Table recognition

Aspose.OCR for Python via .NET now provides a dedicated API for detecting table layout and recognizing table data in images, scanned documents, screenshots, or photos. To extract table text, simply call the universal aspose.ocr.AsposeOcr.recognize method with DetectAreasMode.TABLE settings.

This method accepts an OcrInput object and optional recognition settings.

Recognition results are returned as a list of aspose.ocr.RecognitionResult objects. Each result contains extracted table data, detected regions, and allows exporting to various formats. Additionally, you can retrieve the table’s row and column structure using the get_table_data() method.

Example

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)