Run this command to install the SDK:

npm install cloudmersive-ocr-api-client --save


Or add this snippet to your package.json:

  "dependencies": {
    "cloudmersive-ocr-api-client": "^1.3.3"
  }


var CloudmersiveOcrApiClient = require('cloudmersive-ocr-api-client');
var defaultClient = CloudmersiveOcrApiClient.ApiClient.instance;

// Configure API key authorization: Apikey
var Apikey = defaultClient.authentications['Apikey'];
Apikey.apiKey = 'YOUR API KEY';



var apiInstance = new CloudmersiveOcrApiClient.ImageOcrApi();

var imageFile = Buffer.from(fs.readFileSync("C:\\temp\\inputfile").buffer); // File | Image file to perform OCR on.  Common file formats such as PNG, JPEG are supported.

var opts = { 
  'recognitionMode': "recognitionMode_example", // String | Optional; possible values are 'Basic' which provides basic recognition and is not resillient to page rotation, skew or low quality images uses 1-2 API calls; 'Normal' which provides highly fault tolerant OCR recognition uses 14-16 API calls; and 'Advanced' which provides the highest quality and most fault-tolerant recognition uses 28-30 API calls.  Default recognition mode is 'Advanced'
  'language': "language_example", // String | Optional, language of the input document, default is English (ENG).  Possible values are ENG (English), ARA (Arabic), ZHO (Chinese - Simplified), ZHO-HANT (Chinese - Traditional), ASM (Assamese), AFR (Afrikaans), AMH (Amharic), AZE (Azerbaijani), AZE-CYRL (Azerbaijani - Cyrillic), BEL (Belarusian), BEN (Bengali), BOD (Tibetan), BOS (Bosnian), BUL (Bulgarian), CAT (Catalan; Valencian), CEB (Cebuano), CES (Czech), CHR (Cherokee), CYM (Welsh), DAN (Danish), DEU (German), DZO (Dzongkha), ELL (Greek), ENM (Archaic/Middle English), EPO (Esperanto), EST (Estonian), EUS (Basque), FAS (Persian), FIN (Finnish), FRA (French), FRK (Frankish), FRM (Middle-French), GLE (Irish), GLG (Galician), GRC (Ancient Greek), HAT (Hatian), HEB (Hebrew), HIN (Hindi), HRV (Croatian), HUN (Hungarian), IKU (Inuktitut), IND (Indonesian), ISL (Icelandic), ITA (Italian), ITA-OLD (Old - Italian), JAV (Javanese), JPN (Japanese), KAN (Kannada), KAT (Georgian), KAT-OLD (Old-Georgian), KAZ (Kazakh), KHM (Central Khmer), KIR (Kirghiz), KOR (Korean), KUR (Kurdish), LAO (Lao), LAT (Latin), LAV (Latvian), LIT (Lithuanian), MAL (Malayalam), MAR (Marathi), MKD (Macedonian), MLT (Maltese), MSA (Malay), MYA (Burmese), NEP (Nepali), NLD (Dutch), NOR (Norwegian), ORI (Oriya), PAN (Panjabi), POL (Polish), POR (Portuguese), PUS (Pushto), RON (Romanian), RUS (Russian), SAN (Sanskrit), SIN (Sinhala), SLK (Slovak), SLV (Slovenian), SPA (Spanish), SPA-OLD (Old Spanish), SQI (Albanian), SRP (Serbian), SRP-LAT (Latin Serbian), SWA (Swahili), SWE (Swedish), SYR (Syriac), TAM (Tamil), TEL (Telugu), TGK (Tajik), TGL (Tagalog), THA (Thai), TIR (Tigrinya), TUR (Turkish), UIG (Uighur), UKR (Ukrainian), URD (Urdu), UZB (Uzbek), UZB-CYR (Cyrillic Uzbek), VIE (Vietnamese), YID (Yiddish)
  'preprocessing': "preprocessing_example" // String | Optional, preprocessing mode, default is 'Auto'.  Possible values are None (no preprocessing of the image), and Auto (automatic image enhancement of the image before OCR is applied; this is recommended).
};

var callback = function(error, data, response) {
  if (error) {
    console.error(error);
  } else {
    console.log('API called successfully. Returned data: ' + data);
  }
};
apiInstance.imageOcrPost(imageFile, opts, callback);

Run this command to install the SDK:

pip install cloudmersive-ocr-api-client


from __future__ import print_function
import time
import cloudmersive_ocr_api_client
from cloudmersive_ocr_api_client.rest import ApiException
from pprint import pprint

# Configure API key authorization: Apikey
configuration = cloudmersive_ocr_api_client.Configuration()
configuration.api_key['Apikey'] = 'YOUR_API_KEY'



