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
- Japan East - japaneast.api.cognitive.microsoft.com
- Japan West - japanwest.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
- South Africa North - southafricanorth.api.cognitive.microsoft.com
- South Central US - southcentralus.api.cognitive.microsoft.com
- Southeast Asia - southeastasia.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
- UAE North - uaenorth.api.cognitive.microsoft.com
PersonGroup Person - Add Face
Add a face to a person into a person group for face identification or verification. 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
PersonGroup PersonFace - Delete,
PersonGroup Person - Delete or
PersonGroup - 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.
- Each person entry can hold up to 248 faces.
- 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 person will be processed sequentially. Adding/deleting faces to/from different persons are processed 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 PersonGroup Person - 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.
Http Method
POSTSelect the testing console in the region where you created your resource:
Open API testing consoleRequest URL
Request parameters
Specifying the person group containing the target person.
Target person that the face is added to.
User-specified data about the target face to add for any purpose. The maximum length is 1KB.
A face rectangle to specify the target face to be added to a person, 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.
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
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 the new persistedFaceId.
JSON fields in response body:
Fields | Type | Description |
---|---|---|
persistedFaceId | String | persistedFaceId 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": "B8D802CF-DD8F-4E61-B15C-9E6C5844CCBA"
}
Response 400
Error code and message returned in JSON:
Error Code | Error Message Description |
---|---|
BadArgument | 'userData' is too long. |
BadArgument | Invalid request body. |
BadArgument | Argument targetFace out of range, targetFace is valid but it's intersection with the entire image is empty. |
BadArgument | Invalid argument targetFace. Caused by invalid string format or invalid left/top/height/width value. |
BadArgument | 'detectionModel' is invalid. |
InvalidImage | Decoding error, image format unsupported. |
InvalidImage | No face detected in the image or in the specified targetFace area. |
InvalidImage | There is more than 1 face in the image or in the specified targetFace area. |
InvalidImageSize | Image size is too small. |
InvalidImageSize | Image size is too big. |
InvalidURL | Invalid image URL. |
InvalidURL | Failed to download from target server. Remote server error returned. |
{
"error": {
"code": "BadArgument",
"message": "Request body is invalid."
}
}
Response 401
Error code and message returned in JSON:
Error Code | Error Message Description |
---|---|
Unspecified | Invalid subscription Key or user/plan is blocked. |
{
"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
Persisted face number reached limit, maximum is 248 per person.
{
"error": {
"code": "QuotaExceeded",
"message": "Persisted face number reached limit."
}
}
Response 404
Error code and message returned in JSON:
Error Code | Error Message Description |
---|---|
PersonGroupNotFound | Person group ID is invalid. Valid format should be a string composed by numbers, English letters in lower case, '-', '_', and no longer than 64 characters. |
PersonGroupNotFound | Person group is not found. |
PersonNotFound | Person ID is invalid. |
PersonNotFound | Person is not found. |
{
"error": {
"code": "PersonGroupNotFound",
"message": "Person group is not found."
}
}
Response 408
{
"error": {
"code": "OperationTimeOut",
"message": "Request Timeout."
}
}
Response 409
Error code and message returned in JSON:
Error Code | Error Message Description |
---|---|
PersonGroupTrainingNotFinished | The person group is still under training. Try again after training completed. |
ConcurrentOperationConflict | Concurrent operation conflict on requested resource. |
{
"error": {
"code": "PersonGroupTrainingNotFinished",
"message": "Person group is under training."
}
}
Response 415
Unsupported media type error. Content-Type is not in the allowed types:
- For an image URL, Content-Type should be application/json
- 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://*.cognitiveservices.azure.com/face/v1.0/persongroups/{personGroupId}/persons/{personId}/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://*.cognitiveservices.azure.com/face/v1.0/persongroups/{personGroupId}/persons/{personId}/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://*.cognitiveservices.azure.com/face/v1.0/persongroups/{personGroupId}/persons/{personId}/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://*.cognitiveservices.azure.com/face/v1.0/persongroups/{personGroupId}/persons/{personId}/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://*.cognitiveservices.azure.com/face/v1.0/persongroups/{personGroupId}/persons/{personId}/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://*.cognitiveservices.azure.com/face/v1.0/persongroups/{personGroupId}/persons/{personId}/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('*.cognitiveservices.azure.com')
conn.request("POST", "/face/v1.0/persongroups/{personGroupId}/persons/{personId}/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('*.cognitiveservices.azure.com')
conn.request("POST", "/face/v1.0/persongroups/{personGroupId}/persons/{personId}/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://*.cognitiveservices.azure.com/face/v1.0/persongroups/{personGroupId}/persons/{personId}/persistedFaces')
uri.query = URI.encode_www_form({
# Request parameters
'userData' => '{string}',
'targetFace' => '{string}',
'detectionModel' => 'detection_01'
})
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