Severe sensitivity to Gaussian Blur

0% found this helpful

Vulnerability Info

Vulnerability Typeperformance
CVE Number
Created Date2023/01/07
Reported By@robustintelligence

    Affected Versions

    @1d740b215d07f480fa51efa16df83a63d5f6acf208 April 2022



    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.

    Test Information

    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.

    Why is this important?

    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.

    Model Information

    • Model name: poolformer_s36
    • Model package URL: pkg:huggingface/sail/poolformer_s36@1d740b215d07f480fa51efa16df83a63d5f6acf2
    • Macro F1 score on reference / evaluation: 0.90 / 0.80
    • Multiclass accuracy on reference / evaluation: 0.90 / 0.80
    • Multiclass AUC on reference / evaluation: 1.00 / 1.00
    • Macro Precision on reference / evaluation: 0.92 / 0.82
    • Macro Recall on reference / evaluation: 0.90 / 0.80

    This report was automatically generated by the scanning engine rime-0.21.0rc4.post195+git.2a88076b.d on 2023-01-07 04:40.

    contributor image
    Robust Intelligence
    Helpfulness score: 5