Comments (6)
Sorry for the late response! The calculation is not necessarily wrong, just that it seems to make more sense to scale the cosine distance metric to have a range of [0,1] since most (if not all) of the other metrics like the jaccard distance have the same range. Since the distance can be a weighted combination of all the metrics where the weights sum up to 1 (judging by examples.h), it makes the most sense to me if all the metrics have the same range of [0,1].
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Hi!
Thnx for describing this bug. I'll try to use some modern re-id architecture without OpenVINO
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Thank you so much!
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Sorry for the long answer. I have added support one model, you can see changes here: https://github.com/Smorodov/Multitarget-tracker/pull/430/files
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Hi, thank you so much for taking the time to make the changes. It works well for me. However, I noticed that your calculation for the cosine distance is now 1 - sim
(where sim is the cosine similarity), instead of the original 0.5 * (1-sim)
. May I know the reasoning behind this? The original calculation seems more suitable to me since it scales the distance to a range of [0,1], while the new calculation has a range of [0,2].
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Hi!
Thnx for remark!
I founded it here: https://github.com/bitzy/DeepSort/blob/db8b64e594c97493a0c289a7ce22fa69530b9075/src/matching/nn_matching.cpp#L158
And in some another places. Do you think that it wrong?
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