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An easy-to-use Chinese license plate recognition system.

Project description

AgentCLPR

简介

车牌识别效果

  • 支持多种车牌的检测和识别(其中单层车牌识别效果较好):

      未拼接原图的识别结果如下(格式 [车牌位置坐标,车牌号码及置信度]):
    
          [[[[373, 282], [69, 284], [73, 188], [377, 185]], ['苏E05EV8', 0.9923506379127502]]]
          [[[[393, 278], [318, 279], [318, 257], [393, 255]], ['VA30093', 0.7386096119880676]]]
          [[[[[487, 366], [359, 372], [361, 331], [488, 324]], ['皖K66666', 0.9409016370773315]]]]
          [[[[304, 500], [198, 498], [199, 467], [305, 468]], ['鲁QF02599', 0.995299220085144]]]
          [[[[309, 219], [162, 223], [160, 181], [306, 177]], ['使198476', 0.9938704371452332]]]
          [[[[957, 918], [772, 920], [771, 862], [956, 860]], ['陕A06725D', 0.9791222810745239]]]
    

快速使用

  • 快速安装

    # 安装 AgentCLPR
    $ pip install agentclpr
    
    # 根据设备平台安装合适版本的 ONNXRuntime
    
    # CPU 版本(推荐非 win10 系统,无 CUDA 支持的设备安装)
    $ pip install onnxruntime
    
    # GPU 版本(推荐有 CUDA 支持的设备安装)
    $ pip install onnxruntime-gpu
    
    # DirectML 版本(推荐 win10 系统的设备安装,可实现通用的显卡加速)
    $ pip install onnxruntime-directml
    
    # 更多版本的安装详情请参考 ONNXRuntime 官网
    
    • 简单调用:

      # 导入 CLPSystem 模块
      from agentclpr import CLPSystem
      
      # 初始化车牌识别模型
      clp = CLPSystem()
      
      # 使用模型对图像进行车牌识别
      results = clp('test.jpg')
      

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