notebooks/handwritten-ocr/README.md

# Handwritten OCR with OpenVINO™

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<img width="510" alt="handwritten_simplified_chinese_test" src="https://user-images.githubusercontent.com/36741649/132660640-da2211ec-c389-450e-8980-32a75ed14abb.png">

的人不一了是他有为在责新中任自之我们

This tutorial demonstrates optical character recognition for handwritten Chinese (simplified) and Japanese. An OCR tutorial for the Latin alphabet is available in the [optical character recognition notebook](../optical-character-recognition)

## Notebook Contents

This notebook provides a tutorial on how to use OCR for handwritten Japanese and simplified Chinese. Models used for this notebook are [`handwritten-japanese-recognition-0001`](https://docs.openvino.ai/2024/omz_models_model_handwritten_japanese_recognition_0001.html) and [`handwritten-simplified-chinese-0001`](https://docs.openvino.ai/2024/omz_models_model_handwritten_simplified_chinese_recognition_0001.html). To decode model output to readable text [`kondate_nakayosi`](https://github.com/openvinotoolkit/open_model_zoo/blob/master/data/dataset_classes/kondate_nakayosi.txt) and [`scut_ept`](https://github.com/openvinotoolkit/open_model_zoo/blob/master/data/dataset_classes/scut_ept.txt) charlists are used. Both models are available from [Open Model Zoo](https://github.com/openvinotoolkit/open_model_zoo/).

## Installation Instructions

This is a self-contained example that relies solely on its own code.</br>
We recommend running the notebook in a virtual environment. You only need a Jupyter server to start.
For details, please refer to [Installation Guide](../../README.md).