Form Recognizer API (v2.1)

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.
  • Business Card - Detects and extracts data from business cards using optical character recognition (OCR) and our business card model, enabling you to easily extract structured data from business cards such as contact names, company names, phone numbers, emails, and more.
  • Layout - Extracts text and table structure from documents using optical character recognition (OCR).
  • Invoices - Detects and extracts data from invoices using optical character recognition (OCR) and our invoice understanding deep learning models, enabling you to easily extract structured data from invoices such as customer, vendor, invoice ID, invoice due date, total, invoice amount due, tax amount, ship to, bill to, line items and more.
  • ID Documents - Detects and extracts data from identification documents using optical character recognition (OCR) and our ID document model, enabling you to easily extract structured data from ID documents such as first name, last name, date of birth, document number, and more.

Analyze Receipt - Analyze Receipt

Extract field text and semantic values from a given receipt 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.

Note: this technology is currently only available for English receipts, with one receipt per page.

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

Open API testing console

Request URL

Request parameters

(optional)
boolean

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

(optional)
string

Locale of the receipt. Supported locales: en-AU, en-CA, en-GB, en-IN, en-US.

(optional)
string

The page selection for multi-page PDF and TIFF documents, to extract Receipt information from individual pages and a range of pages (like page 2, and pages 5-7) by entering the page numbers and ranges separated by commas (e.g. '2, 5-7'). If not set, all pages will be processed.

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

Document containing the receipt image(s) to be analyzed. The POST body should be the raw image binary or the image URL in JSON.
Additional requirements:

  • Image format must be one of JPEG, PNG, BMP, PDF or TIFF.
  • For PDF and TIFF, only the first 200 pages are processed.
    • For free tier subscribers, only the first 2 pages are processed.
  • Image file size must be less than 50 MB.
  • Image dimensions must be at least 50 x 50 pixels and at most 10000 x 10000 pixels.

{ "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\" }"
}
[Binary PDF data]
{
  "description": "A pdf document or image (jpg,png,tiff) file to analyze.",
  "type": "object"
}
[Binary JPEG data]
{
  "description": "A pdf document or image (jpg,png,tiff) file to analyze.",
  "type": "object"
}
[Binary PNG data]
{
  "description": "A pdf document or image (jpg,png,tiff) file to analyze.",
  "type": "object"
}
[Binary BMP data]
{
  "description": "A pdf document or image (jpg,png,tiff) file to analyze.",
  "type": "object"
}
[Binary TIFF data]
{
  "description": "A pdf document or image (jpg,png,tiff) file to analyze.",
  "type": "object"
}

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/v2.1-preview.1/prebuilt/receipt/analyzeResults/{resultId}

Response 400

Bad request error. Detailed error code and message are specified in the JSON response:

Error Code Description
BadArgument Bad or unrecognizable request JSON or binary file.
FailedToDownloadImage Failed to download image from input URL.
InvalidImage The input data is not a valid image or password protected.
InvalidImageDimension The input image dimension is out of range. The minimum image dimension is 50 x 50 pixels and the maximum is 10000 x 10000 pixels. The maximum PDF dimension is 17 x 17 inches.
InvalidImageSize The input image is too large. It should not be larger than 50MB.
InvalidImageURL Image URL is badly formatted.
UnsupportedImageFormat Image format unsupported. Supported formats include JPEG, PNG, PDF and TIFF.
UnsupportedLocale Locale unsupported. Supported locales include en-AU, en-CA, en-GB, en-IN and en-US. 

{
  "error": {
    "code": "BadArgument",
    "message": "Invalid input."
  }
}
{
  "type": "object",
  "required": [
    "error"
  ],
  "properties": {
    "error": {
      "type": "object",
      "required": [
        "code",
        "message"
      ],
      "properties": {
        "code": {
          "type": "string"
        },
        "message": {
          "type": "string"
        }
      }
    }
  }
}

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'.

{
  "error": {
    "code": "BadArgument",
    "message": "Unsupported media type."
  }
}
{
  "type": "object",
  "required": [
    "error"
  ],
  "properties": {
    "error": {
      "type": "object",
      "required": [
        "code",
        "message"
      ],
      "properties": {
        "code": {
          "type": "string"
        },
        "message": {
          "type": "string"
        }
      }
    }
  }
}

Response 500

Internal server error.

{
  "error": {
    "code": "Unspecified",
    "message": "Internal server error."
  }
}
{
  "type": "object",
  "required": [
    "error"
  ],
  "properties": {
    "error": {
      "type": "object",
      "required": [
        "code",
        "message"
      ],
      "properties": {
        "code": {
          "type": "string"
        },
        "message": {
          "type": "string"
        }
      }
    }
  }
}

Response 503

Transient fault while querying Microsoft Azure storage services.

{
  "error": {
    "code": "StorageException",
    "message": "Transient fault occurred while querying Microsoft Azure storage services. Please try again later."
  }
}
{
  "type": "object",
  "required": [
    "error"
  ],
  "properties": {
    "error": {
      "type": "object",
      "required": [
        "code",
        "message"
      ],
      "properties": {
        "code": {
          "type": "string"
        },
        "message": {
          "type": "string"
        }
      }
    }
  }
}

Code samples

@ECHO OFF

curl -v -X POST "https://*.cognitiveservices.azure.com/formrecognizer/v2.1/prebuilt/receipt/analyze?includeTextDetails={boolean}&locale={string}&pages={string}"
-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}";
            queryString["locale"] = "{string}";
            queryString["pages"] = "{string}";
            var uri = "https://*.cognitiveservices.azure.com/formrecognizer/v2.1/prebuilt/receipt/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/v2.1/prebuilt/receipt/analyze");

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

            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}",
            "locale": "{string}",
            "pages": "{string}",
        };
      
        $.ajax({
            url: "https://*.cognitiveservices.azure.com/formrecognizer/v2.1/prebuilt/receipt/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/v2.1/prebuilt/receipt/analyze";
    NSArray* array = @[
                         // Request parameters
                         @"entities=true",
                         @"includeTextDetails={boolean}",
                         @"locale={string}",
                         @"pages={string}",
                      ];
    
    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/v2.1/prebuilt/receipt/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}',
    'locale' => '{string}',
    'pages' => '{string}',
);

$url->setQueryVariables($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}',
    'locale': '{string}',
    'pages': '{string}',
})

try:
    conn = httplib.HTTPSConnection('*.cognitiveservices.azure.com')
    conn.request("POST", "/formrecognizer/v2.1/prebuilt/receipt/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}',
    'locale': '{string}',
    'pages': '{string}',
})

try:
    conn = http.client.HTTPSConnection('*.cognitiveservices.azure.com')
    conn.request("POST", "/formrecognizer/v2.1/prebuilt/receipt/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/v2.1/prebuilt/receipt/analyze')
uri.query = URI.encode_www_form({
    # Request parameters
    'includeTextDetails' => '{boolean}',
    'locale' => '{string}',
    'pages' => '{string}'
})

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