Pytorch Implementation For LPRNet, A High Performance And Lightweight License Plate Recognition Framework.
完全适用于中国车牌识别（Chinese License Plate Recognition）及国外车牌识别！
目前仅支持同时识别蓝牌和绿牌即新能源车牌等中国车牌，但可通过扩展训练数据或微调支持其他类型车牌及提高识别准确率！

• pytorch >= 1.0.0
• opencv-python 3.x
• python 3.x
• imutils
• Pillow
• numpy

• pretrained_model

1. prepare your datasets, image size must be 94x24.
2. base on your datsets path modify the scripts its hyperparameters --train_img_dirs or --test_img_dirs.
3. adjust other hyperparameters if need.
4. run 'python train_LPRNet.py' or 'python test_LPRNet.py'.
5. if want to show testing result, add '--show true' or '--show 1' to run command.

• personal test datasets.
• include blue/green license plate.
• images are very widely.
• total test images number is 27320.

1. LPRNet: License Plate Recognition via Deep Neural Networks
2. PyTorch中文文档

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