Basic usage: - Launch `normcap` - Select a region on the screen - Retrieve recognized text in clipboard
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1.2 0.0 normcap VS SignalumTo explore creating an application that detects available connections at once from wifi and bluetooth
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OCR powered screen-capture tool to capture information instead of images.
- 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)
(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.)
As an alternative to a pre-build package you can install the NormCap Python package:
# 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
# Install dependencies brew install tesseract tesseract-lang # Install normcap pip install normcap # Run ./normcap
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"
# 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
Select a region on screen with your mouse to perform text recognition
<esc>key to abort a capture and quit the application.
"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:
|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|
|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|
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
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!
*Note that all licence references and agreements mentioned in the normcap README section above are relevant to that project's source code only.