SynthText3D: Synthesizing Scene Text Images from 3D Virtual Worlds

Introduction

This is a project that synthesizes scene text images from 3D virtual worlds.

For more details, please refer to our paper.

Performance

Detection results with different synthetic data. 5k", 10k'' and ``800k" indicate the number of images used for training.

Video Demo

We made a video demonstration for the synthesis process and visualization. Click the following link to watch the video on YouTube.

Data

For our 10K data set synthesized from 30 scenes, download from Google Drive

Data Formats

The extracted data folder has the following format:

|- Synth3D-10K
|    |- label
|    |    |- 1.txt
|    |    |- 2.txt
|    |    |- 3.txt
|    |    |- ...
|    |    |- 10000.txt
|    |- img
|    |    |- 1.jpg
|    |    |- 2.jpg
|    |    |- 3.jpg
|    |    |- ...
|    |    |- 10000.jpg

Each text instance is the label files takes up 5 lines:

x1,y1
x2,y2
x3,y3
x4,y4
is_difficult

when is_difficult==1, the text is marked as difficult. The coordinates are arranged clockwise.

Code

See ./Code. ./Code/Unrealtext-Source is adapted from UnrealCV and implements functionalities for text synthesis.

How to use (Ubuntu)

Installation

1. Make sure you have UE4.16 installed and the UnrealCV plugin functions normally.
2. Ask an artist to create a virtual scene or download one from the Unreal Market.
3. Use UE4.16 to compile the unrealtext source code and put the plugin into your unreal project.
4. Open your unreal project, add the unrealtext plugin. Compile the myCameraRecordPawn.h/cpp class
5. Add the following components: PugTextPawn, myCameraRecordPawn. You need to add n PugTextPawn pawns to render n text instances in the scene.
6. Package the environment

Data Generation

1. Set camera anchors: launch the executable, manually wander around the scene and use mouse left click to record anchors. The trajectory file is stored at ./{YourSceneRoot}/LinuxNoEditor/UnrealText/Binaries/Linux/trajectory.txt.
2. Run python3 RetrieveSceneInfo.py to obtain scene informations such as depth map and normal map for each camera anchor location.
3. Run python3 GenerateData.py to generate data.

Citing the related works

Please cite the paper in your publications if it helps your research:

@article{liao2020synthtext3d,
  title={SynthText3D: Synthesizing Scene Text Images from 3D Virtual Worlds},
  author={Liao, Minghui and Song, Boyu and Long, Shangbang and He, Minghang and Yao, Cong and Bai, Xiang},
  journal={SCIENCE CHINA Information Sciences},
  year={2020}
}