# Characters Recognition
A Chinese characters recognition repository based on convolutional recurrent networks.
<p align='center'>
<img src='images/wechatgroup.png' title='example' style='max-width:600px'></img>
</p>
## Performance
#### Recognize characters in pictures
<p align='center'>
<img src='images/demo.png' title='example' style='max-width:600px'></img>
</p>
<p align='center'>
<img src='images/demo_2.jpg' title='example2' style='max-width:600px'></img>
</p>
## Dev Environments
1. WIN 10 or Ubuntu 16.04
2. **PyTorch 1.2.0 (may fix ctc loss)** with cuda 10.0 ð¥
3. yaml
4. easydict
5. tensorboardX
### Data
#### Synthetic Chinese String Dataset
1. Download the [dataset](https://pan.baidu.com/s/1ufYbnZAZ1q0AlK7yZ08cvQ)
2. Edit **lib/config/360CC_config.yaml** DATA:ROOT to you image path
```angular2html
DATASET:
ROOT: 'to/your/images/path'
```
3. Download the [labels](https://pan.baidu.com/s/1oOKFDt7t0Wg6ew2uZUN9xg) (password: eaqb)
4. Put *char_std_5990.txt* in **lib/dataset/txt/**
5. And put *train.txt* and *test.txt* in **lib/dataset/txt/**
eg. test.txt
```
20456343_4045240981.jpg 89 201 241 178 19 94 19 22 26 656
20457281_3395886438.jpg 120 1061 2 376 78 249 272 272 120 1061
...
```
#### Or your own data
1. Edit **lib/config/OWN_config.yaml** DATA:ROOT to you image path
```angular2html
DATASET:
ROOT: 'to/your/images/path'
```
2. And put your *train_own.txt* and *test_own.txt* in **lib/dataset/txt/**
eg. test_own.txt
```
20456343_4045240981.jpg ä½ å¥½åï¼ç¥å½ï¼
20457281_3395886438.jpg æå®åï¼ä¸çï¼
...
```
**note**: fixed-length training is supported. yet you can modify dataloader to support random length training.
## Train
```angular2html
[run] python train.py --cfg lib/config/360CC_config.yaml
or [run] python train.py --cfg lib/config/OWN_config.yaml
```
```
#### loss curve
```angular2html
[run] cd output/360CC/crnn/xxxx-xx-xx-xx-xx/
[run] tensorboard --logdir log
```
#### loss overview(first epoch)
<center/>
<img src='images/train_loss.png' title='loss1' style='max-width:800px'></img>
</center>
<p>
<img src='images/tb_loss.png' title='loss1' style='max-width:600px'></img>
</p>
## Demo
```angular2html
[run] python demo.py --image_path images/test.png --checkpoint output/checkpoints/mixed_second_finetune_acc_97P7.pth
```
## References
- https://github.com/meijieru/crnn.pytorch
- https://github.com/HRNet
CRNN_Chinese_Characters_Rec：（CRNN）汉字识别
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2021-02-05
09:52:17
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CRNN_Chinese_Characters_Rec-stable.zip （44个子文件） 
CRNN_Chinese_Characters_Rec-stable images 
loss_2.png 110KB wechatgroup.png 113KB test.png 12KB
wechatpay.jpg 101KB train_loss.png 180KB alipay.jpg 112KB tb_loss.png 30KB loss_1.png 78KB demo_2.jpg 42KB test_2.png 6KB demo.png 80KB output checkpoints 
mixed_second_finetune_acc_97P7.pth 44.91MB 360CC crnn 2020-06-22-15-53 log events.out.tfevents.1592812406.DESKTOP-LVNAKHJ 25B .github FUNDING.yml 827B README.md 2KB .idea crnn.iml 453B misc.xml 288B workspace.xml 24KB vcs.xml 180B modules.xml 260B lib core function.py 4KB __pycache__ function.cpython-35.pyc 4KB dataset _360cc.py 2KB txt 
test.txt 20.71MB train.txt 3B char_std_5990.txt 17KB __init__.py 243B __pycache__ _own.cpython-35.pyc 2KB __init__.cpython-35.pyc 442B _360cc.cpython-35.pyc 3KB _own.py 2KB models __pycache__ crnn.cpython-35.pyc 4KB crnn.py 3KB utils preprocessing.py 1KB imutils.py 5KB utils.py 6KB __pycache__ utils.cpython-35.pyc 6KB imutils.cpython-35.pyc 6KB config alphabets.py 20KB OWN_config.yaml 1KB __pycache__ alphabets.cpython-35.pyc 20KB 360CC_config.yaml 1KB demo.py 3KB train.py 5KB
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