Skip to main content

Aspose.OCR for Python is a powerful yet easy-to-use and cost-effective API for extracting text from scanned images, photos, screenshots, PDF documents, and other files.

Project description

Product Page | Documentation | Demos | Blog | API Reference | Search | Free Support | Temporary License

Try our Free Online Apps demonstrating some of the most popular Aspose.OCR functionality.

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)

Product Page | Documentation | Demos | Blog | API Reference | Search | Free Support | Temporary License

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

aspose_ocr_models_handwritten_python_net-23.12.1-py3-none-win_amd64.whl (59.3 MB view details)

Uploaded Python 3 Windows x86-64

aspose_ocr_models_handwritten_python_net-23.12.1-py3-none-win32.whl (55.7 MB view details)

Uploaded Python 3 Windows x86

File details

Details for the file aspose_ocr_models_handwritten_python_net-23.12.1-py3-none-win_amd64.whl.

File metadata

File hashes

Hashes for aspose_ocr_models_handwritten_python_net-23.12.1-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 c5af5d2ed93601fb7a90116bd77792e8dde8fe54e3bf7aafe72b80b6fc35a2ba
MD5 7d32d229b63f095956846ffa308bb727
BLAKE2b-256 925be363d5abb5f6e9be9367a90b5b7bada85ce7add5d99e9a13baea6e5d8150

See more details on using hashes here.

File details

Details for the file aspose_ocr_models_handwritten_python_net-23.12.1-py3-none-win32.whl.

File metadata

File hashes

Hashes for aspose_ocr_models_handwritten_python_net-23.12.1-py3-none-win32.whl
Algorithm Hash digest
SHA256 d8e057087813e77c62361d1bfa15ab308f1adbf6797af126190a7039d3b4bc5c
MD5 efcb6b57250e3ce8ab450daf383149d5
BLAKE2b-256 92e224f7827ff401866163881792eef7c8854be5f045476a302691f1bc4410ab

See more details on using hashes here.

File details

Details for the file aspose_ocr_models_handwritten_python_net-23.12.1-py3-none-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for aspose_ocr_models_handwritten_python_net-23.12.1-py3-none-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 22dfec8ad0e72916c208ee1344ed8fd8fd390b87a533b3d338bf02b43fe930b1
MD5 2a455f202750d6a7459bea684bf76468
BLAKE2b-256 bb2c7832be8ea3ed11412fe9ff6fcda71a486160ef1fc109b4c2f953bb65dee4

See more details on using hashes here.

File details

Details for the file aspose_ocr_models_handwritten_python_net-23.12.1-py3-none-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for aspose_ocr_models_handwritten_python_net-23.12.1-py3-none-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 6d9ba5059e99b4ec84b6cd5fd4782d09ea6d7232ba31ddcb3ed84e3d6c39ff81
MD5 350c285af195a6aaf24d990a9e8cc471
BLAKE2b-256 a898b6dfee799ca3a1268f0553e9c6fd58739ff8c65a6ca203c203f0c0b94730

See more details on using hashes here.

File details

Details for the file aspose_ocr_models_handwritten_python_net-23.12.1-py3-none-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for aspose_ocr_models_handwritten_python_net-23.12.1-py3-none-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 dda713949d1082aa1416f347c6d6b21e2ee5c030556dfaf56f1dc11859d6b941
MD5 7e0e8687336e07859592db679cd3061b
BLAKE2b-256 91688d1c74061dd6c5d3b8cc068a13c3e7644811331485a9b69452991a3df68c

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page