6.png

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

download.png


Label Classes

The model distinguishes between the following face mask statuses:

0: Face_Mask Found  
1: Face_Mask Not_Found

Installation

pip install transformers torch pillow gradio

Example Inference Code

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
Downloads last month
2
Safetensors
Model size
92.9M params
Tensor type
F32
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for prithivMLmods/Face-Mask-Detection

Finetuned
(90)
this model

Dataset used to train prithivMLmods/Face-Mask-Detection

Collection including prithivMLmods/Face-Mask-Detection