Binary mask classification
According to the model card, the model detects face-mask presence for health monitoring, access control, and compliance use.
Open Source Model Profile · prithivMLmods
Face-Mask-Detection
Face-Mask-Detection is a 92.9M-parameter SigLIP2 binary classifier from prithivMLmods. Its model card documents face-mask detection with a publisher-reported 0.9614 accuracy.
- Publisher
- prithivMLmods
- Task
- image-classification
- Model type
- siglip
- License
- apache-2.0
- Library
- transformers
- Publication status
- Accepted · not indexed
Model overview
Face-Mask-Detection is published by prithivMLmods as a binary image-classification model. The captured configuration identifies SiglipForImageClassification, and Safetensors metadata reports about 92.9M parameters. According to the model card, it fine-tunes google/siglip2-base-patch16-224 to detect face-mask presence.
Recorded capabilities
SigLIP2 base lineage
Hub tags and the card's model tree identify google/siglip2-base-patch16-224 as the base model.
Published classification report
The model card publishes precision, recall, and F1 figures with 0.9614 accuracy across both mask classes.
Use cases in the source record
- Face-mask compliance checks for public-health monitoring, access control, and workplace enforcement, as documented in the card.
- Gradio-based image-upload experiments that return Face_Mask Found or Face_Mask Not_Found probabilities.
Limitations and unknowns
- No independent evaluation results were extracted; accuracy figures are publisher-reported.
- Provider state is historical snapshot data, not independently refreshed current availability.
- Training-dataset detail comes from the publisher card reference to DamarJati/Face-Mask-Detection and has not been independently verified by Ethen.
Source and provenance
Source: prithivMLmods/Face-Mask-Detection
Captured: Unknown. Processed: 2026-09-07T19:35:29.022434+00:00.
Face-Mask-Detection Face-Mask-Detection is a binary image classification model based on google/siglip2-base-patch16-224 , trained to detect whether a person is wearing a face mask or not . This model can be used in public health monitoring , access control systems , and workplace compliance enforcement . Classification Report: precision recall f1-score support Face_Mask Found 0.9662 0.9561 0.9611 5883 Face_Mask Not_Found 0.9568 0.9667 0.9617 5909 accuracy 0.9614 11792 macro avg 0.9615 0.9614 0.9614 11792 weighted avg 0.9615 0.9614 0.9614 11792 Label Classes The model distinguishes between the following face mask statuses: 0: Face_Ma…
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