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---
license: apache-2.0
datasets:
- DamarJati/Face-Mask-Detection
language:
- en
base_model:
- google/siglip2-base-patch16-224
pipeline_tag: image-classification
library_name: transformers
tags:
- Face-Mask-Detection
- SigLIP2
---
# **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**.
```py
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_Mask Found
1: Face_Mask Not_Found
```
---
## **Installation**
```bash
pip install transformers torch pillow gradio
```
---
## **Example Inference Code**
```python
import gradio as gr
from transformers import AutoImageProcessor, SiglipForImageClassification
from PIL import Image
import torch
# Load model and processor
model_name = "prithivMLmods/Face-Mask-Detection"
model = SiglipForImageClassification.from_pretrained(model_name)
processor = AutoImageProcessor.from_pretrained(model_name)
# ID to label mapping
id2label = {
"0": "Face_Mask Found",
"1": "Face_Mask Not_Found"
}
def detect_face_mask(image):
image = Image.fromarray(image).convert("RGB")
inputs = processor(images=image, return_tensors="pt")
with torch.no_grad():
outputs = model(**inputs)
logits = outputs.logits
probs = torch.nn.functional.softmax(logits, dim=1).squeeze().tolist()
prediction = {id2label[str(i)]: round(probs[i], 3) for i in range(len(probs))}
return prediction
# Gradio Interface
iface = gr.Interface(
fn=detect_face_mask,
inputs=gr.Image(type="numpy"),
outputs=gr.Label(num_top_classes=2, label="Mask Status"),
title="Face-Mask-Detection",
description="Upload an image to check if a person is wearing a face mask or not."
)
if __name__ == "__main__":
iface.launch()
```
---
## **Applications**
* **COVID-19 Compliance Monitoring**
* **Security and Access Control**
* **Automated Surveillance Systems**
* **Health Safety Enforcement in Public Spaces** |