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AI Face Recognition (Gallery)

Build a gallery from labeled faces and recognize faces in a target image

Click to upload files or drag and drop files here

Maximum file size: 200MB Maximum files: 50
Supported formats: image/*

Click to upload file or drag and drop file here

Maximum file size: 30MB Supported formats: image/*

Key Facts

Category
AI Tools
Input Types
file, text, number
Output Type
json
Sample Coverage
4
API Ready
Yes

Overview

This AI-powered tool enables you to build a labeled face gallery from uploaded images and use it to recognize individuals in a target photo. Simply provide reference faces with names, then test against new images for accurate identification.

When to Use

  • •When you need to automatically identify known people in photo collections or batches.
  • •To set up a face verification system for security, access control, or attendance tracking.
  • •For organizing digital assets by tagging faces with labels based on a pre-defined gallery.

How It Works

  • •Upload one or more face images to form the gallery, and optionally add comma-separated labels like names.
  • •Upload a single target image containing faces to be recognized against the gallery.
  • •Adjust the match threshold and minimum confidence settings to control recognition sensitivity.
  • •The tool processes the images and returns JSON results with recognized faces, their labels, and confidence scores.

Use Cases

Automated tagging of faces in photo libraries for digital asset management.
Identity verification in security systems or event check-ins.
Organizing personal or professional photo collections by identifying individuals.

Examples

1. Organizing Event Photos

Event Coordinator
Background
After a large conference, you have hundreds of attendee photos and need to tag them with names for the archive.
Problem
Manually identifying each person in photos is time-consuming and error-prone.
How to Use
Upload attendee headshots as the gallery with labels like 'Jane Smith', then upload group photos as target images.
Example Config
Set threshold to 0.6 and minConfidence to 0.5 for balanced accuracy in varied lighting.
Outcome
The tool returns JSON data with recognized attendees and their locations, speeding up the tagging process.

2. Access Control for Secure Areas

Background
A facility requires face-based verification to grant entry to authorized personnel only.
Problem
Traditional methods like keycards can be compromised or lost.
How to Use
Build a gallery with employee photos and names, then use images from entry cameras as target inputs.
Outcome
The system identifies authorized individuals and logs access attempts, improving security efficiency.

Try with Samples

image, file
Hugging Face Deploy Samples
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title token face
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Hugging Face JavaScript Samples
Hugging Face JavaScript/TypeScript examples using Transformers.js for NLP, computer vision, and multimodal tasks in browser and Node.js
title token face
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SVG Samples
Scalable Vector Graphics (SVG) samples demonstrating various SVG features and techniques
preferred input family image
image
Grafana Advanced Application Samples
Comprehensive Grafana samples covering advanced dashboard design, alerting configurations, data source integrations, and plugin development
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image

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FAQ

What image formats are supported for upload?

Common image formats such as JPEG, PNG, and GIF are accepted.

How many images can I include in the gallery?

You can upload up to 50 images for the gallery.

What does the match threshold setting do?

It controls the strictness of face matching; lower values are more lenient, while higher values require closer matches.

Can the tool recognize multiple faces in one target image?

Yes, it can detect and recognize multiple faces within a single target image.

Is this tool suitable for real-time face recognition?

No, it is designed for batch processing of uploaded images, not real-time video streams.

API Documentation

Request Endpoint

POST /en/api/tools/ai-face-recognition

Request Parameters

Parameter Name Type Required Description
galleryFiles file (Upload required) Yes -
galleryLabels text No -
targetImage file (Upload required) Yes -
threshold number No -
minConfidence number No -

File type parameters need to be uploaded first via POST /upload/ai-face-recognition to get filePath, then pass filePath to the corresponding file field.

Response Format

{
  "key": {...},
  "metadata": {
    "key": "value"
  },
  "error": "Error message (optional)",
  "message": "Notification message (optional)"
}
JSON Data: JSON Data

AI MCP Documentation

Add this tool to your MCP server configuration: 

{
  "mcpServers": {
    "elysiatools-ai-face-recognition": {
      "name": "ai-face-recognition",
      "description": "Build a gallery from labeled faces and recognize faces in a target image",
      "baseUrl": "https://elysiatools.com/mcp/sse?toolId=ai-face-recognition",
      "command": "",
      "args": [],
      "env": {},
      "isActive": true,
      "type": "sse"
    }
  }
}

You can chain multiple tools, e.g.: `https://elysiatools.com/mcp/sse?toolId=png-to-webp,jpg-to-webp,gif-to-webp`, max 20 tools.

Supports URL file links or Base64 encoding for file parameters.

If you encounter any issues, please contact us at [email protected]