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mxnet-cnn-plate-recognition's Introduction

基于CNN的OCR车牌识别



所需环境

  • Python2.7
  • Mxnet
  • Numpy
  • Opencv

操作步骤

1.生成车牌sample[^code]

python genPlate.py 100 /Users/shelter/plate_100

参数1:生成车牌的数量
参数2:生成车牌存放的地址

2.训练CNN模型[^code]

python train.py 

3.预测车牌准确率

#随机生成100张车牌图片
python genPlate.py 100 /Users/shelter/test

#批量预测测试图片准确率
python test.py /Users/shelter/test

##输出结果示例
output:
预测车牌号码为:津 K 4 2 R M Y
输入图片数量:100
输入图片行准确率:0.72
输入图片列准确率:0.86

参考资料

1.http://blog.csdn.net/relocy/article/details/52174198
2.https://github.com/szad670401/learning-dl/tree/master/mxnet/ocr

mxnet-cnn-plate-recognition's People

Contributors

huxiaoman7 avatar

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