
0.828
0.871
0.492

Overall accuracy 0.858

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_3_14_class.tif, reference set: no_boundary


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.8930
0.0110
0.0653
0.0127
0.0007
0.0172
building
0.0125
0.9791
0.0031
0.0018
0.0000
0.0034
low_veg
0.0196
0.0034
0.9318
0.0376
0.0000
0.0075
tree
0.0213
0.0039
0.1882
0.7812
0.0013
0.0041
car
0.0125
0.0028
0.0006
0.0156
0.9219
0.0466
clutter
0.1739
0.1374
0.1675
0.0332
0.0052
0.4828
Precision/Correctness
0.910
0.967
0.785
0.936
0.932
0.609
Recall/Completeness
0.893
0.979
0.932
0.781
0.922
0.483
F1
0.901
0.973
0.852
0.852
0.927
0.539

Overall accuracy 0.884

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_4_13_class.tif, reference set: full_reference


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9277
0.0087
0.0343
0.0200
0.0026
0.0067
building
0.0150
0.9680
0.0072
0.0035
0.0001
0.0062
low_veg
0.0571
0.0072
0.8320
0.0960
0.0002
0.0075
tree
0.0394
0.0039
0.0633
0.8880
0.0023
0.0029
car
0.0655
0.0019
0.0025
0.0215
0.9030
0.0056
clutter
0.4612
0.1027
0.1848
0.0522
0.0144
0.1847
Precision/Correctness
0.846
0.966
0.783
0.819
0.902
0.688
Recall/Completeness
0.928
0.968
0.832
0.888
0.903
0.185
F1
0.885
0.967
0.807
0.852
0.903
0.291

Overall accuracy 0.871

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_4_13_class.tif, reference set: no_boundary


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9469
0.0053
0.0281
0.0138
0.0006
0.0053
building
0.0100
0.9791
0.0035
0.0024
0.0001
0.0051
low_veg
0.0426
0.0025
0.8636
0.0856
0.0000
0.0056
tree
0.0263
0.0024
0.0503
0.9171
0.0017
0.0023
car
0.0088
0.0015
0.0008
0.0124
0.9717
0.0047
clutter
0.4772
0.0875
0.1769
0.0445
0.0156
0.1982
Precision/Correctness
0.873
0.978
0.816
0.854
0.927
0.727
Recall/Completeness
0.947
0.979
0.864
0.917
0.972
0.198
F1
0.908
0.979
0.839
0.885
0.949
0.312

Overall accuracy 0.898

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_4_14_class.tif, reference set: full_reference


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.8668
0.0189
0.0627
0.0130
0.0043
0.0343
building
0.0171
0.9652
0.0055
0.0038
0.0001
0.0081
low_veg
0.0743
0.0139
0.8249
0.0543
0.0005
0.0321
tree
0.0392
0.0057
0.1654
0.7792
0.0025
0.0080
car
0.0535
0.0061
0.0075
0.0228
0.8889
0.0212
clutter
0.3633
0.0376
0.1391
0.0108
0.0021
0.4472
Precision/Correctness
0.772
0.938
0.753
0.890
0.913
0.692
Recall/Completeness
0.867
0.965
0.825
0.779
0.889
0.447
F1
0.817
0.951
0.787
0.831
0.901
0.543

Overall accuracy 0.819

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_4_14_class.tif, reference set: no_boundary


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.8851
0.0143
0.0581
0.0082
0.0005
0.0337
building
0.0141
0.9725
0.0036
0.0028
0.0001
0.0068
low_veg
0.0601
0.0084
0.8534
0.0469
0.0002
0.0310
tree
0.0304
0.0042
0.1472
0.8094
0.0019
0.0068
car
0.0101
0.0054
0.0080
0.0167
0.9382
0.0216
clutter
0.3719
0.0338
0.1243
0.0081
0.0015
0.4602
Precision/Correctness
0.788
0.955
0.774
0.915
0.960
0.714
Recall/Completeness
0.885
0.973
0.853
0.809
0.938
0.460
F1
0.834
0.963
0.811
0.859
0.949
0.560

Overall accuracy 0.840

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_4_15_class.tif, reference set: full_reference


