Language detecton

To use language detection, install (aspose-ocr-language-classification-v1) advanced OCR model to your project.

Aspose.OCR for Java can automatically identify the following languages and language families used on the provided image using DetectLanguages method:

• Latin
• Cyrillic
• Arabic
• Chinese
• Japanese
• Korean
• Hindi
• Tamil
• Telugu
• Kannada

The method accepts the collection of images in any of the supported formats and returns them as a list of LanguageDetectionOutput objects with the following properties:

Property	Type	Description
source	string	The full path or URL of the source file. If the file is provided as a BufferedImage, InputStream, an array of pixels, or a Base64 string, this value will be empty.
page	int	Page number. When working with single-page images, this value is always 0.
languages	List<Map.Entry<Language, Float>>	Lists the recognition languages detected in the image along with their probabilities.

Example

The following code sample demonstrates how to detect the image languages:

OcrInput input = new OcrInput(InputType.SingleImage);
input.add("source.png");
LanguageDetectionOutput result = api.DetectLanguages(input).get(0);
out.println("File: " + result.source);
out.println("Page: " + result.page);
for(Map.Entry<Language, Float> l : result.languages)
out.println("Language: " + l.getKey()+ " : " + l.getValue());

The following code sample demonstrates how to recognize the image with auto detection languages:

AsposeOCR recognitionEngine = new AsposeOCR();
// Add an image to OcrInput object
OcrInput input = new OcrInput(InputType.SingleImage);
input.add("source.png");
// Set language detection and it is level.
RecognitionSettings settings = new RecognitionSettings();
settings.setLanguage(com.aspose.ocr.models.Language.Auto);
settings.setLanguageDetectionLevel(LanguageDetectionLevel.BY_PARAGRAPH);
		
// Recognize with detect languages
List<RecognitionResult> result = recognitionEngine.Recognize(input, );
for (RecognitionResult item : result)
{
    System.out.println("Text: "+item.recognitionText);
}