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Aspose.OCR for Python via .NET 24.11.1 - Release Notes

Deprecation warning

What was changed

KeySummaryCategory
OCRPY‑76Added an experimental OCR model for extracting mixed-language Cyrillic/English texts.New feature
OCRPY‑76Added support for recognizing mixed-language Telugu/English texts.New feature
OCRPY‑76Added support for recognizing mixed-language Tamil/English texts.New feature
OCRPY‑76Added support for recognizing mixed-language Kannada/English texts.New feature
OCRPY‑76Added universal recognition of Indic texts based on Devanagari script, including mixed Devanagari/English texts.Enhancement
n/aAdded universal recognition of Chinese/English texts (language-agnostic).Enhancement

Public API changes and backwards compatibility

This section lists all public API changes introduced in Aspose.OCR for Python via .NET 24.11.1 that may affect the code of existing applications.

Added public APIs:

No changes.

Updated public APIs:

The following public APIs have been changed in Aspose.OCR for Python via .NET 24.11.1 release:

Language

Aspose.OCR for .NET can now extract texts in the following languages:

ValueAlphabet
Language.CHINESEUniversal model for all Chinese languages. Mixed-language Chinese/English texts also supported.
Language.DEVANAGARI
Language.Indic
Universal model for all Indic texts based on Devanagari script, including mixed Devanagari/English texts.
Language.EUROPEANMixed-language Cyrillic/English texts.
Language.KANMixed-language Kannada/English texts.
Language.TAMMixed-language Tamil/English texts.
Language.TELMixed-language Telugu/English texts.

Removed public APIs:

No changes.

Examples

The code samples below illustrate the changes introduced in this release:

Mixed-language Cyrillic/English OCR

# Instantiate Aspose.OCR API
api = AsposeOcr()
# Add image to the recognition batch
input = OcrInput(InputType.SINGLE_IMAGE)
input.add("source.png")
# Recognize mixed Cyrillic/English text
recognitionSettings = RecognitionSettings()
recognitionSettings.language = Language.EUROPEAN
# Extract text from image
result = api.recognize(input, recognitionSettings)
# Print recognition result
print(result[0].recognition_text)
input("Press Enter to continue...")