How to convert a scanned document into text with location in Node.JS using OCR

It wasn’t that long ago that converting a document scan into text on a computer seemed like the holy grail, and yet here we are, living with this luxury of productivity. And today, it gets even better — I’m going to show you how to use optical character recognition with virtually zero effort.

Begin by adding the client to your package.json with this reference:

"dependencies": {
    "cloudmersive-ocr-api-client": "^1.2.7"
  }

Then implement our function with this code and provide a language for greater accuracy:

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';
// Uncomment the following line to set a prefix for the API key, e.g. "Token" (defaults to null)
//Apikey.apiKeyPrefix = 'Token';
var apiInstance = new CloudmersiveOcrApiClient.ImageOcrApi();
var imageFile = "/path/to/file"; // 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);

And it’s just that easy. The function will even handle preprocessing on the image to enhance accuracy. Note that if you will be using photos rather than scans, it is best to use our other API function specifically designed for that, as it factors in skewing.