车牌识别

中文车牌识别系统基于crnn

环境配置

1. WIN 10 or Ubuntu 16.04
2. PyTorch > 1.2.0 (may fix ctc loss)🔥
3. yaml
4. easydict
5. tensorboardX

数据

车牌识别数据集CCPD+CRPD

1. 从CCPD和CRPD截下来的车牌小图以及我自己收集的一部分车牌 dataset 提取码：41s9

2. 数据集打上标签,生成train.txt和val.txt

   图片命名如上图 然后执行如下命令，得到train.txt和val.txt

   python plateLabel.py --image_path your/train/img/path/ --label_file datasets/train.txt
   python plateLabel.py --image_path your/val/img/path/ --label_file datasets/val.txt
   

   数据格式如下：

   train.txt

   /mnt/Gu/trainData/plate/new_git_train/CCPD_CRPD_ALL/冀BAJ731_3.jpg 5 53 52 60 49 45 43 
   /mnt/Gu/trainData/plate/new_git_train/CCPD_CRPD_ALL/冀BD387U_2454.jpg 5 53 55 45 50 49 70 
   /mnt/Gu/trainData/plate/new_git_train/CCPD_CRPD_ALL/冀BG150C_3.jpg 5 53 58 43 47 42 54 
   /mnt/Gu/trainData/plate/new_git_train/CCPD_CRPD_OTHER_ALL/皖A656V3_8090.jpg 13 52 48 47 48 71 45 
   /mnt/Gu/trainData/plate/new_git_train/CCPD_CRPD_OTHER_ALL/皖C91546_7979.jpg 13 54 51 43 47 46 48 
   /mnt/Gu/trainData/plate/new_git_train/CCPD_CRPD_OTHER_ALL/皖G88950_1540.jpg 13 58 50 50 51 47 42 
   /mnt/Gu/trainData/plate/new_git_train/CCPD_CRPD_OTHER_ALL/皖GX9Y56_2113.jpg 13 58 73 51 74 47 48 
   

3. 将train.txt val.txt路径写入lib/config/360CC_config.yaml 中

   DATASET:
     DATASET: 360CC
     ROOT: ""
     CHAR_FILE: 'lib/dataset/txt/plate2.txt'
     JSON_FILE: {'train': 'datasets/train.txt', 'val': 'datasets/val.txt'}
   

Train

   [run] python train.py --cfg lib/config/360CC_config.yaml

结果保存再output文件夹中

测试demo

python my_demo_new.py --model_path saved_model/best.pth --image_path images/test.jpg
                                   or your/model/path

结果是：

References

• https://github.com/meijieru/crnn.pytorch