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Inferencing accuracy comparison

Contributors banum-netapp

For this validation, we performed inferencing for an image detection use case by using a set of raw images. We then performed the same inferencing task on the same set of images with Protopia obfuscation added before inferencing. We repeated the task using different values of ALPHA for the Protopia obfuscation component. In the context of Protopia obfuscation, the ALPHA value represents the amount of obfuscation that is applied, with a higher ALPHA value representing a higher level of obfuscation. We then compared inferencing accuracy across these different runs.

The following two tables provide details about our use case and outline the results.

Protopia works directly with customers to determine the appropriate ALPHA value for a specific use case.

Component Details

Model

FaceBoxes (PyTorch) -

Dataset

FDDB dataset

Protopia obfuscation ALPHA Accuracy

No

N/A

0.9337148153739079

Yes

0.05

0.9028766627325002

Yes

0.1

0.9024301009661478

Yes

0.2

0.9081836283186224

Yes

0.4

0.9073066107482036

Yes

0.6

0.8847816568680239

Yes

0.8

0.8841195749171925

Yes

0.9

0.8455427675252052

Yes

0.95

0.8455427675252052