metadata
license: apache-2.0
tags:
- scene text erase
- poster text erase
Self-supervised Text Erasing Model (STE)
Paper: https://arxiv.org/abs/2204.12743
Project Page: https://github.com/alimama-creative/Self-supervised-Text-Erasing
Description
The checkpoints are trained from the posterErase dataset. There are two versions with different training mechanism.
Self-supervised Text Trasing: To use it, please download from this page, and put it under './checkpoints/erasenet/ste/best_net_G.pth'
Finetuning after STE : To use it, please download from this page, and put it under './checkpoints/erasenet/ste/best_net_G.pth'
Usage
First, download the github project and install the python package.
git clone https://github.com/alimama-creative/Self-supervised-Text-Erasing.git
pip install -r requirements.txt
Then, follow the command line provied in the github to run the inference code.
python test.py --dataset_mode items --dataroot ./examples/poster --model erasenet --name ft --which_epoch best # inferece with the ste model on poster
python test.py --dataset_mode items --dataroot ./examples/poster --model erasenet --name ste --which_epoch best # inferece with the finetuned model model on poster