pterhoer/ExplainableFaceImageQuality
Pixel-Level Face Image Quality Assessment for Explainable Face Recognition
This project helps anyone working with face recognition systems understand why a particular face image might be considered low quality. You provide a face image, and it generates a map highlighting which pixels contribute most to its quality for recognition. This helps biometrics experts, security system operators, or identity verification professionals pinpoint issues and improve image capture.
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Use this if you need to explain to a human why a face image isn't suitable for a face recognition system, or if you want guidance on how to improve the quality of a specific face image.
Not ideal if you need a general face recognition system or if you are not interested in the 'why' behind image quality scores.
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62
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Language
Python
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Last pushed
Dec 18, 2024
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