kitti-object-eval-python
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After I redivided the data set, i met such a problem
I redivided the KITTI training to train and val, about 7:3. But when i eval the network. I found my result so low. I also see the result txt. I think I get right result. Can someone help me.
2020-12-30 22:48:50,569 INFO total roi bbox recall(thresh=0.100): 8340 / 8588 = 0.971122 2020-12-30 22:48:50,569 INFO total roi bbox recall(thresh=0.300): 8272 / 8588 = 0.963204 2020-12-30 22:48:50,569 INFO total roi bbox recall(thresh=0.500): 8086 / 8588 = 0.941546 2020-12-30 22:48:50,569 INFO total roi bbox recall(thresh=0.700): 6593 / 8588 = 0.767699 2020-12-30 22:48:50,569 INFO total roi bbox recall(thresh=0.900): 132 / 8588 = 0.015370 2020-12-30 22:48:50,569 INFO total bbox recall(thresh=0.100): 8336 / 8588 = 0.970657 2020-12-30 22:48:50,569 INFO total bbox recall(thresh=0.300): 8274 / 8588 = 0.963437 2020-12-30 22:48:50,569 INFO total bbox recall(thresh=0.500): 8159 / 8588 = 0.950047 2020-12-30 22:48:50,569 INFO total bbox recall(thresh=0.700): 7443 / 8588 = 0.866674 2020-12-30 22:48:50,569 INFO total bbox recall(thresh=0.900): 2002 / 8588 = 0.233116 2020-12-30 22:48:50,570 INFO Averate Precision: 2020-12-30 22:49:08,986 INFO Car [email protected], 0.70, 0.70: bbox AP:0.0063, 0.0103, 0.0155 bev AP:0.0023, 0.0031, 0.0034 3d AP:0.0025, 0.0014, 0.0014 aos AP:0.00, 0.01, 0.01 Car [email protected], 0.50, 0.50: bbox AP:0.0063, 0.0103, 0.0155 bev AP:0.0088, 0.0082, 0.0094 3d AP:0.0044, 0.0048, 0.0048 aos AP:0.00, 0.01, 0.01