Age Detection API

API ID 10675

Automatically detects a person's estimated age from an image using advanced artificial intelligence and accurate facial recognition.

412 ms avg response

API Documentation

Endpoints

Request

Analyzes an image sent via URL and returns the estimated age of the person.

Endpoint ID: 20229
POST https://pr213-testing.zylalabs.com/api/10675/age+detection+api/20229/age+calculation
INPUT PARAMETERS

Age Calculation — Endpoint Features

Object Description
Request Body Required Json

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

API EXAMPLE RESPONSE
JSON
{"input":{"image":"https://t3.ftcdn.net/jpg/02/43/12/34/360_F_243123463_zTooub557xEWABDLk0jJklDyLSGl2jrr.jpg"},"output":"29","id":null,"version":null,"created_at":null,"started_at":"2025-10-08T01:13:39.499963+00:00","completed_at":"2025-10-08T01:13:39.590770+00:00","logs":"","error":null,"status":"succeeded","metrics":{"predict_time":0.090807},"webhook":null,"webhook_events_filter":["start","output","completed","logs"],"output_file_prefix":null}
Age Calculation — CODE SNIPPETS

curl --location --request POST 'https://pr213-testing.zylalabs.com/api/10675/age+detection+api/20229/age+calculation' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
  "input": {
    "image": "https://neweralive.na/wp-content/uploads/2024/06/lloyd-sikeba.jpg"
  }
}'

    

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Age Detection API simply include your bearer token in the Authorization header.

Headers
Header Description
Authorization Required Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

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Overview

The Age Detection API is a powerful AI-based tool that allows you to accurately estimate a person's age from an image. It works simply: the user sends the URL of a photograph and the system returns a detailed analysis with the approximate age of the detected face. Thanks to its advanced computer vision and deep learning algorithms, the API offers fast, reliable results that are adaptable to a wide variety of use cases.

This technology uses neural networks trained with millions of faces of different ages, genders, and backgrounds, ensuring robust and accurate estimates even under varying lighting conditions or poses. In addition, the API prioritizes efficiency, processing images in seconds and returning results in JSON format that is easy to integrate with any existing application or system.

In short, this API combines advanced technology and operational simplicity to deliver reliable, secure, and useful age estimates in a wide range of professional and commercial contexts.

Age Detection API FAQs

The Age Detection API returns a JSON object containing the estimated age of the detected face from the provided image URL. It includes fields such as "input" (the image URL), "output" (the estimated age), and metadata about the processing time and status.

The key fields in the response include "input" (the image URL), "output" (the estimated age), "status" (processing status), "metrics" (performance metrics like prediction time), and timestamps for when the request was started and completed.

The response data is structured in a JSON format. It contains an "input" object with the image URL, an "output" field for the estimated age, and additional metadata such as "status" and "metrics" for performance evaluation.

The API provides information on the estimated age of a person detected in an image. It also includes processing metrics, such as the time taken for prediction, and the status of the request, allowing users to assess performance.

Data accuracy is maintained through advanced AI algorithms and neural networks trained on millions of diverse faces. This extensive training helps ensure reliable age estimates across various lighting conditions and poses.

Typical use cases include age verification for online services, demographic analysis in marketing, enhancing user experience in social media applications, and research in age-related studies or applications.

Users can utilize the returned data by integrating the estimated age into their applications for personalized content, targeted marketing, or user profiling. The JSON format allows for easy parsing and integration into various systems.

Users can expect consistent output patterns, where the "output" field reliably contains an estimated age, while "status" indicates success or failure. Processing times are typically quick, allowing for real-time applications.

The Age Detection API endpoint accepts a single parameter: the image URL. Users must provide a valid URL pointing to an image containing a face for the API to analyze and return an estimated age.

Users can customize their requests by selecting different images to analyze. By providing various image URLs, users can obtain age estimates for different individuals, allowing for diverse applications in their projects.

In the response, "input" refers to the submitted image URL, "output" indicates the estimated age, "status" shows the processing result, and "metrics" provides performance details like prediction time, helping users assess efficiency.

The API employs rigorous testing and validation processes during development, utilizing a vast dataset of images to ensure the model's performance. Continuous monitoring of results helps maintain high accuracy and reliability.

If the API returns an empty or null output, users should check the image URL for validity and ensure it contains a clear face. Implementing error handling in the application can help manage such scenarios effectively.

The Age Detection API is designed to analyze faces from diverse backgrounds, ages, and genders. Its training dataset includes a wide range of images, making it adaptable for various demographic analyses.

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