Face API - v1.0

This API is currently available in:

  • Australia East - australiaeast.api.cognitive.microsoft.com
  • Brazil South - brazilsouth.api.cognitive.microsoft.com
  • Canada Central - canadacentral.api.cognitive.microsoft.com
  • Central India - centralindia.api.cognitive.microsoft.com
  • Central US - centralus.api.cognitive.microsoft.com
  • East Asia - eastasia.api.cognitive.microsoft.com
  • East US - eastus.api.cognitive.microsoft.com
  • East US 2 - eastus2.api.cognitive.microsoft.com
  • France Central - francecentral.api.cognitive.microsoft.com
  • Germany West Central - germanywestcentral.api.cognitive.microsoft.com
  • Italy North - italynorth.api.cognitive.microsoft.com
  • Japan East - japaneast.api.cognitive.microsoft.com
  • Japan West - japanwest.api.cognitive.microsoft.com
  • Jio India West - jioindiawest.api.cognitive.microsoft.com
  • Korea Central - koreacentral.api.cognitive.microsoft.com
  • North Central US - northcentralus.api.cognitive.microsoft.com
  • North Europe - northeurope.api.cognitive.microsoft.com
  • Norway East - norwayeast.api.cognitive.microsoft.com
  • Qatar Central - qatarcentral.api.cognitive.microsoft.com
  • South Africa North - southafricanorth.api.cognitive.microsoft.com
  • South Central US - southcentralus.api.cognitive.microsoft.com
  • Southeast Asia - southeastasia.api.cognitive.microsoft.com
  • Sweden Central - swedencentral.api.cognitive.microsoft.com
  • Switzerland North - switzerlandnorth.api.cognitive.microsoft.com
  • Switzerland West - switzerlandwest.api.cognitive.microsoft.com
  • UAE North - uaenorth.api.cognitive.microsoft.com
  • UK South - uksouth.api.cognitive.microsoft.com
  • West Central US - westcentralus.api.cognitive.microsoft.com
  • West Europe - westeurope.api.cognitive.microsoft.com
  • West US - westus.api.cognitive.microsoft.com
  • West US 2 - westus2.api.cognitive.microsoft.com
  • West US 3 - westus3.api.cognitive.microsoft.com

LargeFaceList - Add Face

Add a face to a specified large face list, up to 1,000,000 faces.
To deal with an image containing multiple faces, input face can be specified as an image with a targetFace rectangle. It returns a persistedFaceId representing the added face. No image will be stored. Only the extracted face feature(s) will be stored on server until LargeFaceList Face - Delete or LargeFaceList - Delete is called.
Note persistedFaceId is different from faceId generated by Face - Detect.

  • Higher face image quality means better recognition precision. Please consider high-quality faces: frontal, clear, and face size is 200x200 pixels (100 pixels between eyes) or bigger.
  • JPEG, PNG, GIF (the first frame), and BMP format are supported. The allowed image file size is from 1KB to 6MB.
  • "targetFace" rectangle should contain one face. Zero or multiple faces will be regarded as an error. If the provided "targetFace" rectangle is not returned from Face - Detect, there’s no guarantee to detect and add the face successfully.
  • Out of detectable face size (36x36 - 4096x4096 pixels), large head-pose, or large occlusions will cause failures.
  • Adding/deleting faces to/from a same face list are processed sequentially and to/from different face lists are in parallel.
  • The minimum detectable face size is 36x36 pixels in an image no larger than 1920x1080 pixels. Images with dimensions higher than 1920x1080 pixels will need a proportionally larger minimum face size.
  • Different 'detectionModel' values can be provided. To use and compare different detection models, please refer to How to specify a detection model
    • 'detection_01': The default detection model for LargeFaceList - Add Face. Recommend for near frontal face detection. For scenarios with exceptionally large angle (head-pose) faces, occluded faces or wrong image orientation, the faces in such cases may not be detected.
    • 'detection_02': Detection model released in 2019 May with improved accuracy especially on small, side and blurry faces.
    • 'detection_03': Detection model released in 2021 February with improved accuracy especially on small faces.
Quota:
  • Free-tier subscription quota: 1,000 faces per large face list.
  • S0-tier subscription quota: 1,000,000 faces per large face list.

