Didit Age Estimation

Didit Age Estimation API

Overview

Estimates a person's age from a facial image using deep learning. Also performs a passive liveness check to prevent spoofing.

Key constraints:

• Supported formats: JPEG, PNG, WebP, TIFF
• Maximum file size: 5MB
• Image must contain one clearly visible face
• Accuracy: MAE ±3.5 years overall; ±1.5 years for under-18

Capabilities: Age estimation with confidence scoring, gender estimation, passive liveness detection, configurable age thresholds, per-country age restrictions, adaptive mode with ID verification fallback for borderline cases.

Liveness methods (workflow mode):

API Reference: https://docs.didit.me/reference/age-estimation-standalone-api

Authentication

All requests require x-api-key header. Get your key from Didit Business Console → API & Webhooks.

Endpoint

POST https://verification.didit.me/v3/age-estimation/

Headers

Request Parameters (multipart/form-data)

Example

import requests

response = requests.post(
    "https://verification.didit.me/v3/age-estimation/",
    headers={"x-api-key": "YOUR_API_KEY"},
    files={"user_image": ("selfie.jpg", open("selfie.jpg", "rb"), "image/jpeg")},
    data={"vendor_data": "user-123"},
)
print(response.json())

const formData = new FormData();
formData.append("user_image", selfieFile);

const response = await fetch("https://verification.didit.me/v3/age-estimation/", {
  method: "POST",
  headers: { "x-api-key": "YOUR_API_KEY" },
  body: formData,
});

Response (200 OK)

{
  "request_id": "a1b2c3d4-...",
  "liveness": {
    "status": "Approved",
    "method": "PASSIVE",
    "score": 89.92,
    "age_estimation": 24.3,
    "reference_image": "https://example.com/reference.jpg",
    "video_url": null,
    "warnings": []
  },
  "created_at": "2025-05-01T13:11:07.977806Z"
}

Status Values & Handling

Error Responses

Response Field Reference

Accuracy by Age Range

Warning Tags

Auto-Decline

Configurable (Decline / Review / Approve)

Warning severity: error (→ Declined), warning (→ In Review), information (no effect).

Common Workflows

Basic Age Gate

1. Capture user selfie
2. POST /v3/age-estimation/ → {"user_image": selfie}
3. Check liveness.age_estimation >= your_minimum_age
4. If "Approved" → user meets age requirement
   If "Declined" → check warnings for AGE_BELOW_MINIMUM or liveness failure

Adaptive Age Estimation (Workflow Mode)

1. Configure workflow with age thresholds in Console
2. POST /v3/session/ → create session with age-estimation workflow
3. User takes selfie → system estimates age
4. Clear pass (well above threshold) → Approved instantly
   Clear fail (well below threshold) → Declined
   Borderline case → automatic ID verification fallback
5. If ID fallback triggered: per-country age restrictions apply

Per-Country Age Restrictions

Configure in Console per issuing country:

Use "Apply age of majority" button in Console to auto-populate defaults.