Skip to main content

Toolkit for document image processing

Project description

Contextualization

In progress toolkit for document image pre processing.

Aimed for images to be OCRed.

Main Available methods

  • Auto rotate image

    Uses left margin of a document to calculate the angle of rotation present, and correct it accordingly.

    Can be given the rotation direction (clocwise or counter_clockwise), or in auto mode tries to determine the side to which the document is tilted (can be none, in which case image won't be rotated).

  • Calculate rotation direction

    Calculates rotation direction of an image by finding the biggest sets of the first black pixels appearances (with outliers removed) in the image for each direction: clockwise, counter_clockwise and none.

    For none direction, the set is created based on pixels with same 'x' coordinate that with less than a 5% height difference, relative to the image's height.

  • Binarize document

  • Split document into columns

    Analyzes document image pixel color frequency and split document image into columns.

  • Auto crop document

    Analyzes document image pixel color frequency and cut document margins, aiming mostly to remove possible folds in the corners.

  • Identify document images Identify document images in image, using algorithm available in leptonica's repository that finds potential image masks.

  • Get document delimiters Get document delimiters, using image transformations.

  • Segment document Segments document image into header, body and footer, using delimiters. Only the body is always guaranteed to have a value.

Bash commands:

  • binarize : binarize document image.

  • rotate_document : rotate document image.

  • split_columns : split document into column images.

  • d_auto_crop : auto crop document image.

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

document_image_utils-0.1.21.tar.gz (31.2 kB view details)

Uploaded Source

Built Distribution

document_image_utils-0.1.21-py3-none-any.whl (36.3 kB view details)

Uploaded Python 3

File details

Details for the file document_image_utils-0.1.21.tar.gz.

File metadata

  • Download URL: document_image_utils-0.1.21.tar.gz
  • Upload date:
  • Size: 31.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.10.12 Linux/5.10.16.3-microsoft-standard-WSL2

File hashes

Hashes for document_image_utils-0.1.21.tar.gz
Algorithm Hash digest
SHA256 10dab34d9e2373c40f551ad709ae097dc7ec6648d9c82765a53263c09c4c74b6
MD5 a8dc9d528bd834afe826b895254900cf
BLAKE2b-256 dd4a7bdaf3e25a77be698c07616bc27b5fb07b23b73c525024c86afdc5f5eda7

See more details on using hashes here.

File details

Details for the file document_image_utils-0.1.21-py3-none-any.whl.

File metadata

  • Download URL: document_image_utils-0.1.21-py3-none-any.whl
  • Upload date:
  • Size: 36.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.10.12 Linux/5.10.16.3-microsoft-standard-WSL2

File hashes

Hashes for document_image_utils-0.1.21-py3-none-any.whl
Algorithm Hash digest
SHA256 284d0d69296121822f48d224b1856f70b0f6a1ad8ac031da096bd72b541fb09d
MD5 f5ad2888378f896b4a813bdeff50f157
BLAKE2b-256 b02e10a7e58e02743df7aa0852fb9789e6845de606ce96fae521be871d0bf9b5

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