Http Method

POST

Select the testing console in the region where you created your resource:

Australia East Brazil South Canada Central Central India Central US East Asia East US East US 2 France Central Germany West Central Japan East Japan West Jio India West Korea Central North Central US North Europe Norway East Qatar Central South Africa North South Central US Southeast Asia Sweden Central Switzerland North Switzerland West UAE North UK South West Central US West Europe West US West US 2 West US 3

Request URL

Request parameters

string

Valid character is letter in lower case or digit or '-' or '_', maximum length is 64.

(optional)
string

User-specified data about the target face to add for any purpose. The maximum length is 1KB.

(optional)
string

A face rectangle to specify the target face to be added to a large face list, in the format of "targetFace=left,top,width,height". E.g. "targetFace=10,10,100,100". If there is more than one face in the image, targetFace is required to specify which face to add. No targetFace means there is only one face detected in the entire image.

(optional)
string

"The 'detectionModel' associated with the detected faceIds. Supported 'detectionModel' values include "detection_01", "detection_02" and "detection_03". The default value is "detection_01".

Request headers

string
Media type of the body sent to the API.
string
Subscription key which provides access to this API. Found in your Cognitive Services accounts.

Request body



JSON fields in request body:

Fields Type Description
url String Face image URL. Valid image size is from 1KB to 6MB. Only one face is allowed per image. 

{
    "url": "http://example.com/1.jpg"
}
[binary data]

Response 200

A successful call returns a new persistedFaceId.

JSON fields in response body:

FieldsTypeDescription
persistedFaceIdStringpersistedFaceId of the added face, which is persisted and will not expire. Different from faceId which is created in Face - Detect and will expire in 24 hours after the detection call.
 

{
    "persistedFaceId": "43897a75-8d6f-42cf-885e-74832febb055"
}

Response 400

Error code and message returned in JSON:

Error Code Error Message Description
BadArgument JSON parsing error.
BadArgument 'userData' is too long.
BadArgument Argument targetFace out of range.
BadArgument Invalid argument targetFace.
BadArgument 'detectionModel' is invalid.
InvalidURL Invalid image URL.
InvalidURL Invalid image URL or error downloading from target server. Remote server error returned: "An error occurred while sending the request."
InvalidImage There is more than 1 face in the image.
InvalidImage No face detected in the image.
InvalidImage Decoding error, image format unsupported.
InvalidImageSize Image size is too small.
InvalidImageSize Image size is too big. 

{
    "error": {
        "code": "BadArgument",
        "message": "JSON parsing error."
    }
}

Response 401

Error code and message returned in JSON:

Error Code Error Message Description
Unspecified Access denied due to invalid subscription key. Make sure you are subscribed to an API you are trying to call and provide the right key. 

{
    "error": {
        "code": "Unspecified",
        "message": "Access denied due to invalid subscription key. Make sure you are subscribed to an API you are trying to call and provide the right key."
    }
}

Response 403

{
    "error": {
        "code": "QuotaExceeded",
        "message": "Persisted face number reached limit."
    }
}

Response 404

Error code and message returned in JSON:

Error Code Error Message Description
LargeFaceListNotFound Large face list is not found.
LargeFaceListNotFound Large face list ID is invalid. 

{
    "error": {
        "code": "LargeFaceListNotFound",
        "message": "Large face list is not found."
    }
}

Response 408

Operation exceeds maximum execution time.

{
    "error": {
        "code": "OperationTimeOut",
        "message": "Request Timeout."
    }
}

Response 415

Unsupported media type error. Content-Type is not in the allowed types:

  1. For an image URL, Content-Type should be application/json
  2. For a local image, Content-Type should be application/octet-stream

{
    "error": {
        "code": "BadArgument",
        "message": "Invalid Media Type."
    }
}

Response 429

{
    "error": {
        "statusCode": 429,
        "message": "Rate limit is exceeded. Try again in 26 seconds."
    }
}

Code samples

@ECHO OFF

curl -v -X POST "https://uaenorth.api.cognitive.microsoft.com/face/v1.0/largefacelists/{largeFaceListId}/persistedfaces?userData={string}&targetFace={string}&detectionModel=detection_01"
-H "Content-Type: application/json"
-H "Ocp-Apim-Subscription-Key: {subscription key}"

--data-ascii "{body}" 

using System;
using System.Net.Http.Headers;
using System.Text;
using System.Net.Http;
using System.Web;

namespace CSHttpClientSample
{
    static class Program
    {
        static void Main()
        {
            MakeRequest();
            Console.WriteLine("Hit ENTER to exit...");
            Console.ReadLine();
        }
        
        static async void MakeRequest()
        {
            var client = new HttpClient();
            var queryString = HttpUtility.ParseQueryString(string.Empty);

