Comments (2)
As @jvlmdr points out, I also found the same error.
To add to the discussion I upload a 'real world' test case, in which this problem is visible. This is extracted from one frame (I don't remember which timestep sorry) for the LPC_MOT tracker running on the MOT20-05 sequence.
My analysis was also that:
- By default the preprocessing script Hungarian.m gave an incorrect solution to the linear assignment problem here.
- By replacing Inf with very large numbers it got the correct solution again.
- By replacing the matlab hungarian code with the c mex code from the repo it gave the correct solution also.
- Scipy's hungarian solver gives the correct solution.
I also found that simply replacing the matlab hungarian with the mex, or replacing inf with large numbers, resulted in the eval running really slow over whole sequneces for some reason (didn't look further into this).
Also note that, in my analysis, when evaluating MOT17 over 15 different trackers (AGT, GNNMatch, GSM_Tracktor, IA, ISE_MOT17R, Lif_T, Lif_TsimInt, LPC_MOT, MAT, MIFTv2, MPNTrack, SSAT, TracktorCorr, Tracktorv2, UnsupTrack) this resulted in a total difference of 13 FPs (out of approx 500k), 13 FNs (out of approx 1.5 mil) and 2 IDSWs (out of approx 13k) compared to using a non-bugged preprocessing (using scipy).
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Note also that to 3 decimal places this bug does not produce any difference in MOTA / MOTP / MODA etc scores.
P.s. to anyone reading, MOTChallenge is in the process of updating it's evaluation to use the code at (https://github.com/JonathonLuiten/HOTA-metrics) where this bug is fixed.
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Related Issues (17)
- How to customize this code to evaluate MOT metrics on custom datasets? HOT 2
- ground truth for the images in the test folder of MOT16 HOT 1
- 3DZeF or 3DZeF20 HOT 1
- MOT20Det Evaluation Clarification
- MOT 20 Data annotation HOT 5
- HT21 annotation and det eval
- custom data annotation?
- Segmentation GT masks for MOT-17 OR Tracking GT annotations for MOTS
- Pose keypoints annotations for MOTSynth
- open source HOT 1
- Converting MOT20DET to YoloV8 format HOT 2
- MOT20\train\MOT20-01\gt\gt.txt data format not consistent HOT 5
- What does it mean for confidence of detections to be zero in MOT20\train\MOT20-01\det\det.txt? HOT 1
- MinCostMatching headers HOT 1
- MinCostMatching may return incorrect result with infinite edges
- MATLAB evalutation failed
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