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9053
0.0179
0.0575
0.0054
0.0029
0.0110
building
0.0111
0.9703
0.0092
0.0013
0.0004
0.0077
low_veg
0.0675
0.0227
0.8700
0.0276
0.0005
0.0118
tree
0.0850
0.0095
0.1754
0.7164
0.0063
0.0074
car
0.0782
0.0161
0.0030
0.0093
0.8743
0.0192
clutter
0.2208
0.2339
0.2241
0.0106
0.0078
0.3028
Precision/Correctness
0.902
0.943
0.734
0.926
0.904
0.480
Recall/Completeness
0.905
0.970
0.870
0.716
0.874
0.303
F1
0.904
0.956
0.797
0.808
0.889
0.371

Overall accuracy 0.877

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_4_15_class.tif, reference set: no_boundary


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9219
0.0122
0.0530
0.0033
0.0004
0.0093
building
0.0081
0.9773
0.0068
0.0009
0.0004
0.0065
low_veg
0.0450
0.0148
0.9090
0.0216
0.0001
0.0095
tree
0.0684
0.0079
0.1543
0.7578
0.0049
0.0066
car
0.0109
0.0177
0.0004
0.0041
0.9464
0.0206
clutter
0.2071
0.2382
0.2273
0.0075
0.0059
0.3140
Precision/Correctness
0.931
0.959
0.758
0.950
0.946
0.483
Recall/Completeness
0.922
0.977
0.909
0.758
0.946
0.314
F1
0.926
0.968
0.827
0.843
0.946
0.381

Overall accuracy 0.903

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_5_13_class.tif, reference set: full_reference


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9205
0.0125
0.0348
0.0191
0.0022
0.0108
building
0.0142
0.9704
0.0063
0.0027
0.0000
0.0064
low_veg
0.0694
0.0112
0.8393
0.0687
0.0001
0.0113
tree
0.0575
0.0057
0.1219
0.8091
0.0022
0.0036
car
0.0856
0.0015
0.0007
0.0076
0.8866
0.0180
clutter
0.2193
0.2249
0.1466
0.0177
0.0503
0.3413
Precision/Correctness
0.901
0.951
0.829
0.826
0.895
0.563
Recall/Completeness
0.920
0.970
0.839
0.809
0.887
0.341
F1
0.911
0.961
0.834
0.818
0.891
0.425

Overall accuracy 0.886

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_5_13_class.tif, reference set: no_boundary


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9396
0.0071
0.0305
0.0141
0.0002
0.0084
building
0.0106
0.9770
0.0048
0.0020
0.0000
0.0056
low_veg
0.0626
0.0063
0.8616
0.0603
0.0000
0.0092
tree
0.0414
0.0041
0.1078
0.8418
0.0017
0.0033
car
0.0170
0.0014
0.0000
0.0045
0.9588
0.0183
clutter
0.1888
0.2099
0.1382
0.0157
0.0619
0.3855
Precision/Correctness
0.925
0.969
0.854
0.855
0.919
0.579
Recall/Completeness
0.940
0.977
0.862
0.842
0.959
0.385
F1
0.932
0.973
0.858
0.848
0.938
0.463

Overall accuracy 0.910

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_5_14_class.tif, reference set: full_reference


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9247
0.0069
0.0294
0.0225
0.0020
0.0144
building
0.0172
0.9691
0.0067
0.0012
0.0002
0.0056
low_veg
0.0586
0.0074
0.8495
0.0720
0.0002
0.0123
tree
0.0546
0.0058
0.1064
0.8238
0.0034
0.0060
car
0.0838
0.0018
0.0117
0.0180
0.8620
0.0227
clutter
0.1738
0.1787
0.1905
0.0331
0.0061
0.4178
Precision/Correctness
0.860
0.932
0.805
0.857
0.910
0.769
Recall/Completeness
0.925
0.969
0.850
0.824
0.862
0.418
F1
0.891
0.950
0.827
0.840
0.885
0.541

Overall accuracy 0.863

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_5_14_class.tif, reference set: no_boundary


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9437
0.0039
0.0227
0.0167
0.0004
0.0127
building
0.0154
0.9742
0.0044
0.0008
0.0001
0.0050
low_veg
0.0429
0.0044
0.8761
0.0665
0.0000
0.0100
tree
0.0436
0.0047
0.0967
0.8473
0.0026
0.0051
car
0.0135
0.0017
0.0106
0.0097
0.9408
0.0237
clutter
0.1583
0.1542
0.1838
0.0307
0.0062
0.4668
Precision/Correctness
0.889
0.951
0.828
0.881
0.938
0.797
Recall/Completeness
0.944
0.974
0.876
0.847
0.941
0.467
F1
0.915
0.962
0.852
0.864
0.939
0.589

