https://github.com/sirius-ai/LPRNet_Pytorch
Pytorch Implementation For LPRNet, A High Performance And Lightweight License Plate Recognition Framework.
https://github.com/sirius-ai/LPRNet_Pytorch
ctc-loss license-plate-recognition lprnet plate-detection plate-recognition pytorch
Last synced: about 1 month ago
JSON representation
Pytorch Implementation For LPRNet, A High Performance And Lightweight License Plate Recognition Framework.
- Host: GitHub
- URL: https://github.com/sirius-ai/LPRNet_Pytorch
- Owner: sirius-ai
- License: apache-2.0
- Created: 2019-05-04T15:05:14.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2023-06-21T13:37:25.000Z (almost 2 years ago)
- Last Synced: 2024-10-28T04:18:49.865Z (6 months ago)
- Topics: ctc-loss, license-plate-recognition, lprnet, plate-detection, plate-recognition, pytorch
- Language: Python
- Homepage:
- Size: 19.6 MB
- Stars: 920
- Watchers: 12
- Forks: 231
- Open Issues: 71
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# 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](https://github.com/sirius-ai/LPRNet_Pytorch/tree/master/weights/)
# 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](https://arxiv.org/abs/1806.10447v1)
2. [PyTorch中文文档](https://pytorch-cn.readthedocs.io/zh/latest/)
# postscript
If you found this useful, please give me a star, thanks!