            // Request headers
            client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", "{subscription key}");

            // Request parameters
            queryString["userData"] = "{string}";
            queryString["targetFace"] = "{string}";
            queryString["detectionModel"] = "detection_01";
            var uri = "https://uaenorth.api.cognitive.microsoft.com/face/v1.0/largefacelists/{largeFaceListId}/persistedfaces?" + queryString;

            HttpResponseMessage response;

            // Request body
            byte[] byteData = Encoding.UTF8.GetBytes("{body}");

            using (var content = new ByteArrayContent(byteData))
            {
               content.Headers.ContentType = new MediaTypeHeaderValue("< your content type, i.e. application/json >");
               response = await client.PostAsync(uri, content);
            }

        }
    }
}	
// // This sample uses the Apache HTTP client from HTTP Components (http://hc.apache.org/httpcomponents-client-ga/)
import java.net.URI;
import org.apache.http.HttpEntity;
import org.apache.http.HttpResponse;
import org.apache.http.client.HttpClient;
import org.apache.http.client.methods.HttpGet;
import org.apache.http.client.utils.URIBuilder;
import org.apache.http.impl.client.HttpClients;
import org.apache.http.util.EntityUtils;

public class JavaSample 
{
    public static void main(String[] args) 
    {
        HttpClient httpclient = HttpClients.createDefault();

        try
        {
            URIBuilder builder = new URIBuilder("https://uaenorth.api.cognitive.microsoft.com/face/v1.0/largefacelists/{largeFaceListId}/persistedfaces");

            builder.setParameter("userData", "{string}");
            builder.setParameter("targetFace", "{string}");
            builder.setParameter("detectionModel", "detection_01");

            URI uri = builder.build();
            HttpPost request = new HttpPost(uri);
            request.setHeader("Content-Type", "application/json");
            request.setHeader("Ocp-Apim-Subscription-Key", "{subscription key}");


            // Request body
            StringEntity reqEntity = new StringEntity("{body}");
            request.setEntity(reqEntity);

            HttpResponse response = httpclient.execute(request);
            HttpEntity entity = response.getEntity();

            if (entity != null) 
            {
                System.out.println(EntityUtils.toString(entity));
            }
        }
        catch (Exception e)
        {
            System.out.println(e.getMessage());
        }
    }
}


<!DOCTYPE html>
<html>
<head>
    <title>JSSample</title>
    <script src="http://ajax.googleapis.com/ajax/libs/jquery/1.9.0/jquery.min.js"></script>
</head>
<body>

<script type="text/javascript">
    $(function() {
        var params = {
            // Request parameters
            "userData": "{string}",
            "targetFace": "{string}",
            "detectionModel": "detection_01",
        };
      
        $.ajax({
            url: "https://uaenorth.api.cognitive.microsoft.com/face/v1.0/largefacelists/{largeFaceListId}/persistedfaces?" + $.param(params),
            beforeSend: function(xhrObj){
                // Request headers
                xhrObj.setRequestHeader("Content-Type","application/json");
                xhrObj.setRequestHeader("Ocp-Apim-Subscription-Key","{subscription key}");
            },
            type: "POST",
            // Request body
            data: "{body}",
        })
        .done(function(data) {
            alert("success");
        })
        .fail(function() {
            alert("error");
        });
    });
</script>
</body>
</html>

#import <Foundation/Foundation.h>

int main(int argc, const char * argv[])
{
    NSAutoreleasePool * pool = [[NSAutoreleasePool alloc] init];
    
    NSString* path = @"https://uaenorth.api.cognitive.microsoft.com/face/v1.0/largefacelists/{largeFaceListId}/persistedfaces";
    NSArray* array = @[
                         // Request parameters
                         @"entities=true",
                         @"userData={string}",
                         @"targetFace={string}",
                         @"detectionModel=detection_01",
                      ];
    
    NSString* string = [array componentsJoinedByString:@"&"];
    path = [path stringByAppendingFormat:@"?%@", string];

    NSLog(@"%@", path);

    NSMutableURLRequest* _request = [NSMutableURLRequest requestWithURL:[NSURL URLWithString:path]];
    [_request setHTTPMethod:@"POST"];
    // Request headers
    [_request setValue:@"application/json" forHTTPHeaderField:@"Content-Type"];
    [_request setValue:@"{subscription key}" forHTTPHeaderField:@"Ocp-Apim-Subscription-Key"];
    // Request body
    [_request setHTTPBody:[@"{body}" dataUsingEncoding:NSUTF8StringEncoding]];
    