Overall accuracy 0.888

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_5_15_class.tif, reference set: full_reference


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.8728
0.0140
0.0486
0.0168
0.0020
0.0458
building
0.0214
0.9381
0.0158
0.0049
0.0004
0.0194
low_veg
0.0497
0.0052
0.8310
0.0974
0.0001
0.0165
tree
0.0420
0.0042
0.1078
0.8410
0.0023
0.0028
car
0.1017
0.0054
0.0023
0.0138
0.8609
0.0159
clutter
0.2518
0.1480
0.1243
0.0149
0.0081
0.4530
Precision/Correctness
0.903
0.930
0.727
0.808
0.929
0.548
Recall/Completeness
0.873
0.938
0.831
0.841
0.861
0.453
F1
0.887
0.934
0.776
0.824
0.894
0.496

Overall accuracy 0.850

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_5_15_class.tif, reference set: no_boundary


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.8866
0.0104
0.0439
0.0125
0.0006
0.0461
building
0.0175
0.9474
0.0139
0.0038
0.0003
0.0172
low_veg
0.0312
0.0020
0.8591
0.0914
0.0000
0.0162
tree
0.0313
0.0026
0.0953
0.8667
0.0017
0.0024
car
0.0258
0.0047
0.0002
0.0110
0.9423
0.0160
clutter
0.2498
0.1211
0.1119
0.0123
0.0082
0.4968
Precision/Correctness
0.924
0.950
0.749
0.837
0.951
0.557
Recall/Completeness
0.887
0.947
0.859
0.867
0.942
0.497
F1
0.905
0.949
0.800
0.852
0.947
0.525

Overall accuracy 0.872

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_6_13_class.tif, reference set: full_reference


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9225
0.0224
0.0289
0.0137
0.0019
0.0105
building
0.0378
0.9355
0.0189
0.0011
0.0016
0.0050
low_veg
0.0201
0.0041
0.9437
0.0292
0.0000
0.0030
tree
0.0793
0.0034
0.1067
0.8079
0.0009
0.0019
car
0.0611
0.0042
0.0005
0.0049
0.9106
0.0186
clutter
0.2578
0.0475
0.3736
0.0216
0.0090
0.2906
Precision/Correctness
0.922
0.954
0.862
0.882
0.888
0.485
Recall/Completeness
0.923
0.935
0.944
0.808
0.911
0.291
F1
0.922
0.945
0.901
0.843
0.899
0.363

Overall accuracy 0.904

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_6_13_class.tif, reference set: no_boundary


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9386
0.0199
0.0236
0.0086
0.0003
0.0089
building
0.0340
0.9455
0.0144
0.0006
0.0014
0.0040
low_veg
0.0112
0.0018
0.9604
0.0243
0.0000
0.0022
tree
0.0611
0.0022
0.0945
0.8401
0.0005
0.0015
car
0.0098
0.0053
0.0002
0.0028
0.9652
0.0168
clutter
0.2456
0.0471
0.3903
0.0203
0.0083
0.2883
Precision/Correctness
0.940
0.963
0.881
0.911
0.933
0.501
Recall/Completeness
0.939
0.945
0.960
0.840
0.965
0.288
F1
0.939
0.954
0.919
0.874
0.949
0.366

Overall accuracy 0.923

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_6_14_class.tif, reference set: full_reference


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9453
0.0054
0.0278
0.0083
0.0049
0.0082
building
0.0408
0.9295
0.0083
0.0012
0.0003
0.0199
low_veg
0.0521
0.0067
0.8830
0.0502
0.0005
0.0075
tree
0.0618
0.0083
0.1053
0.8182
0.0050
0.0013
car
0.0517
0.0024
0.0038
0.0124
0.9180
0.0117
clutter
0.3166
0.0831
0.2247
0.0208
0.0231
0.3316
Precision/Correctness
0.913
0.979
0.826
0.864
0.903
0.415
Recall/Completeness
0.945
0.930
0.883
0.818
0.918
0.332
F1
0.929
0.954
0.853
0.840
0.910
0.369

