A TensorFlow 2 wrapper of DBNet
Project description
TFDBNet
A TensorFlow 2 reimplementation of Real-time Scene Text Detection with Differentiable Binarization available as a Python package and using TedEval as evaluation metrics.
Data Preparation
Store images in imgs
folder and groundtruths in gts
folder. Then, prepare text files for training and validate data in the following format with '\t' as a separator:
- Example for ICDAR 2015
train.txt
:
./datasets/train/train_imgs/img_1.jpg ./datasets/train/train_gts/gt_img_1.txt
./datasets/train/train_imgs/img_2.jpg ./datasets/train/train_gts/gt_img_2.txt
- Example for ICDAR 2015
validate.txt
:
./datasets/validate/validate_imgs/img_1.jpg ./datasets/validate/validate_gts/gt_img_1.txt
./datasets/validate/validate_imgs/img_2.jpg ./datasets/validate/validate_gts/gt_img_2.txt
You can customize the script in dir2paths.sh to generate the above train.txt
and validate.txt
for your own dataset. And the groundtruths can be .txt
files, with the following format:
x1, y1, x2, y2, x3, y3, x4, y4, annotation
Below is the content of ./datasets/train/train_gts/gt_img_1.txt
:
377,117,463,117,465,130,378,130,Genaxis Theatre
493,115,519,115,519,131,493,131,[06]
374,155,409,155,409,170,374,170,###
492,151,551,151,551,170,492,170,62-03
376,198,422,198,422,212,376,212,Carpark
494,190,539,189,539,205,494,206,###
374,1,494,0,492,85,372,86,###
Quick Start
pip install tfdbnet
After above installation, see the demo on ICDAR 2015 dataset to know how to use
Reference
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