2025-10-16 17:18:10 +08:00
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# onnxOCR
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#### 一.优势：
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1.脱离深度学习训练框架，可直接用于部署的通用OCR。
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2.在算力有限，精度不变的情况下使用paddleOCR转成ONNX模型，进行重新构建的一款可部署在arm架构和x86架构计算机上的OCR模型。
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3.在同样性能的计算机上推理速度加速了4-5倍。
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#### 二.环境安装
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python>=3.6
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pip install -i https://pypi.tuna.tsinghua.edu.cn/simple -r requirements.txt
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2025-10-17 01:47:42 +00:00
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2025-10-16 17:18:10 +08:00
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[百度网盘,提取码: 125c](https://pan.baidu.com/s/1O1b30CMwsDjD7Ti9EnxYKQ )
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下载后放到./models/ch_ppocr_server_v2.0/rec/rec.onnx下
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#### 三.一键运行
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python test_ocr.py
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#### 效果展示
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#### 感谢PaddleOcr
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https://github.com/PaddlePaddle/PaddleOCR
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#### 从该项目Fork而来
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https://github.com/jingsongliujing/OnnxOCR
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---
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CHANGELOG
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1. 加入最新的`pp_ocr_v4`的检测与识别模型
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2. 修改包名为`pp_onnx`防止与onnx冲突
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3. 修改部分写死的参数
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