An easy-to-use Chinese license plate recognition system.
Project description
AgentCLPR
简介
- 一个基于 ONNXRuntime、AgentOCR 和 License-Plate-Detector 项目开发的中国车牌检测识别系统。
车牌识别效果
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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
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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
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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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