aspose-ocr-models-handwritten-python-net 23.12.1

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Aspose.OCR.Models.Handwritten for Python via .NET This extension to Aspose.OCR for Python via.NET adds a recognition model and associated methods designed for extracting handwritten text from images. It supports a number of European languages based on Extended Lain alphabet. Handwritten recognition has various business, government and personal applications:

• Extract text from handwritten notes and letters.
• Convert handwritten historical records and documents into digital formats for archival purposes.
• Parse resumes and employee records.
• Analyze information from handwritten inventory lists to maintain accurate and up-to-date databases.
• Analyze handwritten customer feedback and reviews to gain insights into customer preferences.
• And many more.

Important considerations:

• This package requires Aspose.OCR for Python via .NET to function properly. It cannot be used separately from the core API.
• The model only works with Extended Latin letters and numbers. Check Aspose.OCR for .NET documentation (https://docs.aspose.com/ocr/python-net/) for more details.

Get Started

Run pip install aspose-ocr-python-net and pip install aspose-ocr-models-handwritten-python-net to fetch the package. If you already have Aspose.OCR for Python via .NET and want to get the latest version, please run pip install --upgrade aspose-ocr-python-net.

To learn more about Aspose.OCR for Python via .NET and explore the basic requirements and features of the library, check out the following Aspose.OCR for Python via .NET Documentation pages for other use cases.

Code snippet

Aspose.OCR for Python via .NET is extremely easy to use, regardless of the application's scale and complexity. Let's try to create a very simple application that can extract text from images and output it to the console.

1. Install the latest version of the aspose-ocr package using pip.
2. Import aspose.ocr module into the application.
3. Create an instance of AsposeOcr class.
4. Create an instance of OcrInput class and add one or more images to it.
5. Extract text from the image with handwritten text using recognize_handwritten_text method.
6. Output the extracted text to the console.

Full code:

import aspose.ocr as ocr

# Initialize OCR engine
api = AsposeOcr()

# Initialize OCR input
input = OcrInput(InputType.SINGLE_IMAGE)
input.add("1.png")
input.add("2.jpg")

# Recognize images
result = api.recognize_handwritten_text(input)

# Print result
print(result[0].recognition_text)
print(result[1].recognition_text)

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