Metadata-Version: 2.1
Name: OCRfixr
Version: 1.3.4
Summary: A contextual spellchecker for OCR output
Home-page: https://github.com/ja-mcm/ocrfixr
Author: Jack McMahon
Author-email: OCRfixr@mcmahon.work
License: GNU General Public License v3
Description: <img src=https://img.shields.io/badge/python-3.6%20%7C%203.7%20%7C%203.8-blue alt="python versions supported">
        
        # OCRfixr
        
        ## OVERVIEW 
        This project aims to help automate the challenging work of manually correcting OCR output from Distributed Proofreaders' book digitization projects
        
        
        ## Correcting OCR Misreads
        OCRs can sometimes mistake similar-looking characters when scanning a book. For example, "l" and "1" are easily confused, potentially causing the OCR to misread the word "learn" as "1earn".
        
        As written in book: 
        > _"The birds flevv south"_
        
        Corrected text:
        > _"The birds flew south"_
        
        ### How OCRfixr Works:
        OCRfixr fixes misreads by checking __1) possible spell corrections__ against the __2) local context__ of the word. For example, here's how OCRfixr would evaluate the following OCR mistake:
        
        As written in book: 
        > _"Days there were when small trade came to the __stoie__. Then the young clerk read._"
        
        | Method | Plausible Replacements |
        | --------------- | --------------- | 
        | Spellcheck (symspellpy) | stone, __store__, stoke, stove, stowe, stole, soie |
        | Context (BERT) | market, shop, town, city, __store__, table, village, door, light, markets, surface, place, window, docks, area |
        
        Since there is match for both a plausible spellcheck replacement and that word reasonably matches the context of the sentence, OCRfixr updates the word. 
        
        Corrected text:
        > _"Days there were when small trade came to the __store__. Then the young clerk read._"
        
        For very common scanning errors where it is clear what the word should have been (ex: 'onlv' --> 'only'), OCRfixr skips the context check and relies solely on a static mapping of common corrections. This helps to maximize the number of successful edits \& decrease compute time. (You can disable this by setting common_scannos to "F").
        
        ### Using OCRfixr
        
        The package can be installed using [pip](https://pypi.org/project/OCRfixr/). 
        
        ```bash
        pip install OCRfixr
        ```
        
        By default, OCRfixr only returns the original string, with all changes incorporated:
        ```python
        >>> from ocrfixr import spellcheck
        
        >>> text = "The birds flevv south"
        >>> spellcheck(text).fix()
        'The birds flew south'
        ```
        
        Use __return_fixes__ to also include all corrections made to the text, with associated counts for each:
        ```python
        >>> spellcheck(text, return_fixes = "T").fix()
        ['The birds flew south', {("flevv","flew"):1}]
        ```
        
        _(Note: OCRfixr resets its BERT context window at the start of each new paragraph, so splitting by paragraph may be a useful debug feature)_
        
        
        ### Interactive Mode
        OCRfixr also has an option for the user to interactively accept/reject suggested changes to the text:
        
        ```python
        >>> text = "The birds flevv down\n south, but wefe quickly apprehended\n by border patrol agents"
        >>> spellcheck(text, interactive = "T").fix()
        ```
        
        <img width="723" alt="Suggestion 1" src="https://user-images.githubusercontent.com/67446041/107133270-7918c300-68b4-11eb-9de5-5b6282510c16.png">
        
        Each suggestion provides the local context around the garbled text, so that the user can determine if the suggestion fits.
        
        <img width="723" alt="Suggestion 2" src="https://user-images.githubusercontent.com/67446041/115068768-af7c4b00-9ec0-11eb-9c7a-65b518718ec4.png">
        
        ```python
        >>> ### User accepts change to "flevv", but rejects change to "wefe" in GUI
        'The birds flew down\n south, but wefe quickly apprehended\n by border patrol agents'
        ```
        
        This returns the text with all accepted changes reflected. All rejected suggestions are left as-is in the text.
        
        
        ### Avoiding "Damn You, Autocorrect!"
        By design, OCRfixr is change-averse:
        - If spellcheck/context do not line up, no update is made.
        - Likewise, if there is >1 word that lines up for spellcheck/context, no update is made.
        - Only the top 15 context suggestions are considered, to limit low-probability matches.
        - If the suggestion is a homophone of the original word, it is ignored  (original: coupla --> suggestion: couple). These are assumed to be 'stylistic' or phonetic misspellings
        - Proper nouns (anything starting with a capital letter) are not evaluated for spelling.
        
        Word context is drawn from all sentences in the current paragraph (designated by a '\n'), to maximize available information, while also not bogging down the BERT model. 
        
        
        
        ## Credits
        
        - __symspellpy__ powers spellcheck suggestions
        - __transformers__ does the heavy lifting for BERT context modelling
        - __DataMunging__ provided a very useful list of common scanning errors 
        - __SCOWL__ word list is Copyright 2000-2019 by Kevin Atkinson.
        - This project was created to help __Distributed Proofreaders__. Support them here: <https://www.pgdp.net/c/>
Keywords: ocrfixr,spellcheck,OCR,contextual,BERT
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6, <3.9
Description-Content-Type: text/markdown
