Skip to main content

Converts physical flashcards to digital anki flashcards

Project description

anki_ocr

anki_ocr is a python program that converts physical flashcards into digital Anki(Anki is a flashcard program that sychronizes your flashcards and uses spaced repetition for efficient memorization) decks. It uses PyTesseract and genanki to turn your handwritten flashcards into digital anki ones.

There are several use cases, mainly its for you if you have a lot of flashcards and and want to digitalize them. Anki does support image flashcards, but it would take a lot of time and you wouldn't be able to search the flashcards. Its also useful if you're not allowed to use a laptop/phone in class or prefer to handwrite your notes.

Installation

Use the package manager pip to install anki_ocr.

pip install anki_ocr

Usage

To use anki_ocr, you will need a directory with images of your flashcards. The program will automatically sort the images by date, so you should capture the question followed by its answer(i.e question1>answer1>question2>answer2 and so on), and ensure the number of images is even

anki_ocr [img_directory] [output_deck_name]

This will output an Anki deck package output_deck_name.apkg. This package can be imported into the Desktop or mobile Anki apps

Contributing

This project is beginner friendly. The entire module is a small single file, and the only new package you might have to deal with is genanki just to see some other ways to generate notes.

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT

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

anki_ocr-0.1.tar.gz (4.4 kB view details)

Uploaded Source

Built Distribution

anki_ocr-0.1-py3-none-any.whl (6.0 kB view details)

Uploaded Python 3

File details

Details for the file anki_ocr-0.1.tar.gz.

File metadata

  • Download URL: anki_ocr-0.1.tar.gz
  • Upload date:
  • Size: 4.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/39.0.1 requests-toolbelt/0.9.1 tqdm/4.36.0 CPython/3.6.8

File hashes

Hashes for anki_ocr-0.1.tar.gz
Algorithm Hash digest
SHA256 5199f100f3e15ed3f52201964000adccaeab6976c067c86371ec6ee4e96e2156
MD5 f108dd10d0af7a88dc43c6ffff1a3d56
BLAKE2b-256 748532b6773a12f399ccc2f8af08d62f4c55e051dc483ea082a067fddce1a8ee

See more details on using hashes here.

File details

Details for the file anki_ocr-0.1-py3-none-any.whl.

File metadata

  • Download URL: anki_ocr-0.1-py3-none-any.whl
  • Upload date:
  • Size: 6.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/39.0.1 requests-toolbelt/0.9.1 tqdm/4.36.0 CPython/3.6.8

File hashes

Hashes for anki_ocr-0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 bd841827a57b410698ca0c93a2f02376dc327ad634340a6555439766ce17ad42
MD5 5ed1666146901d144e4967063aa101c2
BLAKE2b-256 44894b4dfe3a48679422d52be95522184cada47ac9f7f2f8d10f46841e80f0e1

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