# create an instance of the API class
api_instance = cloudmersive_ocr_api_client.ImageOcrApi(cloudmersive_ocr_api_client.ApiClient(configuration))
image_file = '/path/to/file' # file | Image file to perform OCR on.  Common file formats such as PNG, JPEG are supported.
recognition_mode = 'recognition_mode_example' # str | Optional; possible values are 'Basic' which provides basic recognition and is not resillient to page rotation, skew or low quality images uses 1-2 API calls; 'Normal' which provides highly fault tolerant OCR recognition uses 26-30 API calls; and 'Advanced' which provides the highest quality and most fault-tolerant recognition uses 28-30 API calls.  Default recognition mode is 'Advanced' (optional)
language = 'language_example' # str | Optional, language of the input document, default is English (ENG).  Possible values are ENG (English), ARA (Arabic), ZHO (Chinese - Simplified), ZHO-HANT (Chinese - Traditional), ASM (Assamese), AFR (Afrikaans), AMH (Amharic), AZE (Azerbaijani), AZE-CYRL (Azerbaijani - Cyrillic), BEL (Belarusian), BEN (Bengali), BOD (Tibetan), BOS (Bosnian), BUL (Bulgarian), CAT (Catalan; Valencian), CEB (Cebuano), CES (Czech), CHR (Cherokee), CYM (Welsh), DAN (Danish), DEU (German), DZO (Dzongkha), ELL (Greek), ENM (Archaic/Middle English), EPO (Esperanto), EST (Estonian), EUS (Basque), FAS (Persian), FIN (Finnish), FRA (French), FRK (Frankish), FRM (Middle-French), GLE (Irish), GLG (Galician), GRC (Ancient Greek), HAT (Hatian), HEB (Hebrew), HIN (Hindi), HRV (Croatian), HUN (Hungarian), IKU (Inuktitut), IND (Indonesian), ISL (Icelandic), ITA (Italian), ITA-OLD (Old - Italian), JAV (Javanese), JPN (Japanese), KAN (Kannada), KAT (Georgian), KAT-OLD (Old-Georgian), KAZ (Kazakh), KHM (Central Khmer), KIR (Kirghiz), KOR (Korean), KUR (Kurdish), LAO (Lao), LAT (Latin), LAV (Latvian), LIT (Lithuanian), MAL (Malayalam), MAR (Marathi), MKD (Macedonian), MLT (Maltese), MSA (Malay), MYA (Burmese), NEP (Nepali), NLD (Dutch), NOR (Norwegian), ORI (Oriya), PAN (Panjabi), POL (Polish), POR (Portuguese), PUS (Pushto), RON (Romanian), RUS (Russian), SAN (Sanskrit), SIN (Sinhala), SLK (Slovak), SLV (Slovenian), SPA (Spanish), SPA-OLD (Old Spanish), SQI (Albanian), SRP (Serbian), SRP-LAT (Latin Serbian), SWA (Swahili), SWE (Swedish), SYR (Syriac), TAM (Tamil), TEL (Telugu), TGK (Tajik), TGL (Tagalog), THA (Thai), TIR (Tigrinya), TUR (Turkish), UIG (Uighur), UKR (Ukrainian), URD (Urdu), UZB (Uzbek), UZB-CYR (Cyrillic Uzbek), VIE (Vietnamese), YID (Yiddish) (optional)
preprocessing = 'preprocessing_example' # str | Optional, preprocessing mode, default is 'Auto'.  Possible values are None (no preprocessing of the image), and Auto (automatic image enhancement of the image before OCR is applied; this is recommended). (optional)

try:
    # Convert a scanned image into text
    api_response = api_instance.image_ocr_post(image_file, recognition_mode=recognition_mode, language=language, preprocessing=preprocessing)
    pprint(api_response)
except ApiException as e:
    print("Exception when calling ImageOcrApi->image_ocr_post: %s\n" % e)
.NET Framework | .NET Core

Run this command to install the SDK:

Install-Package Cloudmersive.APIClient.NET.OCR -Version 3.0.5



using System;
using System.Diagnostics;
using Cloudmersive.APIClient.NET.OCR.Api;
using Cloudmersive.APIClient.NET.OCR.Client;
using Cloudmersive.APIClient.NET.OCR.Model;

namespace Example
{
    public class ImageOcrPostExample
    {
        public void main()
        {
            // Configure API key authorization: Apikey
            Configuration.Default.AddApiKey("Apikey", "YOUR_API_KEY");
            
