A Gaussian Blur test was performed on
poolformer_s36, in which
a 60% failure rate was observed.
In at least one case, the model's prediction changed 0.97. This caused the label to change from waffle iron to chocolate sauce, chocolate syrup.
This test measures the robustness of the model to Gaussian Blur transformations. It does this by taking a sample input, blurring the image, and measuring the behavior of the model on the transformed input.
Production inputs can have unusual variations amongst many different dimensions, ranging from lighting changes to sensor errors to compression artifacts. It is important that the models are robust to the introduction of such variations.
This report was automatically generated by the scanning engine
rime-0.21.0rc4.post195+git.2a88076b.d on 2023-01-07 04:40.