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:
Australia East Brazil South Canada Central Central India Central US Central US EUAP East Asia East US East US 2 France Central Germany West Central Japan East Japan West Korea Central North Central US North Europe South Africa North South Central US Southeast Asia Switzerland North Switzerland West UAE North UK South West Central US West Europe West US West US 2 West US 3 Norway East Jio India WestRequest URL
Request parameters
Include text lines and element references in the result. Default: false.
Locale of the receipt. Supported locales: en-AU, en-CA, en-GB, en-IN, en-US.
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
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://japaneast.api.cognitive.microsoft.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://japaneast.api.cognitive.microsoft.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://japaneast.api.cognitive.microsoft.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://japaneast.api.cognitive.microsoft.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://japaneast.api.cognitive.microsoft.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://japaneast.api.cognitive.microsoft.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('japaneast.api.cognitive.microsoft.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('japaneast.api.cognitive.microsoft.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://japaneast.api.cognitive.microsoft.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