MTCNN和LPRNet中的两级轻量化高性能车牌识别

上传者: xixixixixixixi21 | 上传时间: 2022-04-25 16:05:37 | 文件大小: 19.39MB | 文件类型: ZIP
这是一个使用Pytork在MTCNN和LPRNet中进行的两阶段轻量级的车牌识别。MTCNN是一种非常著名的实时检测模型,主要用于人脸识别。它被修改用于车牌检测。LPRNet是另一种实时端到端DNN,用于后续识别。该网络性能优越,计算量小,无需进行初步字符分割。在这项工作中嵌入了空间变换层,以便更好地识别特征。在Nivida Quadro P4000上,在CCPD基础数据集上的识别准确率高达99%,每幅图像约80ms。 Training on LPRNet run 'LPRNet/data/preprocess.py' to prepare the dataset run 'LPRNet/LPRNet_Train.py' for training Test run 'MTCNN/MTCNN.py' for license plate detection run 'LPRNet/LPRNet_Test.py' for license plate recognition run 'main.py' for both

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