    NSURLResponse *response = nil;
    NSError *error = nil;
    NSData* _connectionData = [NSURLConnection sendSynchronousRequest:_request returningResponse:&response error:&error];

    if (nil != error)
    {
        NSLog(@"Error: %@", error);
    }
    else
    {
        NSError* error = nil;
        NSMutableDictionary* json = nil;
        NSString* dataString = [[NSString alloc] initWithData:_connectionData encoding:NSUTF8StringEncoding];
        NSLog(@"%@", dataString);
        
        if (nil != _connectionData)
        {
            json = [NSJSONSerialization JSONObjectWithData:_connectionData options:NSJSONReadingMutableContainers error:&error];
        }
        
        if (error || !json)
        {
            NSLog(@"Could not parse loaded json with error:%@", error);
        }
        
        NSLog(@"%@", json);
        _connectionData = nil;
    }
    
    [pool drain];

    return 0;
}

<?php
// This sample uses the Apache HTTP client from HTTP Components (http://hc.apache.org/httpcomponents-client-ga/)
require_once 'HTTP/Request2.php';

$request = new Http_Request2('https://uaenorth.api.cognitive.microsoft.com/face/v1.0/largefacelists/{largeFaceListId}/persistedfaces');
$url = $request->getUrl();

$headers = array(
    // Request headers
    'Content-Type' => 'application/json',
    'Ocp-Apim-Subscription-Key' => '{subscription key}',
);

$request->setHeader($headers);

$parameters = array(
    // Request parameters
    'userData' => '{string}',
    'targetFace' => '{string}',
    'detectionModel' => 'detection_01',
);

$url->setQueryVariables($parameters);

$request->setMethod(HTTP_Request2::METHOD_POST);

// Request body
$request->setBody("{body}");

try
{
    $response = $request->send();
    echo $response->getBody();
}
catch (HttpException $ex)
{
    echo $ex;
}

?>
########### Python 2.7 #############
import httplib, urllib, base64

headers = {
    # Request headers
    'Content-Type': 'application/json',
    'Ocp-Apim-Subscription-Key': '{subscription key}',
}

params = urllib.urlencode({
    # Request parameters
    'userData': '{string}',
    'targetFace': '{string}',
    'detectionModel': 'detection_01',
})

try:
    conn = httplib.HTTPSConnection('uaenorth.api.cognitive.microsoft.com')
    conn.request("POST", "/face/v1.0/largefacelists/{largeFaceListId}/persistedfaces?%s" % params, "{body}", headers)
    response = conn.getresponse()
    data = response.read()
    print(data)
    conn.close()
except Exception as e:
    print("[Errno {0}] {1}".format(e.errno, e.strerror))

####################################

########### Python 3.2 #############
import http.client, urllib.request, urllib.parse, urllib.error, base64

headers = {
    # Request headers
    'Content-Type': 'application/json',
    'Ocp-Apim-Subscription-Key': '{subscription key}',
}

params = urllib.parse.urlencode({
    # Request parameters
    'userData': '{string}',
    'targetFace': '{string}',
    'detectionModel': 'detection_01',
})

try:
    conn = http.client.HTTPSConnection('uaenorth.api.cognitive.microsoft.com')
    conn.request("POST", "/face/v1.0/largefacelists/{largeFaceListId}/persistedfaces?%s" % params, "{body}", headers)
    response = conn.getresponse()
    data = response.read()
    print(data)
    conn.close()
except Exception as e:
    print("[Errno {0}] {1}".format(e.errno, e.strerror))

####################################
require 'net/http'

uri = URI('https://uaenorth.api.cognitive.microsoft.com/face/v1.0/largefacelists/{largeFaceListId}/persistedfaces')

query = URI.encode_www_form({
    # Request parameters
    'userData' => '{string}',
    'targetFace' => '{string}',
    'detectionModel' => 'detection_01'
})
if query.length > 0
  if uri.query && uri.query.length > 0
    uri.query += '&' + query
  else
    uri.query = query
  end
end

request = Net::HTTP::Post.new(uri.request_uri)
# Request headers
request['Content-Type'] = 'application/json'
# Request headers
request['Ocp-Apim-Subscription-Key'] = '{subscription key}'
# Request body
request.body = "{body}"

response = Net::HTTP.start(uri.host, uri.port, :use_ssl => uri.scheme == 'https') do |http|
    http.request(request)
end

puts response.body