facial age detection facial age detection is a vision language encoder model fine tuned from google/siglip2 base patch16 512 for multi class image classification . It is trained to detect and classify human faces into age groups ranging from early childhood to elderly adults. The model uses the SiglipForImageClassification architecture. \[!note] SigLIP 2: Multilingual Vision Language Encoders with Improved Semantic Understanding, Localization, and Dense Features https://arxiv.org/pdf/2502.14786 Label Space: 8 Classes Install Dependencies Inference Code Intended Use facial age detection is designed for: Demographic Analytics – Estimate age distributions in image datasets for research and commercial analysis. Access Control & Verification – Enforce age based access in digital or physical environments. Retail & Marketing – Understand customer demographics in retail spaces through camera based analytics. Surveillance & Security – Enhance people classification systems by integrating age detection. Human Computer Interaction – Adapt experiences and interfaces based on user age.
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