            

            var apiInstance = new ImageOcrApi();
            var imageFile = new System.IO.FileStream("C:\\temp\\inputfile", System.IO.FileMode.Open); // System.IO.Stream | Image file to perform OCR on.  Common file formats such as PNG, JPEG are supported.
            var recognitionMode = recognitionMode_example;  // string | Optional; possible values are 'Basic' which provides basic recognition and is not resillient to page rotation, skew or low quality images uses 1-2 API calls; 'Normal' which provides highly fault tolerant OCR recognition uses 26-30 API calls; and 'Advanced' which provides the highest quality and most fault-tolerant recognition uses 28-30 API calls.  Default recognition mode is 'Advanced' (optional) 
            var language = language_example;  // string | Optional, language of the input document, default is English (ENG).  Possible values are ENG (English), ARA (Arabic), ZHO (Chinese - Simplified), ZHO-HANT (Chinese - Traditional), ASM (Assamese), AFR (Afrikaans), AMH (Amharic), AZE (Azerbaijani), AZE-CYRL (Azerbaijani - Cyrillic), BEL (Belarusian), BEN (Bengali), BOD (Tibetan), BOS (Bosnian), BUL (Bulgarian), CAT (Catalan; Valencian), CEB (Cebuano), CES (Czech), CHR (Cherokee), CYM (Welsh), DAN (Danish), DEU (German), DZO (Dzongkha), ELL (Greek), ENM (Archaic/Middle English), EPO (Esperanto), EST (Estonian), EUS (Basque), FAS (Persian), FIN (Finnish), FRA (French), FRK (Frankish), FRM (Middle-French), GLE (Irish), GLG (Galician), GRC (Ancient Greek), HAT (Hatian), HEB (Hebrew), HIN (Hindi), HRV (Croatian), HUN (Hungarian), IKU (Inuktitut), IND (Indonesian), ISL (Icelandic), ITA (Italian), ITA-OLD (Old - Italian), JAV (Javanese), JPN (Japanese), KAN (Kannada), KAT (Georgian), KAT-OLD (Old-Georgian), KAZ (Kazakh), KHM (Central Khmer), KIR (Kirghiz), KOR (Korean), KUR (Kurdish), LAO (Lao), LAT (Latin), LAV (Latvian), LIT (Lithuanian), MAL (Malayalam), MAR (Marathi), MKD (Macedonian), MLT (Maltese), MSA (Malay), MYA (Burmese), NEP (Nepali), NLD (Dutch), NOR (Norwegian), ORI (Oriya), PAN (Panjabi), POL (Polish), POR (Portuguese), PUS (Pushto), RON (Romanian), RUS (Russian), SAN (Sanskrit), SIN (Sinhala), SLK (Slovak), SLV (Slovenian), SPA (Spanish), SPA-OLD (Old Spanish), SQI (Albanian), SRP (Serbian), SRP-LAT (Latin Serbian), SWA (Swahili), SWE (Swedish), SYR (Syriac), TAM (Tamil), TEL (Telugu), TGK (Tajik), TGL (Tagalog), THA (Thai), TIR (Tigrinya), TUR (Turkish), UIG (Uighur), UKR (Ukrainian), URD (Urdu), UZB (Uzbek), UZB-CYR (Cyrillic Uzbek), VIE (Vietnamese), YID (Yiddish) (optional) 
            var preprocessing = preprocessing_example;  // string | Optional, preprocessing mode, default is 'Auto'.  Possible values are None (no preprocessing of the image), and Auto (automatic image enhancement of the image before OCR is applied; this is recommended). (optional) 

            try
            {
                // Convert a scanned image into text
                ImageToTextResponse result = apiInstance.ImageOcrPost(imageFile, recognitionMode, language, preprocessing);
                Debug.WriteLine(result);
            }
            catch (Exception e)
            {
                Debug.Print("Exception when calling ImageOcrApi.ImageOcrPost: " + e.Message );
            }
        }
    }
}

To install with Maven, add a reference to the repository in pom.xml:

<repositories>
    <repository>
        <id>jitpack.io</id>
        <url>https://jitpack.io</url>
    </repository>
</repositories>


And add a reference to the dependency in pom.xml:

<dependencies>
<dependency>
    <groupId>com.github.Cloudmersive</groupId>
    <artifactId>Cloudmersive.APIClient.Java</artifactId>
    <version>v4.25</version>
</dependency>
</dependencies>


To install with Gradle, add it in your root build.gradle at the end of repositories:

allprojects {
	repositories {
		...
		maven { url 'https://jitpack.io' }
	}
}


And add the dependency in build.gradle:

dependencies {
        implementation 'com.github.Cloudmersive:Cloudmersive.APIClient.Java:v4.25'
}


// Import classes:
//import com.cloudmersive.client.invoker.ApiClient;
//import com.cloudmersive.client.invoker.ApiException;
//import com.cloudmersive.client.invoker.Configuration;
//import com.cloudmersive.client.invoker.auth.*;
//import com.cloudmersive.client.ImageOcrApi;

ApiClient defaultClient = Configuration.getDefaultApiClient();

