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update readme
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zyddnys committed Mar 4, 2021
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1. clone这个repo
2. [下载](https://github.com/zyddnys/manga-image-translator/releases/tag/alpha-v2.1)ocr.ckpt和detect.ckpt,放到这个repo的根目录下
3. 申请百度翻译API,把你的appid和密钥存到key.py里
4. 运行`python translate_demo.py --image <图片文件路径>`,结果会存放到result文件夹里
4. 运行`python translate_demo.py --image <图片文件路径> [--use-inpainting] [--use-cuda]`,结果会存放到result文件夹里
# 只是初步版本,我们需要您的帮助完善
这个项目目前只完成了简单的demo,依旧存在大量不完善的地方,我们需要您的帮助完善这个项目!

# 下一步
完善这个项目
1. 图片涂改目前只是简单的涂白,图片修补的模型正在训练中!
1. <s>图片涂改目前只是简单的涂白,图片修补的模型正在训练中!</s>图片修补基于[Global and Local Attention-Based Free-Form Image Inpainting](https://www.mdpi.com/1424-8220/20/11/3204),但是根据[Brock, A. et al.](https://arxiv.org/abs/2101.08692)提出的方法修改去除了所有norm层,[repo在这里](https://github.com/zyddnys/anime-inpainting-deq),目前只有Coarse阶段。
2. 【重要,请求帮助】目前的文字渲染引擎只能勉强看,和Adobe的渲染引擎差距明显,我们需要您的帮助完善文本渲染!
3. <s>我尝试了在OCR模型里提取文字颜色,均以失败告终,现在只能用DPGMM凑活提取文字颜色,但是效果欠佳,我会尽量完善文字颜色提取,如果您有好的建议请尽管提issue</s>
4. 文本检测目前不能很好处理英语和韩语,等图片修补模型训练好了我就会训练新版的文字检测模型。
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journal={arXiv preprint arXiv:1711.00937},
year={2017}
}
@article{uddin2020global,
title={Global and Local Attention-Based Free-Form Image Inpainting},
author={Uddin, SM and Jung, Yong Ju},
journal={Sensors},
volume={20},
number={11},
pages={3204},
year={2020},
publisher={Multidisciplinary Digital Publishing Institute}
}
@article{brock2021characterizing,
title={Characterizing signal propagation to close the performance gap in unnormalized ResNets},
author={Brock, Andrew and De, Soham and Smith, Samuel L},
journal={arXiv preprint arXiv:2101.08692},
year={2021}
}
```
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