Comments (2)
Hey @hongin13, does this statement in Readme.md resolve your question?
Metric MOTP seems to be off. To convert compute (1 - MOTP) * 100. MOTChallenge benchmarks compute MOTP as percentage, while py-motmetrics sticks to the original definition of average distance over number of assigned objects [1].
from py-motmetrics.
Can this statement be interpreted as "(1 - motp) is the appropriate motp calculation result"?
from py-motmetrics.
Related Issues (20)
- MOTP with euclidean distance metric gives mean squared distance. HOT 1
- how to solve this problem? HOT 1
- eval_motchallenge.py: error: the following arguments are required: groundtruths, tests
- Total number of objects calculation HOT 3
- Do we need to keep original detection order? HOT 5
- About OSPA/GOSPA HOT 2
- Wrong results HOT 1
- Everything gets 0 / NaN if confidence is -1 in motChallenge format HOT 1
- AttributeError for `np.bool` in Numpy `1.24.0` HOT 5
- How to calculate IDF1 metric for multi-camera multi-target(MCMT,MTMC) tracking? HOT 1
- MOTP Metric
- Precision-Recall Curve
- Why idp and idr samein result?
- Custom dataset example in `README` gives worse results than `motmetrics.apps.eval_motchallenge`
- A BUG caused by pandas.Index.map
- can idp and idr be more than 1? HOT 1
- Person exits and re-enters
- mostly_tracked(MT) HOT 2
- Error with Default Option "ana" When Computing Metrics
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