Skip to main content

Fast and accurate OCR on images and PDFs using Apple Vision framework directly from command line.

Project description

Apple Vision Framework Python Utilities

Fast and accurate OCR on images and PDFs using Apple Vision framework (pyobjc-framework-Vision) directly from command line.

Features

  • Fast and accurate, multi-language support (-l, --lang), powered by Apple's industry-strength Vision framework (pyobjc-framework-Vision).
  • Supports all common input image formats: PNG, JPEG, TIFF and WebP.
  • Supports PDF input (the file gets converted to images first). This tool does NOT assume a file is PDF just because it has a .pdf extension, you need to pass -p, --pdf flag.
  • Outputs extracted text only by default, but can output in JSON format containing confidence of recognition for each line with -j, --json flag.

Demo

Below is the output of running the tests:

https://g.teddysc.me/96d5b1217b90035c163b3c97ce99112f

Installation

Requires Python >= 3.11, <4.0.

Since this package uses Apple's Vision framework, it only works on macOS.

To OCR PDFs with -p, you need to install required dependency poppler with brew install poppler (detailed guide).

pipx

This is the recommended installation method.

$ pipx install apple-vision-utils

pip

$ pip install apple-vision-utils

Usage

$ apple-ocr --help

usage: apple-ocr [-h] [-j] [-p] [-l LANG] [--pdf2image-only]
                 [--pdf2image-dir PDF2IMAGE_DIR] [-V]
                 file_path

Extract text from an image or PDF using Apple's Vision framework.

positional arguments:
  file_path             Path to the image or PDF file.

options:
  -h, --help            show this help message and exit
  -j, --json            Output results in JSON format.
  -p, --pdf             Specify if the input file is a PDF.
  -l LANG, --lang LANG  Specify the language for text recognition (e.g., eng,
                        fra, deu, zh-Hans for Simplified Chinese, zh-Hant for
                        Traditional Chinese). Default is 'zh-Hant', which
                        works with images containing both Chinese characters
                        and latin letters.
  --pdf2image-only      Only convert PDF to images without performing OCR.
  --pdf2image-dir PDF2IMAGE_DIR
                        Specify the directory to store output images. By
                        default, a secure temporary directory is created.
  -V, --version         show program's version number and exit

Develop

$ git clone https://github.com/tddschn/apple-vision-utils.git
$ cd apple-vision-utils
$ poetry install

Test

# in the root of the project
poetry install
poetry shell
cd tests && ./test.sh

Project details


Download files

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

Source Distribution

apple_vision_utils-0.1.4.tar.gz (3.7 kB view details)

Uploaded Source

Built Distribution

apple_vision_utils-0.1.4-py3-none-any.whl (4.7 kB view details)

Uploaded Python 3

File details

Details for the file apple_vision_utils-0.1.4.tar.gz.

File metadata

  • Download URL: apple_vision_utils-0.1.4.tar.gz
  • Upload date:
  • Size: 3.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.7.1 CPython/3.12.3 Darwin/23.4.0

File hashes

Hashes for apple_vision_utils-0.1.4.tar.gz
Algorithm Hash digest
SHA256 645eb7dfc60912df54a0a07203f16207520a2eb06f30d3bc26dad22a6ee375cd
MD5 d7911371a7c36033f25c02557f03a115
BLAKE2b-256 f7a70e9e81f42ac3f73b3e7fc5bedd7993e61713f0ffe422ef6213e2900ccb79

See more details on using hashes here.

File details

Details for the file apple_vision_utils-0.1.4-py3-none-any.whl.

File metadata

File hashes

Hashes for apple_vision_utils-0.1.4-py3-none-any.whl
Algorithm Hash digest
SHA256 13849b2c4f2b54c7ac94eb833cee1108b6f04e1f6b2b5d0f1138026f78dc067a
MD5 d7ccda3175fe5037f7af195b65838375
BLAKE2b-256 7ae1328b03ce89cc3875392cb73c6887088684085b071f83235751f69c2e3914

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