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https://github.com/szad670401/end-to-end-for-chinese-plate-recognition
多标签分类,端到端的中文车牌识别基于mxnet, End-to-End Chinese plate recognition base on mxnet
https://github.com/szad670401/end-to-end-for-chinese-plate-recognition
Last synced: 4 days ago
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多标签分类,端到端的中文车牌识别基于mxnet, End-to-End Chinese plate recognition base on mxnet
- Host: GitHub
- URL: https://github.com/szad670401/end-to-end-for-chinese-plate-recognition
- Owner: szad670401
- Created: 2016-08-07T13:34:20.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2019-01-08T09:43:23.000Z (almost 6 years ago)
- Last Synced: 2024-10-30T03:42:53.468Z (17 days ago)
- Language: Python
- Homepage:
- Size: 35.9 MB
- Stars: 1,112
- Watchers: 62
- Forks: 522
- Open Issues: 29
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-ocr - 多标签分类,端到端的中文车牌识别基于mxnet, End-to-End Chinese plate recognition base on mxnet
README
# end-to-end-for-plate-recognition
多标签分类,端到端的中文车牌识别基于mxnet .
从[xlvector的ocr代码](https://github.com/szad670401/learning-dl/tree/master/mxnet/ocr)修改,减少了参数,由于我没有显卡。单线程 9 samples/s 速度 ,用CPU在MBP上跑了50w张样本。识别率到了81%。不过还没有完全收敛。## 训练好的模型
https://github.com/ibyte2011/end-to-end-for-chinese-plate-recognition## 关于车牌识别
生成的车牌对于实际车牌并不是效果很好,在结合真实样本和GAN,训练了一个更好的模型,对真实车牌表现很好。
并实现了一整套车牌识别的系统命名为HyperLPR https://github.com/zeusees/HyperLPR## 依赖:
+ Numpy
+ Mxnet
+ Opencv
## 生成的车牌样张
通过渲染车牌加上畸变、噪声、与自然环境结合生成车牌的样本。![image](./recognize_samples/00.jpg)
![image](./recognize_samples/01.jpg)
![image](./recognize_samples/02.jpg)
![image](./recognize_samples/03.jpg)
![image](./recognize_samples/04.jpg)
![image](./recognize_samples/06.jpg)
![image](./recognize_samples/07.jpg)
![image](./recognize_samples/08.jpg) ![image](./recognize_samples/02.jpg)
![image](./recognize_samples/09.jpg)
![image](./recognize_samples/10.jpg)
![image](./recognize_samples/11.jpg)
## 识别样张
## Author
+ Jack Yu
+ Xiao Xiao