One of the earliest and most well defined use cases of Deep Learning has been face identification and verification. Arya's face recognition module is one of the robust modules trained to recognise and match faces from a variety of sources such as surveillance footage or images.
Minimize identity theft and image fraud risks effectively.
Recognise and match faces from various sources accurately
Performed over 10 million verifications monthly
Complete verifications in less than a minute
Annual API Volume
Accuracy Rate
Daily API Volume
Time to launch
Hassle-Free,
No Code Platform
Easy to adopt
& integrate
99.99%
API Success Rate
Reliable &
Secure
6 Dec 2023
Financial document fraud has increased in the last two years. Scammers...
19 March 2024
While we expect bank statements to be accurate records of financial transactions...
30 April 2024
With banks and financial institutions heavily relying on large volumes of data, they...
Please wait...
Faces Matched!
Matching Score: {{outputSample.score || output.score |percent}}%
Faces Not Matched!
Matching Score: {{outputSample.score || output.score |percent}}%
curl --location --request POST '{{getEndpoint(url, api_version, pageDetails.ping_endpoint)}}' \
--header 'token: < your private token >' \
--header 'content-type: application/json' \
--data-raw '{
"doc1_type":'image',
"doc2_type":'image',
"img1_base64": '< base64 string of document >',
"img2_base64": '< base64 string of document >',
"req_id": '< req id string >'
}'
OkHttpClient client = new OkHttpClient().newBuilder().build();
MediaType mediaType = MediaType.parse("application/javascript");
RequestBody body = RequestBody.create(mediaType, "{ "doc1_type":'image',"doc2_type":'image',"img1_base64": '< base64 string of document >',"img2_base64": '< base64 string of document >',"req_id": '< req id string >' }");
Request request = new Request.Builder()
.url("{{getEndpoint(url, api_version, pageDetails.ping_endpoint)}}")
.method("POST", body)
.addHeader("token", "< your private token >")
.addHeader("content-type", "application/json")
.build();
Response response = client.newCall(request).execute();
require "uri"
require "net/http"
url = URI("{{getEndpoint(url, api_version, pageDetails.ping_endpoint)}}")
https = Net::HTTP.new(url.host, url.port)
https.use_ssl = true
request = Net::HTTP::Post.new(url)
request["token"] = "< your private token >"
request["content-type"] = "application/json"
request.body = "{"doc1_type":'image',"doc2_type":'image',"img1_base64": '< base64 string of document >',"img2_base64": '< base64 string of document >',"req_id": '< req id string >' }"
response = https.request(request)
puts response.read_body
CURL *curl;
CURLcode res;
curl = curl_easy_init();
if(curl) {
curl_easy_setopt(curl, CURLOPT_CUSTOMREQUEST, "POST");
curl_easy_setopt(curl, CURLOPT_URL, "{{getEndpoint(url, api_version, pageDetails.ping_endpoint)}}");
curl_easy_setopt(curl, CURLOPT_FOLLOWLOCATION, 1L);
curl_easy_setopt(curl, CURLOPT_DEFAULT_PROTOCOL, "https");
struct curl_slist *headers = NULL;
headers = curl_slist_append(headers, "token: < your private token >");
headers = curl_slist_append(headers, "content-type: application/json");
curl_easy_setopt(curl, CURLOPT_HTTPHEADER, headers);
const char *data = "{"doc1_type":'image',"doc2_type":'image',"img1_base64": '< base64 string of document >',"img2_base64": '< base64 string of document >',"req_id": '< req id string >' }";
curl_easy_setopt(curl, CURLOPT_POSTFIELDS, data);
res = curl_easy_perform(curl);
}
curl_easy_cleanup(curl);
var request = require('request');
var options = {
'method': 'POST',
'url': '{{getEndpoint(url, api_version, pageDetails.ping_endpoint)}}',
'headers': {
'token': '< your private token >',
'content-type':'application/json'
},
body: '{"doc1_type":'image',"doc2_type":'image',"img1_base64": '< base64 string of document >',"img2_base64": '< base64 string of document >',"req_id": '< req id string >' }'
};
request(options, function (error, response) {
if (error) throw new Error(error);
console.log(response.body);
});
var client = new RestClient("{{getEndpoint(url, api_version, pageDetails.ping_endpoint)}}");
ṣclient.Timeout = -1;
var request = new RestRequest(Method.POST);
request.AddHeader("token", "< your private token >");
request.AddHeader("content-type", "application/json");
var body = @"{" + "" +
@" "doc1_type": 'image'," + "" +
@" "img1_base64": '< base64 string of document >'," + "" +
@" "doc2_type": 'image'," + "" +
@" "img2_base64": '< base64 string of document >'," + "" +
@" "req_id": < req id string >" + "" +
@" }";
request.AddParameter("application/json", body, ParameterType.RequestBody);
IRestResponse response = client.Execute(request);
Console.WriteLine(response.Content);
php
require_once 'HTTP/Request2.php';
$request = new HTTP_Request2();
$request->setUrl('{{getEndpoint(url, api_version, pageDetails.ping_endpoint)}}');
$request->setMethod(HTTP_Request2::METHOD_POST);
$request->setConfig(array(
'follow_redirects' => TRUE
));
$request->setHeader(array(
'token' => '< your private token >',
'content-type' => 'application/json'
));
$request->setBody('{"doc1_type":'image',"doc2_type":'image',"img1_base64": '< base64 string of document >',"img2_base64": '< base64 string of document >',"req_id": '< req id string >' }');
try {
$response = $request->send();
if ($response->getStatus() == 200) {
echo $response->getBody();
}
else {
echo 'Unexpected HTTP status: ' . $response->getStatus() . ' ' .
$response->getReasonPhrase();
}
}
catch(HTTP_Request2_Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
import requests
url = "{{getEndpoint(url, api_version, pageDetails.ping_endpoint)}}"
payload = {"doc1_type":'image',"doc2_type":'image',"img1_base64": '< base64 string of document >',"img2_base64": '< base64 string of document >',"req_id": '< req id string >' }
headers = {
'token': '< your private token >',
'content-type':'application/json'
}
response = requests.request("POST", url, json=payload, headers=headers)
print(response.text)
Name | Description |
---|---|
token | String |
Name | Description |
---|---|
body |
{ "req_id" : < string >, "doc_base64": < base64 encoded string > "doc_type" : < string>, } |
Name | Description |
---|---|
body |
{ "req_id" : < string >, "success" : < boolean >, "doc_type": < string >, "error_message" : < string >, "data" : < dict >, } |
Fields | Values/Description |
---|---|
doc_type | “image" / "pdf” |
req_id | Unique request ID used for processing requests |
doc_base64 | Base64 encoded string of the document |
Fields | Values/Description |
---|---|
req_id | Corresponding request id |
success | Flag if the request is processed successfully |
doc_type | Type of document uploaded |
error_message | If success is False then: Error message |
data | Dictionary of extracted data |