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Aspose.OCR for Python via .NET 25.9.0 - Release Notes

What was changed

KeySummaryCategory
OCRNET‑1097Improve markdown output format with table detection.New feature
OCRNET‑1093HOCR export to MemoryStream and incompatibility with Aspose.PDF conversion.Bug fix

Public API changes and backwards compatibility

This section lists all public API changes introduced in Aspose.OCR for Python via .NET 25.9.0 that September affect the code of existing applications.

Added public APIs:

No changes.

Updated public APIs:

The following public APIs have been updated in Aspose.OCR for .NET 25.9.0 release:

aspose.ocr.ai.TableAIProcessor class

🛠 Constructors

    # Initializes a new instance of the TableAIProcessor class
    TableAIProcessor(mode) #AITableDetectionMode

Aspose.OCR for Python vis .NET can now automatically detect tables and save them in Markdown format.

New Methods

MethodDescription
save_md(path)Saves the extracted structured tables into a Markdown (.md) file.

aspose.ocr.OcrOutput class

The save(full_file_name, save_format) method has been enhanced: now the Markdown output also supports automatic table detection and insertion.

Deprecated APIs

The following public APIs have been marked as deprecated and will be removed in 25.10.0 (October 2025) release:

RectangleOutput class

AsposeOcr.detect_rectangles method

RecognitionResult.recognition_areas_text

RecognitionResult.recognition_areas_rectangles

RecognitionResult.skew

CharacterRecognitionResult.image_index

SkewOutput.image_index

RecognitionResult.skew

RecognitionResult.skew

RecognitionResult.skew

Removed public APIs:

No changes.

Examples

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

Enable Table AI postprocessor

from aspose.ocr import *
from aspose.ocr.ai import *
from aspose.ocr.models import *


# Initialize recognition API
api = AsposeOcr()

# Add an image to OcrInput object
input = OcrInput(InputType.SINGLE_IMAGE)
input.add("source.png")

# Recognize image
results = api.recognize(input)

# Initialize AI API
ai = AsposeAI()
config = AsposeAIModelConfig()
proces = TableAIProcessor(AITableDetectionMode.AUTO)
ai.set_post_processor(proces, config)
ai.run_postprocessor(result)
corrected = proces.get_result()
print(corrected[0].recognition_text)
ai.free_resources()