OwOCR

OwOCR is a command-line text recognition tool that continuously scans for images and performs OCR (Optical Character Recognition) on them. Its main focus is Japanese, but it works for many other languages.

Demo

Visual novel:

output.webm

Manga:

output.webm

Installation

OwOCR has been tested on Python 3.11, 3.12 and 3.13. It can be installed with pip install owocr after you install Python. You also need to have one or more OCR engines, check the list below for instructions. I recommend installing at least Google Lens on any operating system, and OneOCR if you are on Windows. Bing is pre-installed, Apple Vision and Live Text come pre-installed on macOS.

Basic usage

owocr

This default behavior monitors the clipboard for images and outputs recognized text back to the clipboard.

Main features

• Multiple input sources: clipboard, folders, websockets, unix domain socket, and screen capture
• Multiple output destinations: clipboard, text files, and websockets
• Pause/unpause with p or terminate with t/q in the terminal, switch between engines with s or the engine-specific keys (from the engine list below)
• Capture from specific screen areas, windows, of areas within windows (window capture is only supported on Windows/macOS). This also tries to capture entire sentences and filter all repetitions. If you use an online engine like Lens I recommend setting a secondary local engine with the -es option: -es=oneocr on Windows and -es=alivetext on macOS. With this "two pass" system only the changed areas are sent to the online service, allowing for both speed and accuracy
• Multiple configurable keyboard combinations to control owocr from anywhere, including pausing, switching engines, taking a screenshot of the selected screen/window and running the automatic tool to re-select an area of the screen/window via drag and drop
• Read from a unix domain socket /tmp/owocr.sock on macOS/Linux
• Furigana filter, works by default with Japanese text (both vertical and horizontal)

Common option examples

• Write text to a file: owocr -w=<txt file path>
• Read images from a folder: owocr -r=<folder path>
• Write text to a websocket: owocr -w=websocket (default websocket port is 7331)
• Read from the screen or a portion of the screen (opens the automatic drag and drop selector): owocr -r=screencapture
• Read from a window having "Notepad" in the title: owocr -r=screencapture -sa=Notepad
• Read from a portion of a window having "Notepad" in the title (opens the automatic drag and drop selector): owocr -r=screencapture -sa=Notepad -swa

Configuration

There are many more options and customization features. For complete documentation of all available settings:

• View all command-line options and their descriptions: owocr -h
• Check the automatically generated config file at ~/.config/owocr_config.ini on Linux/macOS, or C:\Users\yourusername\.config\owocr_config.ini on Windows
• See a sample config file: owocr_config.ini

The command-line options/config file allow you to configure OCR providers, hotkeys, screen capture settings, notifications, and much more.

Supported engines

Local

• Manga OCR (with optional comic-text-detector as segmenter) - install: pip install "owocr[mangaocr]" → keys: m (regular, ideal for small text areas), n (segmented, ideal for manga panels/larger images with multiple text areas)
• EasyOCR - install: pip install "owocr[easyocr]" → key: e
• RapidOCR - install: pip install "owocr[rapidocr]" → key: r
• Apple Vision framework - Probably the best local engine to date. macOS only - Recommended (pre-installed) → key: a
• Apple Live Text (VisionKit framework) - It should be the same as Vision except that in Sonoma Apple added vertical text reading. macOS only - Recommended (pre-installed) → key: d
• WinRT OCR: install: pip install "owocr[winocr]". It can also be used by installing winocr on a Windows virtual machine and running the server there (winocr_serve) and specifying the IP address of the Windows VM/machine in the config file. Windows 10/11 only → key: w
• OneOCR - install: pip install "owocr[oneocr]". Close second local best to the Apple one. You need to copy 3 system files from Windows 11 to use it, refer to the readme here. It can also be used by installing oneocr on a Windows virtual machine and running the server there (oneocr_serve) and specifying the IP address of the Windows VM/machine in the config file. Windows 10/11 only - Recommended → key: z

Cloud

• Google Lens - install: pip install "owocr[lens]". Arguably the best OCR engine to date. Recommended → key: l
• Bing - Close second best. Recommended (pre-installed) → key: b
• Google Vision: install: pip install "owocr[gvision]", you also need a service account .json file named google_vision.json in user directory/.config/ → key: g
• Azure Image Analysis: install: pip install "owocr[azure]", you also need to specify an api key and an endpoint in the config file → key: v
• OCRSpace: you need to specify an api key in the config file → key: o

Acknowledgments

This uses code from/references these people/projects:

• Viola for working on the Google Lens implementation (twice!) and helping with the pyobjc VisionKit code!
• @rtr46 for contributing a big overhaul allowing for coordinate support and JSON output
• @bpwhelan for contributing code for other language support and for his ideas (like two pass processing) originally implemented in the Game Sentence Miner fork of owocr
• @bropines for the Bing code (Github issue)
• @ronaldoussoren for helping with the pyobjc VisionKit code
• Manga OCR for inspiring and being the project owocr was originally derived from
• Mokuro for the comic text detector integration code
• ocrmac for the Apple Vision framework API
• ccylin2000_lipboard_monitor for the Windows clipboard polling code
• vicky for the demo videos in this readme!