Overall accuracy 0.904

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_6_14_class.tif, reference set: no_boundary


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9613
0.0025
0.0227
0.0056
0.0004
0.0074
building
0.0362
0.9390
0.0049
0.0007
0.0002
0.0190
low_veg
0.0358
0.0035
0.9112
0.0439
0.0001
0.0055
tree
0.0494
0.0069
0.0914
0.8472
0.0039
0.0012
car
0.0051
0.0012
0.0023
0.0078
0.9719
0.0116
clutter
0.3071
0.0892
0.2145
0.0161
0.0222
0.3510
Precision/Correctness
0.931
0.986
0.852
0.894
0.958
0.419
Recall/Completeness
0.961
0.939
0.911
0.847
0.972
0.351
F1
0.946
0.962
0.880
0.870
0.965
0.382

Overall accuracy 0.924

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_6_15_class.tif, reference set: full_reference


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9163
0.0074
0.0406
0.0078
0.0049
0.0229
building
0.0123
0.9311
0.0414
0.0013
0.0032
0.0107
low_veg
0.0537
0.0048
0.8883
0.0375
0.0010
0.0147
tree
0.0523
0.0062
0.1943
0.7376
0.0045
0.0051
car
0.0593
0.0015
0.0039
0.0094
0.9144
0.0114
clutter
0.1378
0.0341
0.2358
0.0065
0.0108
0.5751
Precision/Correctness
0.923
0.970
0.655
0.924
0.872
0.704
Recall/Completeness
0.916
0.931
0.888
0.738
0.914
0.575
F1
0.919
0.950
0.754
0.820
0.893
0.633

Overall accuracy 0.867

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_6_15_class.tif, reference set: no_boundary


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9349
0.0050
0.0330
0.0048
0.0004
0.0218
building
0.0075
0.9405
0.0386
0.0007
0.0031
0.0095
low_veg
0.0367
0.0027
0.9171
0.0302
0.0001
0.0131
tree
0.0428
0.0048
0.1762
0.7683
0.0035
0.0044
car
0.0092
0.0013
0.0005
0.0052
0.9724
0.0115
clutter
0.1296
0.0332
0.2289
0.0050
0.0097
0.5935
Precision/Correctness
0.943
0.978
0.671
0.947
0.922
0.725
Recall/Completeness
0.935
0.941
0.917
0.768
0.972
0.594
F1
0.939
0.959
0.775
0.848
0.947
0.653

Overall accuracy 0.889

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_7_13_class.tif, reference set: full_reference


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9196
0.0181
0.0175
0.0217
0.0021
0.0211
building
0.0189
0.9280
0.0051
0.0019
0.0004
0.0457
low_veg
0.0464
0.0097
0.8033
0.1325
0.0002
0.0079
tree
0.0360
0.0097
0.1372
0.8150
0.0006
0.0015
car
0.0441
0.0224
0.0008
0.0309
0.8826
0.0192
clutter
0.1738
0.0143
0.1041
0.0020
0.0076
0.6982
Precision/Correctness
0.942
0.944
0.731
0.716
0.866
0.743
Recall/Completeness
0.920
0.928
0.803
0.815
0.883
0.698
F1
0.931
0.936
0.765
0.762
0.874
0.720

Overall accuracy 0.881

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image


=============================================================

Tile top_potsdam_7_13_class.tif, reference set: no_boundary


↓ predicted || reference →
imp_surf
building
low_veg
tree
car
clutter
imp_surf
0.9344
0.0150
0.0147
0.0152
0.0005
0.0203
building
0.0161
0.9336
0.0040
0.0012
0.0004
0.0447
low_veg
0.0340
0.0063
0.8275
0.1251
0.0001
0.0071
tree
0.0263
0.0078
0.1293
0.8348
0.0004
0.0013
car
0.0044
0.0290
0.0001
0.0208
0.9274
0.0182
clutter
0.1662
0.0129
0.1027
0.0014
0.0069
0.7098
Precision/Correctness
0.951
0.955
0.745
0.751
0.910
0.753
Recall/Completeness
0.934
0.934
0.828
0.835
0.927
0.710
F1
0.942
0.944
0.784
0.791
0.918
0.731

Overall accuracy 0.896

Red/green image, indicating wrongly classified pixels


Original, resized true ortho image for better comparison


Classified image