pypdfocr 0.4.1

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

PyPDFOCR

This program will help manage your scanned PDFs by doing 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

• New: Evernote auto-upload and filing based on keyword search

More links:

• Blog @ virantha.com

• Documentation @ documentup.com

• Source @ github

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:

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.

Evernote upload(new!):

Evernote authentication token

To enable Evernote support, you will need to get a developer token for your Evernote account.. You should note that this script will never delete or modify existing notes in your account, and limits itself to creating new Notebooks and Notes. Once you get that token, you copy and paste it into your configuration file as shown below

Evernote filing usage

To automatically upload the OCR’ed pdf to a folder based on a keyword, use the -e option instead of the -f auto filing option.

pypdfocr filename.pdf -e -c config.yaml

Similarly, you can also do this in folder monitoring mode:

pypdfocr -w watch_directory -e -c config.yaml

Evernote filing configuration file

The config file shown above only needs to change slightly. The folders section is completely unchanged, but note that target_folder is the name of your “Notebook stack” in Evernote, and the default_folder should just be the default Evernote upload notebook name.

target_folder: "evernote_stack"
default_folder: "default"
original_move_folder: "docs/originals"
evernote_developer_token: "YOUR_TOKEN"

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

Caveats

This code is brand-new, and incorporation of unit-testing is just starting. I plan to improve things as time allows in the near-future. Sphinx code generation is on my TODO list. The software is distributed on an “AS IS” BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

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:

• Tesseract OCR software https://code.google.com/p/tesseract-ocr/

• GhostScript http://www.ghostscript.com/

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

brew install tesseract
brew install ghostscript

Version	Date	Changes
v0.4.1	10/28/13	Made HOCR parsing more robust
v0.4.0	10/28/13	Added early Evernote upload support
v0.3.1	10/24/13	Path fix on windows
v0.3.0	10/23/13	Added filing of converted pdfs using a configuration file to specify target directories based on keyword matches in the pdf text
v0.2.2	10/22/13	Added a console script to put the pypdfocr script into your bin
v0.2.1	10/22/13	Fix to initial packaging problem.
v0.2.0	10/21/13	Initial release.

Todo list

• Add smtp emailing option after OCR

• Complete unit tests