Convert JPG to Words in Node.JS using OCR

Today, through the use of some cutting-edge Optical Character Recognition (OCR), we will be able to take a photo of text and automatically convert it into digital text. To set this up manually would be a very time-consuming endeavor, indeed, as this requires a ton of code and the training of a Deep Learning AI, which can take weeks even with industrial grade hardware at your disposal. So instead, how about we implement this into your project with a total time spent of oh, say about 5 minutes.

The beginning of this process is the installation of the Cloudmersive OCR client; use the following command for this for npm install.

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

Now we can call our OCR function, like so:

var CloudmersiveOcrApiClient = require('cloudmersive-ocr-api-client');var defaultClient = CloudmersiveOcrApiClient.ApiClient.instance;// Configure API key authorization: Apikeyvar 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)};var callback = function(error, data, response) {if (error) {console.error(error);} else {console.log('API called successfully. Returned data: ' + data);}};apiInstance.imageOcrPhotoToText(imageFile, opts, callback);

Pick your recognition level (matched to the quality and skewing of your input image), the language, and of course the image itself. And that’s it! You now have OCR tech at your fingertips.

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