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🐍 ⚗️ Optical Character Recognition using tesseract within Frappe.

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Monogramm/erpnext_ocr

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License: MIT Managed with Taiga.io Build Status Codacy Badge Coverage Status

ERPNext OCR

⚗️ Experimental Frappe OCR application with tesseract.

This project is a fork of ERPNext-OCR by John Vincent Fiel. Its aim is to fix and cleanup the original source code and add some new features.

Check out more on ERPNext Discuss.

📈 Changes

See CHANGELOG

🔖 Roadmap

See Taiga.io

🚧 Install

Pre-requisites: tesseract-python and imagemagick

Install tesseract-ocr, plus imagemagick and ghostscript (to work with pdf files) using this command on Debian:

sudo apt-get install tesseract-ocr imagemagick libmagickwand-dev ghostscript

Install Frappe application

bench get-app --branch develop erpnext_ocr https://github.com/Monogramm/erpnext_ocr
bench install-app erpnext_ocr

When installing Frappe app, the following python requirements will be installed:

  • python binding for tesseract, tesserocr

  • image processing library in python, pillow

  • HTTP library in python, requests

  • python binding for imagemagick, wand

🚀 Usage

File Being Read:

File Being Read

Sample Screenshot:

Sample Screenshot

Tesseract trained data

In order to use OCR with different languages, you need to install the appropriate trained data files. Check tesseract Wiki for details: https://github.com/tesseract-ocr/tesseract/wiki/Data-Files

Development

If you wish to develop or just test locally this application, you can use docker-compose up -d at the root of the this repository. You can then access your ERPNext OCR dev env at http://localhost:8080.

Known issues

✅ Run tests

bench run-tests --app erpnext_ocr

👤 Authors

Monogramm

John Vincent Fiel

🤝 Contributing

Contributions, issues and feature requests are welcome!
Feel free to check issues page. Check the contributing guide.

👍 Show your support

Give a ⭐ if this project helped you!

📄 License

Copyright © 2019 Monogramm.
This project is MIT licensed.


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