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https://github.com/YukangWang/TextField
TextField: Learning A Deep Direction Field for Irregular Scene Text Detection (TIP 2019)
https://github.com/YukangWang/TextField
scene-text text-detection
Last synced: 10 days ago
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TextField: Learning A Deep Direction Field for Irregular Scene Text Detection (TIP 2019)
- Host: GitHub
- URL: https://github.com/YukangWang/TextField
- Owner: YukangWang
- License: other
- Created: 2018-12-21T03:00:19.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2019-03-15T12:43:15.000Z (over 5 years ago)
- Last Synced: 2024-08-02T11:15:24.972Z (3 months ago)
- Topics: scene-text, text-detection
- Language: C++
- Homepage:
- Size: 2.37 MB
- Stars: 99
- Watchers: 5
- Forks: 25
- Open Issues: 7
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
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README
# TextField: Learning A Deep Direction Field for Irregular Scene Text Detection
## Introduction
The code and trained models of:
TextField: Learning A Deep Direction Field for Irregular Scene Text Detection, TIP 2019 [[Paper]](https://arxiv.org/abs/1812.01393)
## Citation
Please cite the related works in your publications if it helps your research:
```
@article{xu2018textfield,
title={TextField: Learning A Deep Direction Field for Irregular Scene Text Detection},
author={Xu, Yongchao and Wang, Yukang and Zhou, Wei and Wang, Yongpan and Yang, Zhibo and Bai, Xiang},
journal={arXiv preprint arXiv:1812.01393},
year={2018}
}
```
## Prerequisite
* Caffe and SynthText pretrained model [[Link]](https://drive.google.com/file/d/1C4EUllZMTNYt_Q2t4PjZypepYjHechvj/view?usp=sharing)
* Datasets: [[Total-Text]](http://www.cs-chan.com/source/ICDAR2017/totaltext.zip), [[ICDAR2015]](http://rrc.cvc.uab.es/?ch=4&com=downloads)
* OpenCV 3.4.3
* MATLAB
## Usage
#### 1. Install Caffe
```bash
cp Makefile.config.example Makefile.config
# adjust Makefile.config (for example, enable python layer)
make all -j16
# make sure to include $CAFFE_ROOT/python to your PYTHONPATH.
make pycaffe
```
Please refer to [Caffe Installation](http://caffe.berkeleyvision.org/install_apt.html) to ensure other dependencies.
#### 2. Data and model preparation
```bash
# download datasets and pretrained model then
mkdir data && mv [your_dataset_folder] data/
mkdir models && mv [your_pretrained_model] models/
```
#### 3. Training scripts
```bash
# an example on Total-Text dataset
cd examples/TextField/
python train.py --gpu [your_gpu_id] --dataset total --initmodel ../../models/synth_iter_800000.caffemodel
```
#### 4. Evaluation scripts
```bash
# an example on Total-Text dataset
cd evaluation/total/
./eval.sh
```
## Results and Trained Models
#### Total-Text
| Recall | Precision | F-measure | Link |
|:-------------:|:-------------:|:-------------:|:-----:|
| 0.816 | 0.824 | 0.820 | [[Google drive]](https://drive.google.com/file/d/1FAiL2C0WOuN5QFSD6wfLSgP29mmBUdIV/view?usp=sharing) |
>*lambda=0.50 for post-processing
#### ICDAR2015
| Recall | Precision | F-measure | Link |
|:-------------:|:-------------:|:-------------:|:-----:|
| 0.811 | 0.846 | 0.828 | [[Google drive]](https://drive.google.com/file/d/1T6lBbe1BXfppsuijZTE_LSaH1XT_5_jD/view?usp=sharing) |
>*lambda=0.75 for post-processing