// Configure API key authorization: Apikey
ApiKeyAuth Apikey = (ApiKeyAuth) defaultClient.getAuthentication("Apikey");
Apikey.setApiKey("YOUR API KEY");
// Uncomment the following line to set a prefix for the API key, e.g. "Token" (defaults to null)
//Apikey.setApiKeyPrefix("Token");

ImageOcrApi apiInstance = new ImageOcrApi();
File imageFile = new File("/path/to/file"); // File | Image file to perform OCR on.  Common file formats such as PNG, JPEG are supported.
String recognitionMode = "recognitionMode_example"; // String | Optional; possible values are 'Basic' which provides basic recognition and is not resillient to page rotation, skew or low quality images uses 1-2 API calls; 'Normal' which provides highly fault tolerant OCR recognition uses 26-30 API calls; and 'Advanced' which provides the highest quality and most fault-tolerant recognition uses 28-30 API calls.  Default recognition mode is 'Advanced'
String language = "language_example"; // String | Optional, language of the input document, default is English (ENG).  Possible values are ENG (English), ARA (Arabic), ZHO (Chinese - Simplified), ZHO-HANT (Chinese - Traditional), ASM (Assamese), AFR (Afrikaans), AMH (Amharic), AZE (Azerbaijani), AZE-CYRL (Azerbaijani - Cyrillic), BEL (Belarusian), BEN (Bengali), BOD (Tibetan), BOS (Bosnian), BUL (Bulgarian), CAT (Catalan; Valencian), CEB (Cebuano), CES (Czech), CHR (Cherokee), CYM (Welsh), DAN (Danish), DEU (German), DZO (Dzongkha), ELL (Greek), ENM (Archaic/Middle English), EPO (Esperanto), EST (Estonian), EUS (Basque), FAS (Persian), FIN (Finnish), FRA (French), FRK (Frankish), FRM (Middle-French), GLE (Irish), GLG (Galician), GRC (Ancient Greek), HAT (Hatian), HEB (Hebrew), HIN (Hindi), HRV (Croatian), HUN (Hungarian), IKU (Inuktitut), IND (Indonesian), ISL (Icelandic), ITA (Italian), ITA-OLD (Old - Italian), JAV (Javanese), JPN (Japanese), KAN (Kannada), KAT (Georgian), KAT-OLD (Old-Georgian), KAZ (Kazakh), KHM (Central Khmer), KIR (Kirghiz), KOR (Korean), KUR (Kurdish), LAO (Lao), LAT (Latin), LAV (Latvian), LIT (Lithuanian), MAL (Malayalam), MAR (Marathi), MKD (Macedonian), MLT (Maltese), MSA (Malay), MYA (Burmese), NEP (Nepali), NLD (Dutch), NOR (Norwegian), ORI (Oriya), PAN (Panjabi), POL (Polish), POR (Portuguese), PUS (Pushto), RON (Romanian), RUS (Russian), SAN (Sanskrit), SIN (Sinhala), SLK (Slovak), SLV (Slovenian), SPA (Spanish), SPA-OLD (Old Spanish), SQI (Albanian), SRP (Serbian), SRP-LAT (Latin Serbian), SWA (Swahili), SWE (Swedish), SYR (Syriac), TAM (Tamil), TEL (Telugu), TGK (Tajik), TGL (Tagalog), THA (Thai), TIR (Tigrinya), TUR (Turkish), UIG (Uighur), UKR (Ukrainian), URD (Urdu), UZB (Uzbek), UZB-CYR (Cyrillic Uzbek), VIE (Vietnamese), YID (Yiddish)
String preprocessing = "preprocessing_example"; // String | Optional, preprocessing mode, default is 'Auto'.  Possible values are None (no preprocessing of the image), and Auto (automatic image enhancement of the image before OCR is applied; this is recommended).
try {
    ImageToTextResponse result = apiInstance.imageOcrPost(imageFile, recognitionMode, language, preprocessing);
    System.out.println(result);
} catch (ApiException e) {
    System.err.println("Exception when calling ImageOcrApi#imageOcrPost");
    e.printStackTrace();
}

Run this command to install the SDK:

composer require cloudmersive/cloudmersive_ocr_api_client


<?php
require_once(__DIR__ . '/vendor/autoload.php');

// Configure API key authorization: Apikey
$config = Swagger\Client\Configuration::getDefaultConfiguration()->setApiKey('Apikey', 'YOUR_API_KEY');



