Keras-OCR教程：深度学习中的文本检测与识别

This is a slightly polished and packaged version of the Keras CRNN implementation and the published CRAFT text detection model. It provides a high level API for training a text detection and OCR pipeline. Please see the documentation for more examples, in

keras-ocr ¶ keras-ocr provides out-of-the-box OCR models and an end-to-end training pipeline to build new OCR models. Please see the examples for more information. Installation ¶ keras-ocr supports Python >= 3.6 and TensorFlow >= 2.0.0.

In this tutorial, you will learn how to train an Optical Character Recognition (OCR) model using Keras, TensorFlow, and Deep Learning.

The OCR example uses the MNIST dataset, which can be downloaded here. Save the dataset in a folder and let’s start coding. Check also here for a presentation on this problem.

资源摘要信息:"Keras-OCR是基于Keras框架的光学字符识别（OCR）工具包，提供了简单易用的API来实现文字的检测和识别。 该工具包是CRAFT文本检测器和Keras CRNN识别模型的结合，它提供了一个灵活的接口，允许用户根据需求调整网络结构和参数。

Keras OCR is a popular open-source library that provides a user-friendly interface for performing OCR tasks in Python. It is built on top of deep learning frameworks like Keras and TensorFlow, making it easy to train and deploy accurate OCR models.