OFA-OCR / ezocr /README.md
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EasyOCR Lite

从EasyOCR提取文本定位有关代码,进一步适配中文,修正缺陷

安装

Python版本至少为3.8。

首先按照PyTorch官方说明安装PyTorch。

pip install -e .

使用

from easyocrlite import ReaderLite

reader = ReaderLite()
results = reader.process('my_awesome_handwriting.png')

返回的内容为边界框和对应的图像区域的列表。 其它说明见demo

致谢

基于EasyOCR修改实现。以下为EasyOCR致谢:

This project is based on research and code from several papers and open-source repositories.

All deep learning execution is based on Pytorch. :heart:

Detection execution uses the CRAFT algorithm from this official repository and their paper (Thanks @YoungminBaek from @clovaai). We also use their pretrained model. Training script is provided by @gmuffiness.

The recognition model is a CRNN (paper). It is composed of 3 main components: feature extraction (we are currently using Resnet) and VGG, sequence labeling (LSTM) and decoding (CTC). The training pipeline for recognition execution is a modified version of the deep-text-recognition-benchmark framework. (Thanks @ku21fan from @clovaai) This repository is a gem that deserves more recognition.

Beam search code is based on this repository and his blog. (Thanks @githubharald)

Data synthesis is based on TextRecognitionDataGenerator. (Thanks @Belval)

And a good read about CTC from distill.pub here.

许可证 (注意!)

Apache 2.0