$apiInstance = new Swagger\Client\Api\ImageOcrApi(
    
    
    new GuzzleHttp\Client(),
    $config
);
$image_file = "/path/to/file"; // \SplFileObject | Image file to perform OCR on.  Common file formats such as PNG, JPEG are supported.
$recognition_mode = "recognition_mode_example"; // string | Optional; possible values are 'Basic' which provides basic recognition and is not resillient to page rotation, skew or low quality images uses 1-2 API calls; 'Normal' which provides highly fault tolerant OCR recognition uses 14-16 API calls; and 'Advanced' which provides the highest quality and most fault-tolerant recognition uses 28-30 API calls.  Default recognition mode is 'Advanced'
$language = "language_example"; // string | Optional, language of the input document, default is English (ENG).  Possible values are ENG (English), ARA (Arabic), ZHO (Chinese - Simplified), ZHO-HANT (Chinese - Traditional), ASM (Assamese), AFR (Afrikaans), AMH (Amharic), AZE (Azerbaijani), AZE-CYRL (Azerbaijani - Cyrillic), BEL (Belarusian), BEN (Bengali), BOD (Tibetan), BOS (Bosnian), BUL (Bulgarian), CAT (Catalan; Valencian), CEB (Cebuano), CES (Czech), CHR (Cherokee), CYM (Welsh), DAN (Danish), DEU (German), DZO (Dzongkha), ELL (Greek), ENM (Archaic/Middle English), EPO (Esperanto), EST (Estonian), EUS (Basque), FAS (Persian), FIN (Finnish), FRA (French), FRK (Frankish), FRM (Middle-French), GLE (Irish), GLG (Galician), GRC (Ancient Greek), HAT (Hatian), HEB (Hebrew), HIN (Hindi), HRV (Croatian), HUN (Hungarian), IKU (Inuktitut), IND (Indonesian), ISL (Icelandic), ITA (Italian), ITA-OLD (Old - Italian), JAV (Javanese), JPN (Japanese), KAN (Kannada), KAT (Georgian), KAT-OLD (Old-Georgian), KAZ (Kazakh), KHM (Central Khmer), KIR (Kirghiz), KOR (Korean), KUR (Kurdish), LAO (Lao), LAT (Latin), LAV (Latvian), LIT (Lithuanian), MAL (Malayalam), MAR (Marathi), MKD (Macedonian), MLT (Maltese), MSA (Malay), MYA (Burmese), NEP (Nepali), NLD (Dutch), NOR (Norwegian), ORI (Oriya), PAN (Panjabi), POL (Polish), POR (Portuguese), PUS (Pushto), RON (Romanian), RUS (Russian), SAN (Sanskrit), SIN (Sinhala), SLK (Slovak), SLV (Slovenian), SPA (Spanish), SPA-OLD (Old Spanish), SQI (Albanian), SRP (Serbian), SRP-LAT (Latin Serbian), SWA (Swahili), SWE (Swedish), SYR (Syriac), TAM (Tamil), TEL (Telugu), TGK (Tajik), TGL (Tagalog), THA (Thai), TIR (Tigrinya), TUR (Turkish), UIG (Uighur), UKR (Ukrainian), URD (Urdu), UZB (Uzbek), UZB-CYR (Cyrillic Uzbek), VIE (Vietnamese), YID (Yiddish)
$preprocessing = "preprocessing_example"; // string | Optional, preprocessing mode, default is 'Auto'.  Possible values are None (no preprocessing of the image), and Auto (automatic image enhancement of the image before OCR is applied; this is recommended).

try {
    $result = $apiInstance->imageOcrPost($image_file, $recognition_mode, $language, $preprocessing);
    print_r($result);
} catch (Exception $e) {
    echo 'Exception when calling ImageOcrApi->imageOcrPost: ', $e->getMessage(), PHP_EOL;
}
?>

Add the Objective-C client to your Podfile:

pod 'CloudmersiveOCRApiClient', '~> 1.0'


CMDefaultConfiguration *apiConfig = [CMDefaultConfiguration sharedConfig];

// Configure API key authorization: (authentication scheme: Apikey)
[apiConfig setApiKey:@"YOUR_API_KEY" forApiKeyIdentifier:@"Apikey"];




