History

Tong Gao 7571763376 [Refactor] Use MMOCR's registry (#436 ) * [Refactor] Use MMOCR's registry 1. Define MMOCR's registries as a child of MMDet's 2. Register all models to MMOCR's own registries 3. Modify some model configs so that some models in MMDet can be correctly located 4. Remove some outdated demo scripts * add detectors		2021-08-19 19:17:15 +08:00
..
README.md	Add methods to readme	2021-04-10 18:04:36 +08:00
metafile.yml	update metafile (#183 )	2021-05-14 00:17:33 +08:00
psenet_r50_fpnf_600e_ctw1500.py	[Refactor] Use MMOCR's registry (#436 )	2021-08-19 19:17:15 +08:00
psenet_r50_fpnf_600e_icdar2015.py	[Refactor] Use MMOCR's registry (#436 )	2021-08-19 19:17:15 +08:00
psenet_r50_fpnf_600e_icdar2017.py	[Refactor] Use MMOCR's registry (#436 )	2021-08-19 19:17:15 +08:00

README.md

PSENet

Introduction

[ALGORITHM]

@inproceedings{wang2019shape,
  title={Shape robust text detection with progressive scale expansion network},
  author={Wang, Wenhai and Xie, Enze and Li, Xiang and Hou, Wenbo and Lu, Tong and Yu, Gang and Shao, Shuai},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={9336--9345},
  year={2019}
}

Results and models

CTW1500

Method	Backbone	Extra Data	Training set	Test set	#epochs	Test size	Recall	Precision	Hmean	Download
PSENet-4s	ResNet50	-	CTW1500 Train	CTW1500 Test	600	1280	0.728	0.849	0.784	model \| log

ICDAR2015

Method	Backbone	Extra Data	Training set	Test set	#epochs	Test size	Recall	Precision	Hmean	Download
PSENet-4s	ResNet50	-	IC15 Train	IC15 Test	600	2240	0.784	0.831	0.807	model \| log
PSENet-4s	ResNet50	pretrain on IC17 MLT model	IC15 Train	IC15 Test	600	2240	0.834	0.861	0.847	model \| log