normcap 0.2.5

OCR-powered screen-capture tool to capture information instead of images.

NormCap

OCR powered screen-capture tool to capture information instead of images.

Links: Repo | PyPi | Releases | Changelog | FAQs

Content: Quickstart | Python package | Usage | Contribute | Credits

Features

• On-screen recognition of selected text
• Multi platform support for Linux, Windows, MacOS
• Multi monitor support, incl. HDPI displays
• "Magically" parsing the text (optional, on by default)
• Show notifications (optional)
• Stay in system tray (optional)
• Check for updates (optional, off by default)

Quickstart

❱❱ Download & run a pre-build package for Linux, MacOS or Windows ❰❰

If you experience issues please look at the FAQs or open an issue.

(On MacOS, allow the unsigned application on first start: "System Preferences" → "Security & Privacy" → "General" → "Open anyway". You might also need to allow NormCap to take screenshots.)

Python package

As an alternative to a pre-build package you can install the NormCap Python package:

On Linux

# Install dependencies (Ubuntu/Debian)
sudo apt install tesseract-ocr tesseract-ocr-eng \
                 libtesseract-dev libleptonica-dev \
                 python3-dev

## Install dependencies (Arch)
sudo pacman -S tesseract tesseract-data-eng leptonica

## Install dependencies (Fedora)
sudo dnf install tesseract tesseract-devel \
                 libleptonica-devel python3-devel

# Install normcap
pip install normcap

# Run
./normcap

On MacOS

# Install dependencies
brew install tesseract tesseract-lang

# Install normcap
pip install normcap

# Run
./normcap

On Windows

1. Install "Tesseract 4.1", e.g. by using the installer provided by UB Mannheim.

2. Set the environment variable TESSDATA_PREFIX to Tesseract's data folder, e.g.:

setx TESSDATA_PREFIX "C:\Program Files\Tesseract-OCR\tessdata"

3. Install tesserocr using the Windows specific wheel and NormCap afterwards:

# Install tesserocr package
pip install https://github.com/simonflueckiger/tesserocr-windows_build/releases/download/tesserocr-v2.4.0-tesseract-4.0.0/tesserocr-2.4.0-cp37-cp37m-win_amd64.whl

# Install normcap
pip install normcap

# Run
normcap

Usage

General

• Select a region on screen with your mouse to perform text recognition

• Press <esc> key to abort a capture and quit the application.

Magics

"Magics" are like add-ons providing automated functionality to intelligently detect and format the captured input.

First, every "magic" calculates a "score" to determine the likelihood of being responsible for this type of text. Second, the "magic" which achieved the highest "score" takes the necessary actions to "transform" the input text according to its type.

Currently implemented Magics:

Magic	Score	Transform
Single line	Only single line is detected	Trim unnecessary whitespace
Multi line	Multi lines, but single Paragraph	Separated by line breaks and trim each lined
Paragraph	Multiple blocks of lines or multiple paragraphs	Join every paragraph into a single line, separate different paragraphs by empty line
E-Mail	Number of chars in email addresses vs. overall chars	Transform to a comma-separated list of email addresses
URL	Number of chars in URLs vs. overall chars	Transform to line-break separated URLs

Why "NormCap"?

See XKCD:

Contribute

Setup Environment

Prerequisites are Python >=3.7.1, Poetry, Tesseract (incl. language data).

# Clone repository
git clone https://github.com/dynobo/normcap.git

# Change into project directory
cd normcap

# Create virtual env and install dependencies
poetry install

# Register pre-commit hook
poetry run pre-commit install

# Run NormCap in virtual env
poetry run python -m normcap

Credits

This project uses the following non-standard libraries:

• pyside2 - bindings for Qt UI Framework
• tesserocr - wrapper for tesseract's API
• jeepney - DBUS client

Packaging is done with:

• briefcase - converting Python projects into standalone apps

And it depends on external software

• tesseract - OCR engine

Thanks to the maintainers of those nice libraries!

Certification