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.

Seamlessly integrate advanced optical character recognition into your Python projects with ease. Designed for all-in-one functionality and developer-friendly simplicity, this solution enables you to convert images, scans, PDFs, illustrations, and screenshots into accurate, editable, and searchable text with just a few lines of code. Convert scanned documents into searchable, indexable PDFs, extract and compare text from images, and streamline workflows with unmatched precision and performance. Aspose OCR API is suitable for prototypes, cross-platform applications, and cloud services.

What is optical character recognition (OCR)?

Optical Character Recognition (OCR) is a technology that converts images of printed or handwritten text into machine-readable, editable, and searchable digital text. By analyzing shapes and patterns within an image, OCR identifies characters—letters, numbers, and symbols—and translates them into text that computers can process. This powerful technology enables the extraction of information from physical documents, images, and forms, transforming them into actionable digital data. OCR also plays a vital role in accessibility, providing visually impaired individuals access to text through screen readers and other assistive technologies.

Recognition languages

Aspose OCR is the perfect solution for global applications and multi-lingual documents. With support for nearly all languages, it ensures accurate text extraction across a wide range of scripts and alphabets. Our engine excels at handling mixed-language documents, such as those featuring both Chinese and English, and can automatically detect the language of the input text during recognition.

  • Extended Latin (English, French, German, Spanish, Portuguese, and other European languages)
  • Cyrillic (Russian, Ukrainian, Bulgarian, and more)
  • Arabic and Persian
  • Chinese
  • Hindi and other Devanagari-based scripts
  • Korean
  • Japanese

Aspose OCR can also extract text from handwritten notes and street photos.

Key features

  • Universal – Effortlessly extract text from any image, whether it's a high-quality scan or a casual street photo, captured via scanner or camera.
  • Fast – Achieve rapid text recognition, processing a page in just seconds with minimal resource consumption. Adjust recognition speed, quality, and resource usage according to your specific needs.
  • Developer-friendly – With just a few lines of code, easily convert images to text, create searchable PDFs, save recognition results to documents, and more, integrating OCR into your workflows seamlessly.
  • Modular – Maintain a lean and efficient application by selectively incorporating advanced features from our comprehensive resource repository.
  • Reliable – Experience exceptional recognition accuracy, even with challenging images that are blurry, rotated, distorted, or noisy.

Supported file formats

Aspose OCR can handle nearly any file format from scanners or cameras, including:

  • JPEG, PNG, BMP, and GIF images
  • Single-page and multi-page TIFF files
  • PDF documents
  • DjVu files

All above-mentioned files can be read directly from web links. You can also use Aspose OCR to perform bulk recognition on images within folders and archives, streamlining large-scale document processing.

The recognition results are returned in popular file and data exchange formats, enabling easy storage, database import, or real-time analysis:

  • Plain Text
  • Searchable PDF
  • Microsoft Word or Excel documents
  • HTML
  • RTF
  • ePUB
  • JSON and XML
  • Markdown

Platforms

  • Windows
  • Linux
  • macOS

Developer-friendly

Aspose OCR is designed by developers for developers, offering a straightforward and intuitive interface. You only need 6 lines of code to convert image to text:

import aspose.ocr as ocr
# Initialize OCR engine
api = AsposeOcr()
# Add images to recognition batch
input = OcrInput(InputType.SINGLE_IMAGE)
input.add("1.png")
# Recognize images
results = api.recognize(input)
# Print result
print(results[0].recognition_text)

Licensing

You can begin using the Aspose OCR library immediately after installation. In evaluation mode (without providing a license), you can recognize text in any supported language and save recognition results in all supported formats, with a few limitations:

  • If the number of characters in a recognized image exceeds 300, only the first 300 characters will be recognized.
  • If the number of characters is fewer than 300, only the first 60% of the characters will be recognized.

To unlock all features, request a temporary license, which removes all trial limitations for 30 days. This gives you the opportunity to build a fully functional OCR application and evaluate Aspose.OCR before making your final purchase decision.

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

If you're not sure about the file name format, learn more about wheel file names.

aspose_ocr_python_net-26.1.0-py3-none-win_amd64.whl (126.5 MB view details)

Uploaded Python 3Windows x86-64

aspose_ocr_python_net-26.1.0-py3-none-win32.whl (121.8 MB view details)

Uploaded Python 3Windows x86

aspose_ocr_python_net-26.1.0-py3-none-macosx_11_0_arm64.whl (131.1 MB view details)

Uploaded Python 3macOS 11.0+ ARM64

aspose_ocr_python_net-26.1.0-py3-none-macosx_10_14_x86_64.whl (136.1 MB view details)

Uploaded Python 3macOS 10.14+ x86-64

File details

Details for the file aspose_ocr_python_net-26.1.0-py3-none-win_amd64.whl.

File metadata

File hashes

Hashes for aspose_ocr_python_net-26.1.0-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 8447567c6ff8c24ce4554b7e41060dae1c6c8259d734c1ef9a47cb2928b3d73d
MD5 a3cb9e0f5bae268d37df1eabcd90b67a
BLAKE2b-256 ce63f5d173f05af70c786ea49207dc592d3c7730c2d5d1852560eae47913c12e

See more details on using hashes here.

File details

Details for the file aspose_ocr_python_net-26.1.0-py3-none-win32.whl.

File metadata

File hashes

Hashes for aspose_ocr_python_net-26.1.0-py3-none-win32.whl
Algorithm Hash digest
SHA256 f139de23f2a1d42c028861cf0ab3c420b450ccebf0c9cdb6623108dec453f8bd
MD5 74c8539400397b9fa3906ea8b53ee44a
BLAKE2b-256 a0cf5f54d8f175608ba0d1607213c746233124e561d7b40e16580283f8835bef

See more details on using hashes here.

File details

Details for the file aspose_ocr_python_net-26.1.0-py3-none-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for aspose_ocr_python_net-26.1.0-py3-none-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 bbeab02cc6a1677c2275773fcae596875227226e8a6f5f6ced611ee14c9db7bd
MD5 fc3ecc67a7e707bb2c5bd8d9d634da22
BLAKE2b-256 3515358fe78cd7a898862618f7526892d4107ee1a41b5a4e8b0d6e9f37643b92

See more details on using hashes here.

File details

Details for the file aspose_ocr_python_net-26.1.0-py3-none-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for aspose_ocr_python_net-26.1.0-py3-none-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7682ade30e86c7d38205799e07bb8ba634b32097a5aa60e5ed967c81298c46c1
MD5 aefcb0fe518d84b85d9bcbeef1f544a0
BLAKE2b-256 9c138ebedfa6915abeb025766130e99159f1f0f00c6939551cdf2cf0994d0190

See more details on using hashes here.

File details

Details for the file aspose_ocr_python_net-26.1.0-py3-none-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for aspose_ocr_python_net-26.1.0-py3-none-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 1b53e9e6c9025f323c3840ddfffb8b45ad76b140c7ade617f8cae16fdccedb72
MD5 76053e6781302ec9ba65f7b557cda995
BLAKE2b-256 8be2c8d6942cd2c2e00968cfda98925b6d03939c0c6eb3513db92fcb98aeb907

See more details on using hashes here.

Supported by

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