NSURL* imageFile = [NSURL fileURLWithPath:@"/path/to/file"]; // Image file to perform OCR on.  Common file formats such as PNG, JPEG are supported.
NSString* recognitionMode = @"recognitionMode_example"; // Optional; possible values are 'Basic' which provides basic recognition and is not resillient to page rotation, skew or low quality images uses 1-2 API calls; 'Normal' which provides highly fault tolerant OCR recognition uses 26-30 API calls; and 'Advanced' which provides the highest quality and most fault-tolerant recognition uses 28-30 API calls.  Default recognition mode is 'Advanced' (optional)
NSString* language = @"language_example"; // Optional, language of the input document, default is English (ENG).  Possible values are ENG (English), ARA (Arabic), ZHO (Chinese - Simplified), ZHO-HANT (Chinese - Traditional), ASM (Assamese), AFR (Afrikaans), AMH (Amharic), AZE (Azerbaijani), AZE-CYRL (Azerbaijani - Cyrillic), BEL (Belarusian), BEN (Bengali), BOD (Tibetan), BOS (Bosnian), BUL (Bulgarian), CAT (Catalan; Valencian), CEB (Cebuano), CES (Czech), CHR (Cherokee), CYM (Welsh), DAN (Danish), DEU (German), DZO (Dzongkha), ELL (Greek), ENM (Archaic/Middle English), EPO (Esperanto), EST (Estonian), EUS (Basque), FAS (Persian), FIN (Finnish), FRA (French), FRK (Frankish), FRM (Middle-French), GLE (Irish), GLG (Galician), GRC (Ancient Greek), HAT (Hatian), HEB (Hebrew), HIN (Hindi), HRV (Croatian), HUN (Hungarian), IKU (Inuktitut), IND (Indonesian), ISL (Icelandic), ITA (Italian), ITA-OLD (Old - Italian), JAV (Javanese), JPN (Japanese), KAN (Kannada), KAT (Georgian), KAT-OLD (Old-Georgian), KAZ (Kazakh), KHM (Central Khmer), KIR (Kirghiz), KOR (Korean), KUR (Kurdish), LAO (Lao), LAT (Latin), LAV (Latvian), LIT (Lithuanian), MAL (Malayalam), MAR (Marathi), MKD (Macedonian), MLT (Maltese), MSA (Malay), MYA (Burmese), NEP (Nepali), NLD (Dutch), NOR (Norwegian), ORI (Oriya), PAN (Panjabi), POL (Polish), POR (Portuguese), PUS (Pushto), RON (Romanian), RUS (Russian), SAN (Sanskrit), SIN (Sinhala), SLK (Slovak), SLV (Slovenian), SPA (Spanish), SPA-OLD (Old Spanish), SQI (Albanian), SRP (Serbian), SRP-LAT (Latin Serbian), SWA (Swahili), SWE (Swedish), SYR (Syriac), TAM (Tamil), TEL (Telugu), TGK (Tajik), TGL (Tagalog), THA (Thai), TIR (Tigrinya), TUR (Turkish), UIG (Uighur), UKR (Ukrainian), URD (Urdu), UZB (Uzbek), UZB-CYR (Cyrillic Uzbek), VIE (Vietnamese), YID (Yiddish) (optional)
NSString* preprocessing = @"preprocessing_example"; // Optional, preprocessing mode, default is 'Auto'.  Possible values are None (no preprocessing of the image), and Auto (automatic image enhancement of the image before OCR is applied; this is recommended). (optional)

CMImageOcrApi*apiInstance = [[CMImageOcrApi alloc] init];

// Convert a scanned image into text
[apiInstance imageOcrPostWithImageFile:imageFile
              recognitionMode:recognitionMode
              language:language
              preprocessing:preprocessing
          completionHandler: ^(CMImageToTextResponse* output, NSError* error) {
                        if (output) {
                            NSLog(@"%@", output);
                        }
                        if (error) {
                            NSLog(@"Error calling CMImageOcrApi->imageOcrPost: %@", error);
                        }
                    }];

Add the Ruby client to your Gemfile:

gem 'cloudmersive-ocr-api-client', '~> 2.0.2'


# load the gem
require 'cloudmersive-ocr-api-client'
# setup authorization
CloudmersiveOcrApiClient.configure do |config|
  # Configure API key authorization: Apikey
  config.api_key['Apikey'] = 'YOUR API KEY'
  # Uncomment the following line to set a prefix for the API key, e.g. 'Bearer' (defaults to nil)
  #config.api_key_prefix['Apikey'] = 'Bearer'
end

api_instance = CloudmersiveOcrApiClient::ImageOcrApi.new

image_file = File.new('/path/to/inputfile') # File | Image file to perform OCR on.  Common file formats such as PNG, JPEG are supported.

