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JonathonLuiten avatar JonathonLuiten commented on September 3, 2024 1

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.

test.zip

My analysis was also that:

  1. By default the preprocessing script Hungarian.m gave an incorrect solution to the linear assignment problem here.
  2. By replacing Inf with very large numbers it got the correct solution again.
  3. By replacing the matlab hungarian code with the c mex code from the repo it gave the correct solution also.
  4. 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).

from motchallengeevalkit.

JonathonLuiten avatar JonathonLuiten commented on September 3, 2024 1

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.

from motchallengeevalkit.

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