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how to evaluate multi-class multi-object 2D-tracking task on custom dataset

Open upsx opened this issue 3 years ago • 3 comments

i try to use run_mot_challenge.py tool to evaluate my tracker on my custom dataset. Before evalutation, i have change default_dataset_config['CLASS_TO_EVAL'], self.valid_classes, self.class_name_to_class_id, distractor_class_name etc in mot_challenge_2d_box.py. But the output MOTA is negative, and i dont know how to solve it. Can you help me?thks

upsx avatar Oct 26 '21 11:10 upsx

顶,同求

Jason-lzc avatar Nov 10 '21 08:11 Jason-lzc

Also interested please.

orilifs avatar Dec 23 '21 10:12 orilifs

Negative MOTA does not necessarily indicate a problem with the evaluation. MOTA is negative when FN + FP > GT, i.e. when FP > GT - FN = TP (described in the HOTA paper https://arxiv.org/abs/2009.07736; "MOTA scores can be negative and are unbounded."). Check whether CLR_TP, CLR_FN, CLR_FP seem reasonable.

jvlmdr avatar May 31 '22 02:05 jvlmdr