DBNet.pytorch
A pytorch re-implementation of Real-time Scene Text Detection with Differentiable Binarization.
Requirements
- pytorch 1.1+
- torchvision 0.3+
- pyclipper
- opencv3
Download
TBD
Data Preparation
train: prepare a text in the following format, use '\t' as a separator
/path/to/img.jpg path/to/label.txt
...
val:
use a folder
img/ store img
gt/ store gt file
Train
- config the
train_data_path
,val_data_path
in config.json - use following script to run
python3 train.py
Test
eval.py is used to test model on test dataset
- config
model_path
,img_path
,gt_path
,save_path
in eval.py - use following script to test
python3 eval.py
Predict
predict.py is used to inference on single image
- config
model_path
,img_path
, in predict.py - use following script to predict
python3 predict.py
The project is still under development.
Performance
ICDAR 2015
only train on ICDAR2015 dataset
Method | image size (short size) | learning rate | Precision (%) | Recall (%) | F-measure (%) | FPS |
---|---|---|---|---|---|---|
DB-ResNet-18(paper) | 736 | 0.007 | 86.8 | 78.4 | 82.3 | 48 |
TBD | 736 | 1e-3 | TBD | TBD | TBD | TBD |
examples
TBD