Form Recognizer API (v1.0-preview)

Form Recognizer extracts key value pairs and tables from documents and includes the following options:

  • Custom - Extracts information from forms (PDFs and images) into structured data based on a model created by 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 and tables, and then outputs structured data that includes the relationships within the original file.
  • Prebuilt 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.


This API is currently available in:

  • Australia East - australiaeast.api.cognitive.microsoft.com
  • Canada Central - canadacentral.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
  • North Europe - northeurope.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 Europe - westeurope.api.cognitive.microsoft.com
  • West US 2 - westus2.api.cognitive.microsoft.com

Train Model

Create and train a custom model. The train request must include a source parameter that is either an externally accessible Azure Storage blob container Uri (preferably a Shared Access Signature Uri) or valid path to a data folder in a locally mounted drive. When local paths are specified, they must follow the Linux/Unix path format and be an absolute path rooted to the input mount configuration setting value e.g., if '' configuration setting value is '/input' then a valid source path would be '/input/contosodataset'. All data to be trained is expected to be directly under the source folder. Subfolders are not supported. Models are trained using documents that are of the following content type - 'application/pdf', 'image/jpeg' and 'image/png'." Other type of content is ignored.

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

Open API testing console

Request URL

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

Request object for training.

{
  "source": "string",
  "sourceFilter": {
    "prefix": "string",
    "includeSubFolders": true
  }
}
{
  "description": "Contract to initiate a train request.",
  "required": [
    "source"
  ],
  "type": "object",
  "properties": {
    "source": {
      "description": "Get or set source path.",
      "maxLength": 2048,
      "minLength": 0,
      "type": "string"
    },
    "sourceFilter": {
      "description": "Get or set filter to further search the\r\nsource path for content.",
      "type": "object",
      "properties": {
        "prefix": {
          "description": "A case-sensitive prefix string to filter content\r\nunder the source location. For e.g., when using a Azure Blob\r\nUri use the prefix to restrict subfolders for content.",
          "maxLength": 128,
          "minLength": 0,
          "type": "string"
        },
        "includeSubFolders": {
          "description": "A flag to indicate of sub folders within the set of\r\nprefix folders will also need to included when searching\r\nfor content to be preprocessed.",
          "type": "boolean"
        }
      }
    }
  }
}

Response 200

Success

{
  "modelId": "string",
  "trainingDocuments": [
    {
      "documentName": "string",
      "pages": 0,
      "errors": [
        "string"
      ],
      "status": "success"
    }
  ],
  "errors": [
    {
      "errorMessage": "string"
    }
  ]
}
{
  "description": "Response of the Train API call.",
  "type": "object",
  "properties": {
    "modelId": {
      "description": "Identifier of the model.",
      "type": "string",
      "format": "uuid",
      "x-nullable": false
    },
    "trainingDocuments": {
      "description": "List of documents used to train the model and the\r\ntrain operation error reported by each.",
      "uniqueItems": false,
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "documentName": {
            "description": "Reference to the data that the report is for.",
            "type": "string"
          },
          "pages": {
            "format": "int32",
            "description": "Total number of pages trained on.",
            "type": "integer"
          },
          "errors": {
            "description": "List of errors per page.",
            "uniqueItems": false,
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          "status": {
            "description": "Status of the training operation.",
            "enum": [
              "success",
              "partialSuccess",
              "failure"
            ],
            "type": "string"
          }
        }
      }
    },
    "errors": {
      "description": "Errors returned during the training operation.",
      "uniqueItems": false,
      "type": "array",
      "items": {
        "description": "Error reported during an operation.",
        "type": "object",
        "properties": {
          "errorMessage": {
            "description": "Message reported during the train operation.",
            "type": "string"
          }
        }
      }
    }
  }
}

Response 500

Response entity accompanying non-successful responses containing additional details about the error.

{
  "error": {
    "code": "string",
    "innerError": {
      "requestId": "string"
    },
    "message": "string"
  }
}
{
  "type": "object",
  "properties": {
    "error": {
      "type": "object",
      "properties": {
        "code": {
          "type": "string"
        },
        "innerError": {
          "type": "object",
          "properties": {
            "requestId": {
              "type": "string"
            }
          }
        },
        "message": {
          "type": "string"
        }
      }
    }
  }
}

Code samples

@ECHO OFF

curl -v -X POST "https://*.cognitiveservices.azure.com/formrecognizer/v1.0-preview/custom/train"
-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}");

            var uri = "https://*.cognitiveservices.azure.com/formrecognizer/v1.0-preview/custom/train?" + 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/v1.0-preview/custom/train");


            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
        };
      
        $.ajax({
            url: "https://*.cognitiveservices.azure.com/formrecognizer/v1.0-preview/custom/train?" + $.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/v1.0-preview/custom/train";
    NSArray* array = @[
                         // Request parameters
                         @"entities=true",
                      ];
    
    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/v1.0-preview/custom/train');
$url = $request->getUrl();

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

$request->setHeader($headers);

$parameters = array(
    // Request parameters
);

$url->setQueryVariables($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({
})

try:
    conn = httplib.HTTPSConnection('*.cognitiveservices.azure.com')
    conn.request("POST", "/formrecognizer/v1.0-preview/custom/train?%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({
})

try:
    conn = http.client.HTTPSConnection('*.cognitiveservices.azure.com')
    conn.request("POST", "/formrecognizer/v1.0-preview/custom/train?%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/v1.0-preview/custom/train')
uri.query = URI.encode_www_form({
})

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