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chinese_ocr_api's Introduction

这里基于tensorflow,pytorch实现对自然场景的文字检测及端到端的OCR中文文字识别

模型和数据都可以到原项目上去下载,然后放入指定文件夹下

还在更新

ctnp_ocr_test.ipynb文件是运行的Demo,运行前需要下载模型,并放入指定文件夹下(可查看CHINESE-OCR-API\img)。

chinese_ocr_api\ctpn目录下: python train_ctpn.py可开始训练CTPN

chinese_ocr_api\lib\datasets\pascal_voc.py 下需要确认训练数据的路径self._devkit_path = './data/VOCdevkit2007'

训练后在chinese_ocr_api下会产生几个文件夹,其中data/下有一个cache/voc_2007_trainval_gt_roidb.pkl文件,如果换新数据重新训练需要先删除该缓存文件不然会报(KeyError: 'max_overlaps')的错。

数据集预处理 下载icdar2017rctw_train_v1.2数据集,可转为训练需要的数据格式,在放入指定文件夹下,就可以扩充训练数据。如果有特殊要求,可以用labelImg自己标一些数据。

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