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Converts a scanned PDF into an OCR'ed pdf using Tesseract-OCR and Ghostscript

Project description

This program will help manage your scanned PDFs for you. It can do the following:

  • Take a scanned PDF file and run OCR on it (using free OCR tools), generating a searchable PDF

  • Optionally, watch a folder for incoming scanned PDFs and automatically run OCR on them

  • Optionally, file the scanned PDFs into directories based on simple keyword matching that you specify

  • Coming soon: Evernote auto-upload and filing

More links:

Usage:

Single conversion:

pypdfocr filename.pdf

--> filename_ocr.pdf will be generated

Folder monitoring:

pypdfocr -w watch_directory

--> Every time a pdf file is added to `watch_directory` it will be OCR'ed

Automatic filing (new!):

To automatically move the OCR’ed pdf to a directory based on a keyword, use the -f option and specify a configuration file (described below):

pypdfocr filename.pdf -f -c config.yaml

You can also do this in folder monitoring mode:

pypdfocr -w watch_directory -f -c config.yaml

Configuration file for automatic PDF filing

The config.yaml file above is a simple folder to keyword matching text file. It determines where your OCR’ed PDFs (and optionally, the original scanned PDF) are placed after processing. An example is given below:

target_folder: "docs/filed"
default_folder: "docs/filed/manual_sort"
original_move_folder: "docs/originals"

folders:
    finances:
        - american express
        - chase card
        - internal revenue service
    travel:
        - boarding pass
        - airlines
        - expedia
        - orbitz
    receipts:
        - receipt

The target_folder is the root of your filing cabinet. Any PDF moving will happen in sub-directories under this directory.

The folders section defines your filing directories and the keywords associated with them. In this example, we have three filing directories (finances, travl, receipts), and some associated keywords for each filing directory. For example, if your OCR’ed PDF contains the phrase “american express” (in any upper/lower case), it will be filed into docs/filed/finances

The default_folder is where the OCR’ed PDF is moved to if there is no keyword match.

The original_move_folder is optional (you can comment it out with # in front of that line), but if specified, the original scanned PDF is moved into this directory after OCR is done. Otherwise, if this field is not present or commented out, your original PDF will stay where it was found.

If there is any naming conflict during filing, the program will add an underscore followed by a number to each filename, in order to avoid overwriting files that may already be present.

Caveats

This code is brand-new, and is barely commented with no unit-tests included. I plan to improve things as time allows in the near-future. Sphinx code generation is on my TODO list.

Installation

Using pip

PyPDFOCR is available in PyPI, so you can just run:

pip install pypdfocr

You will also need to install the external dependencies listed below. For those on Windows, because it’s such a pain to get all the PIL and PDF dependencies installed, I’ve gone ahead and made an executable called pypdfocr.exe

You still need to install Tesseract and GhostScript as detailed below in the dependencies list.

Manual install

Clone the source directly from github (you need to have git installed):

git clone https://github.com/virantha/pypdfocr.git

Then, install the following third-party python libraries: - PIL (Python Imaging Library) http://www.pythonware.com/products/pil/ - ReportLab (PDF generation library) http://www.reportlab.com/software/opensource/ - Watchdog (Cross-platform fhlesystem events monitoring) https://pypi.python.org/pypi/watchdog - PyPDF2 (Pure python pdf library)

These can all be installed via pip:

pip install pil
pip install reportlab
pip install watchdog
pip install pypdf2

You will also need to install the external dependencies listed below.

External Dependencies:

PyPDFOCR relies on the following (free) programs being installed and in the path:

On Mac OS X, you can install these using homebrew:

brew install tesseract
brew install ghostscript

Project details


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