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