didit-biometric-age-estimation

name	didit-biometric-age-estimation
description	Estimates a person's age from a facial image via the Didit standalone API. Use when implementing age gating, checking if someone is over 18 or 21, performing age verification for compliance, or detecting underage users. Includes passive liveness check. Supports configurable thresholds, adaptive fallback to ID verification, and per-country restrictions.
version	1.0.0
metadata	{"openclaw":{"requires":{"env":["DIDIT_API_KEY"]},"primaryEnv":"DIDIT_API_KEY","emoji":"🎂","homepage":"https://docs.didit.me"}}

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):

Method	Security	Best For
ACTIVE_3D (Action + Flash)	Highest	Banking, government, healthcare
FLASHING (3D Flash)	High	Financial services, identity verification
PASSIVE (single-frame CNN)	Standard	Low-friction consumer apps

API Reference: https://docs.didit.me/standalone-apis/age-estimation Feature Guide: https://docs.didit.me/core-technology/age-estimation/overview

---

Authentication

All requests require x-api-key header. Get your key from Didit Business Console → API & Webhooks, or via programmatic registration (see below).

Getting Started (No Account Yet?)

If you don't have a Didit API key, create one in 2 API calls:

1. Register: POST https://apx.didit.me/auth/v2/programmatic/register/ with {"email": "[e-mail]", "password": "MyStr0ng!Pass"}
2. Check email for a 6-character OTP code
3. Verify: POST https://apx.didit.me/auth/v2/programmatic/verify-email/ with {"email": "[e-mail]", "code": "A3K9F2"} → response includes api_key

To add credits: GET /v3/billing/balance/ to check, POST /v3/billing/top-up/ with {"amount_in_dollars": 50} for a Stripe checkout link.

See the didit-verification-management skill for full platform management (workflows, sessions, users, billing).

---

Endpoint

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

Headers

Header	Value	Required
x-api-key	Your API key	Yes
Content-Type	multipart/form-data	Yes

Request Parameters (multipart/form-data)

Parameter	Type	Required	Default	Description
user_image	file	Yes	—	Facial image (JPEG/PNG/WebP/TIFF, max 5MB)
rotate_image	boolean	No	false	Try 0/90/180/270 rotations for non-upright faces
save_api_request	boolean	No	true	Save in Business Console Manual Checks
vendor_data	string	No	—	Your identifier for session tracking

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

Status	Meaning	Action
"Approved"	Age verified above threshold, liveness passed	Proceed with your flow
"Declined"	Age below minimum or liveness failed	Check warnings for specifics
"In Review"	Borderline case, needs review	Trigger ID verification fallback or manual review

Error Responses

Code	Meaning	Action
400	Invalid request	Check file format, size, parameters
401	Invalid API key	Verify x-api-key header
403	Insufficient credits	Top up at business.didit.me

---

Response Field Reference

Field	Type	Description
status	string	"Approved", "Declined", "In Review", "Not Finished"
method	string	"ACTIVE_3D", "FLASHING", or "PASSIVE"
score	float	0-100 liveness confidence score
age_estimation	float	Estimated age in years (e.g. 24.3). null if no face
reference_image	string	Temporary URL (expires 60 min)
video_url	string	Temporary URL for active liveness video. null for passive
warnings	array	{risk, log_type, short_description, long_description}

Accuracy by Age Range

Age Range	MAE (years)	Confidence
Under 18	1.5	High
18-25	2.8	High
26-40	3.2	High
41-60	3.9	Medium-High
60+	4.5	Medium

---

Warning Tags

Auto-Decline

Tag	Description
NO_FACE_DETECTED	No face found in image
LIVENESS_FACE_ATTACK	Spoofing attempt detected
FACE_IN_BLOCKLIST	Face matches a blocklist entry

Configurable (Decline / Review / Approve)

Tag	Description
AGE_BELOW_MINIMUM	Estimated age below configured minimum
AGE_NOT_DETECTED	Unable to estimate age (image quality, lighting)
LOW_LIVENESS_SCORE	Liveness score below threshold
POSSIBLE_DUPLICATED_FACE	Significant similarity with previously verified face

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)

Uses workflow_type: "adaptive_age_verification" — creates a session where borderline ages trigger automatic ID verification fallback.

1. POST /v3/workflows/ → {"workflow_type": "adaptive_age_verification", "is_liveness_enabled": true, "is_age_restrictions_enabled": true}
2. POST /v3/session/ → create session with the workflow_id from step 1
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:

Country	Min Age	Overrides
USA	18	Mississippi: 21, Alabama: 19
KOR	19	—
GBR	18	—
ARE	21	—

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

---

Utility Scripts

estimate_age.py: Estimate age from a facial image via the command line.

# Requires: pip install requests
export DIDIT_API_KEY="your_api_key"
python scripts/estimate_age.py selfie.jpg
python scripts/estimate_age.py photo.png --threshold 21 --vendor-data user-123