LPRNet_Pytorch

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！

dependencies

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

pretrained model

• pretrained_model

training and testing

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.

performance

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

size	personal test imgs(%)	inference@gtx 1060(ms)
1.7M	96.0+	0.5-

References

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

postscript

If you found this useful, please give me a star, thanks!