[var.media_title;onformat=retitle]

Build a Custom OCR Model in TensorFlow: A Step-by-Step Tutorial YouTube Tutorial -- Python Lessons · YouTube Link · Test Tutorial. https://pylessons ...

Handwritten Text Recognition (HTR) system implemented with TensorFlow (TF) and trained on the IAM off-line HTR dataset.

This is a slightly polished and packaged version of the Keras CRNN implementation and the published CRAFT text detection model. Dockerfile · Issues · MIT license

This reference app demos how to use TensorFlow Lite to do OCR. It uses a text detection model and a text recognition model as a pipeline to recognize texts.

This is a simple version of OCR (Optical Character Recognition) by using Tensorflow and OpenCV within Python3.

End-to-End OCR is achieved in docTR using a two-stage approach: text detection (localizing words), then text recognition (identify all characters in the word). TensorFlow.js demo · Issues 28 · Pull requests 4 · Discussions

Ready-to-use OCR with 80+ supported languages and all popular writing scripts including: Latin, Chinese, Arabic, Devanagari, Cyrillic, etc. Try Demo on our ...

A simple OCR application using Python, OpenCV, and Keras. test_handwriting.py file recognizes handwritten text and returns an output.png image with the text ...

A clear and maintainable implementation of Attention OCR in Tensorflow 2.0. This sequence to sequence OCR model aims to provide a clear and maintainable ...

OCR & Real-time Text Detection. Real-time OCR with openCV EAST & Tesseract. Requires openCV 3.4.2 or above. Requires Tesseract 4.0 or above.