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Perf object detection #1098
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gogetron
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Perf object detection #1098
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elisno
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Apr 16, 2024
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Nice work @gogetron!
I have a few suggestions for rank.py.
Thank you for your review, your suggestions are very clear and useful. I have just committed your suggestions. |
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Summary
This PR partially addresses #862
[ ✏️ Write your summary here. ]
A significant improvement comes from vectorizing
_get_iou
,_euc_dis
and_calculate_average_precision
. I searched for all references to the deleted_mod_coordinates
and_get_overlap
but they are not used anywhere else in the code. I assumed it is ok to remove them because they are not part of the public api however let me know if you prefer to deprecate them or keep both versions.For memory I used the memory-profiler library. The code I used for benchmarking is copied below. In addition I sorted the imports in the modified files.
Code Setup
Current version
This PR
Testing
References
Reviewer Notes
I was not sure about which input would be more realistic, I have tried different options but the improvements were similar, however let me know if you want me to test a specific combination of inputs, I tried to use the largest input dataset I could while still being able to run the master %%timeit in about an hour.
I have noticed that the
num_procs
argument in_calculate_ap_per_class
is always set to the default value. Thus, i made a few changes there to ensure that the pool is only created whennum_procs
is higher than 1.After each change I ran the tests and they were catching any minor mistake I made. However once they were passing I ensured with some random input that both versions (master and this PR) still produced the same exact output.