Aspose.OCR for Python via .NET 25.11.0 - Release Notes

What was changed

Public API changes and backwards compatibility

This section lists all public API changes introduced in Aspose.OCR for Python via .NET 25.11.0 that November affect the code of existing applications.

Added public APIs:

The following public APIs have been introduced in this release:

RecognizeFormula(OcrInput input, boolean detectAreas) method

A specialized recognition method for extracting and recognizing formulas from images.

RecognizeFormula() method has parameter:

• boolean detectAreas If set to true, automatically detects and isolates formula regions before performing recognition. If false, processes the entire image as a formula.

OCRTable class

Represents the full result of table recognition for all processed pages.

OCRTablePage class

Represents table recognition results for a single page. A page consists of multiple rows extracted from the recognized table.

OCRTableRow class

A row contains a collection of cells, each holding text from a corresponding column.

OCRTableCell class

Represents a single table cell. A cell contains recognized text and its position in the row.

Updated public APIs:

The following public APIs have been changed in Aspose.OCR for Java 25.11.0 release:

Format enumeration

Aspose.OCR for Java can now output csv files:

OcrOutput class with method getTableData()

Aspose.OCR for Java can now output table data:

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:

DetectAreasMode.FORMULA

# Instantiate Aspose.OCR API
api = AsposeOcr()
# Add image to the recognition
input = OcrInput(InputType.SINGLE_IMAGE)
input.add("source1.png")

# Set areas detection mode
recognitionSettings = RecognitionSettings()
recognitionSettings.detect_areas_mode = DetectAreasMode.FORMULA
# Recognize the image
results = api.recognize(input, recognitionSettings)

# Print recognition result
for result in results:
    print(result.recognition_text)

RecognizeFormula(OcrInput images, bool detectAreas = true)

# Instantiate Aspose.OCR API
api = AsposeOcr()
# Add image to the recognition
input = OcrInput(InputType.SINGLE_IMAGE)
input.add("source1.png")

# Recognize formulas with areas detection
results = api.recognize_formula(input, True)
# Parameter bool detectAreas - if set to true, automatically detects and isolates formula regions before performing recognition. If false, processes the entire image as a formula.

# Print recognition result
for result in results:
    print(result.recognition_text)

DetectAreasMode.TABLE and GetTableData

The following code example shows how to extract text from table and get rows and columns structure:

# Instantiate Aspose.OCR API
api = AsposeOcr()
# Add image to the recognition
input = OcrInput(InputType.SINGLE_IMAGE)
input.add("source1.png")

# Set areas detection mode
recognitionSettings = RecognitionSettings()
recognitionSettings.detect_areas_mode = DetectAreasMode.TABLE
# Recognize the image
results = api.recognize(input, recognitionSettings)

# Print recognition result
for result in results:
    print(result.recognition_text)

# Print table rows cloumns
 table =  results.get_table_data()
        for page in table.pages:
            print("page:" + str(page.page_index))
            for row in page.rows:
                print("row:" + str(row.row_index))
                for cell in row.cells:
                    print("cell:" + str(cell.column_index)+": "+cell.text)

Save results as CSV file

# Recognize the image
results = api.recognize(input)
# Save recognition result
results.save("result.csv", SaveFormat.CSV)