chinese_ocr
yolo3 + densenet + ctc ocr
setup
see setup
dowon model
-
densenet model used for 5990 chars
url：https://pan.baidu.com/s/1gm0Uq_sLe00En-IbUPiQUg password ：qcco
put the model file in project_root/chinese_ocr/models/densenet_base_model/1 -
densenet model used for 7476 chars
url：https://pan.baidu.com/s/1_eGdF9odvzziJn35wOzQlA password ：jve5 put the model file in project_root/chinese_ocr/models/densenet_base_model/2 -
other model url: https://pan.baidu.com/s/10t5BYHm-YJXb9NpT7OnIOg
password: 8zbx
put the model file in project_root/chinese_ocr/models/
test
python demo.py
you can also see understand_detect
train
cd train
python train.py
or you can use train_with_param to deal with different dataset
dataset format
---dataset
--images
--xxx.jpg
--data_train.txt
--data_test.txt
dataset
this dataset is generate by code.
link：https://pan.baidu.com/s/1JgS1gSRcfnjWF_epU-E2vA password：wigu
The dataset contains 800,000 pictures
300,000 from chinese novel
100,000 from random number 0-9
100,000 from random code
300,000 random selected by it's frequency
- Random char space
- Random font size
- 10 different fonts
- Blur
- noise(gauss,uniform,salt_pepper,poisson)
- ...
for more detial see train_with_param
Or you can use YCG09's dataset to train,url:
url：https://pan.baidu.com/s/1QkI7kjah8SPHwOQ40rS1Pw (passwd：lu7m)
put your dataset into train/images and change the label file data_test.txt data_train.txt
generate you own dataset
or you can generate your own dataset:
- text location:
SynthText - text recognition
TextRecognitionDataGenerator
text_renderer (which one I used )
you can use tools/tmp_label_to_id_label.py to change label file format to what we need here
update
-
use pretrain model to detect word
- add demo √
- add densenet training code √
- test gpu nms √
- generate my own dataset √
-
add framework to easy train on your own dataset
- add yolo3 train code
- make the code can be easy use on other dataset
Reference
https://github.com/chineseocr/chineseocr https://github.com/YCG09/chinese_ocr