opts = { 
  recognition_mode: 'recognition_mode_example', # String | Optional; possible values are 'Basic' which provides basic recognition and is not resillient to page rotation, skew or low quality images uses 1-2 API calls; 'Normal' which provides highly fault tolerant OCR recognition uses 26-30 API calls; and 'Advanced' which provides the highest quality and most fault-tolerant recognition uses 28-30 API calls.  Default recognition mode is 'Advanced'
  language: 'language_example', # String | Optional, language of the input document, default is English (ENG).  Possible values are ENG (English), ARA (Arabic), ZHO (Chinese - Simplified), ZHO-HANT (Chinese - Traditional), ASM (Assamese), AFR (Afrikaans), AMH (Amharic), AZE (Azerbaijani), AZE-CYRL (Azerbaijani - Cyrillic), BEL (Belarusian), BEN (Bengali), BOD (Tibetan), BOS (Bosnian), BUL (Bulgarian), CAT (Catalan; Valencian), CEB (Cebuano), CES (Czech), CHR (Cherokee), CYM (Welsh), DAN (Danish), DEU (German), DZO (Dzongkha), ELL (Greek), ENM (Archaic/Middle English), EPO (Esperanto), EST (Estonian), EUS (Basque), FAS (Persian), FIN (Finnish), FRA (French), FRK (Frankish), FRM (Middle-French), GLE (Irish), GLG (Galician), GRC (Ancient Greek), HAT (Hatian), HEB (Hebrew), HIN (Hindi), HRV (Croatian), HUN (Hungarian), IKU (Inuktitut), IND (Indonesian), ISL (Icelandic), ITA (Italian), ITA-OLD (Old - Italian), JAV (Javanese), JPN (Japanese), KAN (Kannada), KAT (Georgian), KAT-OLD (Old-Georgian), KAZ (Kazakh), KHM (Central Khmer), KIR (Kirghiz), KOR (Korean), KUR (Kurdish), LAO (Lao), LAT (Latin), LAV (Latvian), LIT (Lithuanian), MAL (Malayalam), MAR (Marathi), MKD (Macedonian), MLT (Maltese), MSA (Malay), MYA (Burmese), NEP (Nepali), NLD (Dutch), NOR (Norwegian), ORI (Oriya), PAN (Panjabi), POL (Polish), POR (Portuguese), PUS (Pushto), RON (Romanian), RUS (Russian), SAN (Sanskrit), SIN (Sinhala), SLK (Slovak), SLV (Slovenian), SPA (Spanish), SPA-OLD (Old Spanish), SQI (Albanian), SRP (Serbian), SRP-LAT (Latin Serbian), SWA (Swahili), SWE (Swedish), SYR (Syriac), TAM (Tamil), TEL (Telugu), TGK (Tajik), TGL (Tagalog), THA (Thai), TIR (Tigrinya), TUR (Turkish), UIG (Uighur), UKR (Ukrainian), URD (Urdu), UZB (Uzbek), UZB-CYR (Cyrillic Uzbek), VIE (Vietnamese), YID (Yiddish)
  preprocessing: 'preprocessing_example' # String | Optional, preprocessing mode, default is 'Auto'.  Possible values are None (no preprocessing of the image), and Auto (automatic image enhancement of the image before OCR is applied; this is recommended).
}

begin
  #Convert a scanned image into text
  result = api_instance.image_ocr_post(image_file, opts)
  p result
rescue CloudmersiveOcrApiClient::ApiError => e
  puts "Exception when calling ImageOcrApi->image_ocr_post: #{e}"
end

Download and copy the /client folder into your Apex project:

Download Apex Client

SwagImageOcrApi api = new SwagImageOcrApi();
SwagClient client = api.getClient();

// Configure API key authorization: Apikey
ApiKeyAuth Apikey = (ApiKeyAuth) client.getAuthentication('Apikey');
Apikey.setApiKey('YOUR API KEY');

Map<String, Object> params = new Map<String, Object>{
    'imageFile' => Blob.valueOf('Sample text file\nContents'),
    'recognitionMode' => 'recognitionMode_example',
    'language' => 'language_example',
    'preprocessing' => 'preprocessing_example'
};

try {
    // cross your fingers
    SwagImageToTextResponse result = api.imageOcrPost(params);
    System.debug(result);
} catch (Swagger.ApiException e) {
    // ...handle your exceptions
}

Install libcurl in your C/C++ project:

libcurl/7.75.0
CURL *curl;
CURLcode res;
curl = curl_easy_init();
if(curl) {
     curl_easy_setopt(curl, CURLOPT_CUSTOMREQUEST, "POST");
     curl_easy_setopt(curl, CURLOPT_URL, "https://api.cloudmersive.com/ocr/image/toText");
     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, "recognitionMode: <string>");
     headers = curl_slist_append(headers, "language: <string>");
     headers = curl_slist_append(headers, "preprocessing: <string>");
     headers = curl_slist_append(headers, "Content-Type: multipart/form-data");
     headers = curl_slist_append(headers, "Apikey: YOUR-API-KEY-HERE");
     curl_easy_setopt(curl, CURLOPT_HTTPHEADER, headers);
     curl_mime *mime;
     curl_mimepart *part;
     mime = curl_mime_init(curl);
     part = curl_mime_addpart(mime);
     curl_mime_name(part, "imageFile");
     curl_mime_filedata(part, "/path/to/file");
     curl_easy_setopt(curl, CURLOPT_MIMEPOST, mime);
     res = curl_easy_perform(curl);
     curl_mime_free(mime);
}
curl_easy_cleanup(curl);

curl --location --request POST 'https://api.cloudmersive.com/ocr/image/toText' \
--header 'recognitionMode: <string>' \
--header 'language: <string>' \
--header 'preprocessing: <string>' \
--header 'Content-Type: multipart/form-data' \
--header 'Apikey: YOUR-API-KEY-HERE' \
--form 'imageFile=@"/path/to/file"'
import Foundation
#if canImport(FoundationNetworking)
import FoundationNetworking
#endif

