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Recognition find batched #1351
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Recognition find batched #1351
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serengil
reviewed
Sep 30, 2024
serengil
reviewed
Sep 30, 2024
serengil
reviewed
Sep 30, 2024
serengil
reviewed
Sep 30, 2024
this is a comprehensive PR, need to spend some time on it |
serengil
reviewed
Sep 30, 2024
serengil
reviewed
Sep 30, 2024
serengil
reviewed
Sep 30, 2024
serengil
reviewed
Oct 1, 2024
distances = np.linalg.norm(diff, axis=2) # (M, N) | ||
return distances | ||
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def find_distance_batch( |
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as a future PR, we may consider to move find_distance_batch, find_euclidean_distance_batch and find_cosine_distance_batch to the functions in verification.
LGTM |
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Tickets
#1332
What has been done
With this PR, the
find_batched
method was developed as a batched version of thefind
method. The main difference of that method is using numpy arrays instead ofpd.DataFrame
and using batched distance calculation instead of element-wise distance calculation. Also, the function returns array of array of dicts (wherearray[:]
is source faces andarray[:][:]
is founded faces corresponding to each source face) instead of array of DataFrames.Also, the tests for the
find_batched
method was developed in thetests/test_find_batched.py
.Based on the experiments conducted on large face databases, which include photos with multiple faces, the
find_batched
method achieves a speedup of more than 50% compared to thefind
method.How to test