Form Recognizer API (v2.0)

Form Recognizer extracts information from forms and images into structured data. It includes the following options:

  • Form - Extracts information from forms (PDFs and images) into structured data based on a model created from a set of representative training forms. Form Recognizer learns the structure of your forms to intelligently extract text and data. It ingests text from forms, applies machine learning technology to identify keys, tables, and fields, and then outputs structured data that includes the relationships within the original file.
  • Receipt - Detects and extracts data from receipts using optical character recognition (OCR) and our receipt model, enabling you to easily extract structured data from receipts such as merchant name, merchant phone number, transaction date, transaction total, and more.
  • Layout - Extracts text and table structure from documents using optical character recognition (OCR).

Custom Form - Analyze Form

Extract key-value pairs, tables, and semantic values from a given document. The input document must be of one of the supported content types - 'application/pdf', 'image/jpeg', 'image/png' or 'image/tiff'. Alternatively, use 'application/json' type to specify the Url location of the document to be analyzed.

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

Open API testing console

Request URL

Request parameters

string

Format - uuid. Model identifier.

(optional)
boolean

Include text lines and element references in the result. Default: false.

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, .pdf, .jpg, .png or .tiff type file stream.

{
  "source": "http://example.com/test.jpg"
}
{
  "description": "Url to source data.",
  "type": "object",
  "properties": {
    "source": {
      "description": "Url path.",
      "maxLength": 2048,
      "minLength": 0,
      "type": "string"
    }
  },
  "example": {
    "source": "http://example.com/test.jpg"
  }
}
{
  "source": "http://example.com/test.jpg"
}
{
  "description": "Url to source data.",
  "type": "object",
  "properties": {
    "source": {
      "description": "Url path.",
      "maxLength": 2048,
      "minLength": 0,
      "type": "string"
    }
  },
  "example": {
    "source": "http://example.com/test.jpg"
  }
}
{
  "source": "http://example.com/test.jpg"
}
{
  "description": "Url to source data.",
  "type": "object",
  "properties": {
    "source": {
      "description": "Url path.",
      "maxLength": 2048,
      "minLength": 0,
      "type": "string"
    }
  },
  "example": {
    "source": "http://example.com/test.jpg"
  }
}
{
  "source": "http://example.com/test.jpg"
}
{
  "description": "Url to source data.",
  "type": "object",
  "properties": {
    "source": {
      "description": "Url path.",
      "maxLength": 2048,
      "minLength": 0,
      "type": "string"
    }
  },
  "example": {
    "source": "http://example.com/test.jpg"
  }
}
{
  "source": "http://example.com/test.jpg"
}
{
  "description": "Url to source data.",
  "type": "object",
  "properties": {
    "source": {
      "description": "Url path.",
      "maxLength": 2048,
      "minLength": 0,
      "type": "string"
    }
  },
  "example": {
    "source": "http://example.com/test.jpg"
  }
}

Response 202

The service has accepted the request and will start processing soon. The client can query the operation status and result using the URL specified in the 'Operation-Location' response header. The URL expires in 48 hours.

Operation-Location URL containing the resultId used to track the progress and obtain the result of the analyze operation.
Example: https://cognitiveservice/formrecognizer/v2.0/custom/models/{modelId}/analyzeResults/{resultId}

Response 400

Bad request error.

Response 404

Model not found.

Response 415

Unsupported media type error. 'Content-Type' does not match the POST content.

  • For image URL, 'Content-Type' should be 'application/json'.
  • For binary PDF data, 'Content-Type' should be 'application/pdf'.
  • For binary image data, 'Content-Type' should be 'image/jpeg', 'image/png' or 'image/tiff'.

Response 500

Internal server error.

Response 503

Transient fault.

Code samples

@ECHO OFF

curl -v -X POST "https://*.cognitiveservices.azure.com/formrecognizer/v2.0/custom/models/{modelId}/analyze?includeTextDetails={boolean}"
-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["includeTextDetails"] = "{boolean}";
            var uri = "https://*.cognitiveservices.azure.com/formrecognizer/v2.0/custom/models/{modelId}/analyze?" + 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/formrecognizer/v2.0/custom/models/{modelId}/analyze");

            builder.setParameter("includeTextDetails", "{boolean}");

            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
            "includeTextDetails": "{boolean}",
        };
      
        $.ajax({
            url: "https://*.cognitiveservices.azure.com/formrecognizer/v2.0/custom/models/{modelId}/analyze?" + $.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/formrecognizer/v2.0/custom/models/{modelId}/analyze";
    NSArray* array = @[
                         // Request parameters
                         @"entities=true",
                         @"includeTextDetails={boolean}",
                      ];
    
    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/formrecognizer/v2.0/custom/models/{modelId}/analyze');
$url = $request->getUrl();

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

$request->setHeader($headers);

$parameters = array(
    // Request parameters
    'includeTextDetails' => '{boolean}',
);

$url->setQueryVariables($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
    'includeTextDetails': '{boolean}',
})

try:
    conn = httplib.HTTPSConnection('*.cognitiveservices.azure.com')
    conn.request("POST", "/formrecognizer/v2.0/custom/models/{modelId}/analyze?%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
    'includeTextDetails': '{boolean}',
})

try:
    conn = http.client.HTTPSConnection('*.cognitiveservices.azure.com')
    conn.request("POST", "/formrecognizer/v2.0/custom/models/{modelId}/analyze?%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/formrecognizer/v2.0/custom/models/{modelId}/analyze')

query = URI.encode_www_form({
    # Request parameters
    'includeTextDetails' => '{boolean}'
})
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