vpocc-semantickitti / test_log.txt
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========================== Arguments ==========================
dataset: /tmp/codalab/tmp9okiGc/run/input/ref
predictions: /tmp/codalab/tmp9okiGc/run/input/res
datacfg: /tmp/codalab/tmp9okiGc/run/program/semantic-kitti.yaml
split: test
output: /tmp/codalab/tmp9okiGc/run/output
===============================================================
[IOU EVAL] IGNORE: []
[IOU EVAL] INCLUDE: [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19]
Evaluating: 10% 20% 30% 40% 50% 60% 70% 80% 90% Done ๐ŸŽ‰.
========================== RESULTS ==========================
Validation set:
IoU avg 0.161
IoU class 1 [car] = 0.253
IoU class 2 [bicycle] = 0.020
IoU class 3 [motorcycle] = 0.034
IoU class 4 [truck] = 0.061
IoU class 5 [other-vehicle] = 0.072
IoU class 6 [person] = 0.023
IoU class 7 [bicyclist] = 0.029
IoU class 8 [motorcyclist] = 0.016
IoU class 9 [road] = 0.589
IoU class 10 [parking] = 0.302
IoU class 11 [sidewalk] = 0.326
IoU class 12 [other-ground] = 0.111
IoU class 13 [building] = 0.274
IoU class 14 [fence] = 0.188
IoU class 15 [vegetation] = 0.269
IoU class 16 [trunk] = 0.093
IoU class 17 [terrain] = 0.270
IoU class 18 [pole] = 0.068
IoU class 19 [traffic-sign] = 0.069
Precision = 63.26
Recall = 60.15
IoU Cmpltn = 44.58
mIoU SSC = 16.15