var semaphore = DispatchSemaphore (value: 0)

let parameters = [
     [
          "key": "imageFile",
          "src": "/path/to/file",
          "type": "file"
     ]] as [[String : Any]]

let boundary = "Boundary-\(UUID().uuidString)"
var body = ""
var error: Error? = nil
for param in parameters {
     if param["disabled"] == nil {
          let paramName = param["key"]!
          body += "--\(boundary)\r\n"
          body += "Content-Disposition:form-data; name=\"\(paramName)\""
          if param["contentType"] != nil {
               body += "\r\nContent-Type: \(param["contentType"] as! String)"
          }
          let paramType = param["type"] as! String
          if paramType == "text" {
               let paramValue = param["value"] as! String
               body += "\r\n\r\n\(paramValue)\r\n"
          } else {
               let paramSrc = param["src"] as! String
               let fileData = try NSData(contentsOfFile:paramSrc, options:[]) as Data
               let fileContent = String(data: fileData, encoding: .utf8)!
               body += "; filename=\"\(paramSrc)\"\r\n"
                 + "Content-Type: \"content-type header\"\r\n\r\n\(fileContent)\r\n"
          }
     }
}
body += "--\(boundary)--\r\n";
let postData = body.data(using: .utf8)

var request = URLRequest(url: URL(string: "https://api.cloudmersive.com/ocr/image/toText")!,timeoutInterval: Double.infinity)
request.addValue("<string>", forHTTPHeaderField: "recognitionMode")
request.addValue("<string>", forHTTPHeaderField: "language")
request.addValue("<string>", forHTTPHeaderField: "preprocessing")
request.addValue("multipart/form-data", forHTTPHeaderField: "Content-Type")
request.addValue("YOUR-API-KEY-HERE", forHTTPHeaderField: "Apikey")
request.addValue("multipart/form-data; boundary=\(boundary)", forHTTPHeaderField: "Content-Type")

request.httpMethod = "POST"
request.httpBody = postData

let task = URLSession.shared.dataTask(with: request) { data, response, error in 
     guard let data = data else {
          print(String(describing: error))
          semaphore.signal()
          return
     }
     print(String(data: data, encoding: .utf8)!)
     semaphore.signal()
}

task.resume()
semaphore.wait()
XHR | jQuery

This code snippet uses the built-in JavaScript XHR request capability

 
var data = new FormData();
data.append("imageFile", fileInput.files[0], "file");
 
var xhr = new XMLHttpRequest();
xhr.withCredentials = true;

xhr.addEventListener("readystatechange", function() {
     if(this.readyState === 4) {
          console.log(this.responseText);
     }
});

xhr.open("POST", "https://api.cloudmersive.com/ocr/image/toText");
xhr.setRequestHeader("recognitionMode", "<string>");
xhr.setRequestHeader("language", "<string>");
xhr.setRequestHeader("preprocessing", "<string>");

xhr.setRequestHeader("Apikey", "YOUR-API-KEY-HERE");

xhr.send(data);
package main

import (
     "fmt"
     "bytes"
     "mime/multipart"
     "os"
     "path/filepath"
     "io"
     "net/http"
     "io/ioutil"
)

func main() {

     url := "https://api.cloudmersive.com/ocr/image/toText"
     method := "POST"

     payload := &bytes.Buffer{}
     writer := multipart.NewWriter(payload)
     file, errFile1 := os.Open("/path/to/file")
     defer file.Close()
     part1,
         errFile1 := writer.CreateFormFile("imageFile",filepath.Base("/path/to/file"))
     _, errFile1 = io.Copy(part1, file)
     if errFile1 != nil {
          fmt.Println(errFile1)
          return
     }
     err := writer.Close()
     if err != nil {
          fmt.Println(err)
          return
     }


     client := &http.Client {
     }
     req, err := http.NewRequest(method, url, payload)

     if err != nil {
          fmt.Println(err)
          return
     }
     req.Header.Add("recognitionMode", "<string>")
     req.Header.Add("language", "<string>")
     req.Header.Add("preprocessing", "<string>")
     req.Header.Add("Content-Type", "multipart/form-data")
     req.Header.Add("Apikey", "YOUR-API-KEY-HERE")

     req.Header.Set("Content-Type", writer.FormDataContentType())
     res, err := client.Do(req)
     if err != nil {
          fmt.Println(err)
          return
     }
     defer res.Body.Close()

     body, err := ioutil.ReadAll(res.Body)
     if err != nil {
          fmt.Println(err)
          return
     }
     fmt.Println(string(body))
}

Walkthrough Video