owocr 1.5.2

Japanese OCR

OwOCR

Command line client for several Japanese OCR providers derived from Manga OCR.

Installation

This has been tested with Python 3.11. Newer/older versions might work. It can be installed with pip install owocr

Supported providers

Local providers

• Manga OCR: refer to the readme for installation ("m" key)
• EasyOCR: refer to the readme for installation ("e" key)
• RapidOCR: refer to the readme for installation ("r" key)
• Apple Vision framework: this will work on macOS Ventura or later. In my experience, the best of the local providers for horizontal text ("a" key)
• WinRT OCR: this will work on Windows 10 or later if winocr (pip install winocr) is installed. It can also be used by installing winocr on a Windows virtual machine and running the server (winocr_serve), installing requests (pip install requests) and specifying the IP address of the Windows VM/machine in the config file (see below) ("w" key)

Cloud providers

• Google Lens: Google Vision in disguise (no need for API keys!), however it needs to download a couple megabytes of data for each request. You need to install pyjson5 and requests (pip install pyjson5 requests) ("l" key)
• Google Vision: you need a service account .json file named google_vision.json in user directory/.config/ and installing google-cloud-vision (pip install google-cloud-vision) ("g" key)
• Azure Image Analysis: you need to specify an api key and an endpoint in the config file (see below) and to install azure-ai-vision-imageanalysis (pip install azure-ai-vision-imageanalysis) ("v" key)

Usage

It mostly functions like Manga OCR: https://github.com/kha-white/manga-ocr?tab=readme-ov-file#running-in-the-background However:

• it supports reading images and/or writing text to a websocket when the -r=websocket and/or -w=websocket parameters are specified (port 7331 by default, configurable in the config file)
• it supports capturing the screen directly with -r screencapture. It will default to the entire first screen every 3 seconds, but a different screen/coordinates/window/delay can be specified in the config file. Instead of using a delay it's also possible to specify a keyboard combo (refer to the config file or the help page)
• you can pause/unpause the image processing by pressing "p" or terminate the script with "t" or "q" in the terminal window
• you can switch OCR provider pressing its corresponding keyboard key in the terminal window (refer to the list of keys above). You can also start the script paused with the -p option or with a specific provider with the -e option (refer to owocr -h for the list)
• holding ctrl or cmd at any time will pause image processing temporarily, or you can specify keyboard combos in the config file to pause/unpause and switch the OCR provider (refer to the config file or the help page)
• for systems where text can be copied to the clipboard at the same time as images, if *ocr_ignore* is copied with an image, the image will be ignored
• optionally, notifications can be enabled in the config file to show the text with a native OS notification
• optionally, you can speed up the online providers by installing fpng-py: pip install fpng-py (requires a developer environment on some operating systems/Python versions)
• optionally, you can improve filtering of non-Japanese text for screen capture by installing transformers: pip install transformers
• idle resource usage on macOS and Windows when reading from the clipboard has been eliminated using native OS polling
• a config file (to be created in user directory/.config/owocr_config.ini, on Windows user directory is the C:\Users\yourusername folder) can be used to configure the script, as an example to limit providers (to reduce clutter/memory usage) as well as specifying provider settings such as api keys etc. A sample config file is provided here

Acknowledgments

This uses code from/references these projects:

• Manga OCR
• ocrmac for the Apple Vision framework API
• NadeOCR for the Google Vision API
• ccylin2000_lipboard_monitor for the Windows clipboard polling code

Thanks to viola for working on the Google Lens implementation!