Gang Dai

Results 122 comments of Gang Dai

暂时还没开发多卡的训练的版本哦~

> 研究了一个晚上发现了几个问题 **第一,使用`user_generate.py`生成的单位是106,而用`test.py`生成的单位却是468,都是引用了同一个.pth文件为何会这样** ![image](https://private-user-images.githubusercontent.com/147568222/294919443-42e6e2b8-5f0e-44eb-9eed-e85953d73c48.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MDQ3NjU5ODUsIm5iZiI6MTcwNDc2NTY4NSwicGF0aCI6Ii8xNDc1NjgyMjIvMjk0OTE5NDQzLTQyZTZlMmI4LTVmMGUtNDRlYi05ZWVkLWU4NTk1M2Q3M2M0OC5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwMTA5JTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDEwOVQwMjAxMjVaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT1lZmEzZjI4M2U1ZWQ1YmUxYTJiODUxZjM3MTU0YmMxNTE2NjQ0NGYxNGNiZTJlZjhjYzk3YTJhYzBkNjI1ZTAzJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.S_cWhmibXRXasxMqSI5ypQDJnhaQMZppvWiZJFv7UDI) ![image](https://private-user-images.githubusercontent.com/147568222/294920813-a478eb05-268e-4885-9a25-afc7fbd8f110.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MDQ3NjU5ODUsIm5iZiI6MTcwNDc2NTY4NSwicGF0aCI6Ii8xNDc1NjgyMjIvMjk0OTIwODEzLWE0NzhlYjA1LTI2OGUtNDg4NS05YTI1LWFmYzdmYmQ4ZjExMC5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwMTA5JTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDEwOVQwMjAxMjVaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT0zMjAyODcwNWExMzNkMWUwZGVkOGM1NDljZmY3YjEzZGNmMDBlYzgwNDdiMDI2YjE2OWJkOGNjYzdkMTU5NzY0JlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.i7qs0-P2cqiOsht7t0AcnznqNwF-9TXtFjeUPn2vuSs) > > **第二,使用`user_generate.py`生成的字十分的潦草,即使尽力把预处理做好,虽能看出与‘test.py'确实不同** **该如何达到`readme`中的效果** ![image](https://private-user-images.githubusercontent.com/147568222/294923628-d2338a01-a457-4771-81c3-23d528deb751.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MDQ3NjU5ODUsIm5iZiI6MTcwNDc2NTY4NSwicGF0aCI6Ii8xNDc1NjgyMjIvMjk0OTIzNjI4LWQyMzM4YTAxLWE0NTctNDc3MS04MWMzLTIzZDUyOGRlYjc1MS5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwMTA5JTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDEwOVQwMjAxMjVaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT1hZmE4OTM1Yjk5MzQ2OWIyYmExZTNjOGRiZGUzMzYyNTgyYmY0NzA4NmRkNWQ3ODc0ZWJlOTFjM2FiOTJjZmRmJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.j1twmGxJoAmMx8c1EpKeW1assZ1qLnwUkJQz1YxLe5U) ![image](https://private-user-images.githubusercontent.com/147568222/294923259-be9547d7-cdda-4d56-9331-ffe0b709a476.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MDQ3NjU5ODUsIm5iZiI6MTcwNDc2NTY4NSwicGF0aCI6Ii8xNDc1NjgyMjIvMjk0OTIzMjU5LWJlOTU0N2Q3LWNkZGEtNGQ1Ni05MzMxLWZmZTBiNzA5YTQ3Ni5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwMTA5JTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDEwOVQwMjAxMjVaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT0zYTZjOGI5NjA4M2U2MjA1OWEyMGM0YTAzMGI1ZTIzZDkzNDJjYzE2NjljY2ZhZmEzOGRjZDZmMDNhMzE3ZmQ2JlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.TnPlk_VMWXOFEzzi6P1Iw5ZA6_8v058bQ82DNTGZb-o) **我尝试过给了30个去推演,结果风格都是一笔划写的字,因为预训练模型不是同一个吗?** ![image](https://private-user-images.githubusercontent.com/147568222/294945694-94d09817-f105-4b57-99ce-83ae56c8d178.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MDQ3NjU5ODUsIm5iZiI6MTcwNDc2NTY4NSwicGF0aCI6Ii8xNDc1NjgyMjIvMjk0OTQ1Njk0LTk0ZDA5ODE3LWYxMDUtNGI1Ny05OWNlLTgzYWU1NmM4ZDE3OC5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwMTA5JTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDEwOVQwMjAxMjVaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT0zY2MxOWIxMjA4MDA4MjJlODZmM2ZhMjI2N2M4ZTdkMTFjYjJiZGFhZTg3NTlhZTU0NDRkNTM5NTljYWI3YWRhJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.xD-SFq_C71MxOcx4JiQwMVPauJ6dJNS2G65ZL1ArV1E) `user_generate.py`生成的 ![image](https://private-user-images.githubusercontent.com/147568222/294945793-0415ec35-eb8c-4f8d-ad37-bd72abcf4271.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MDQ3NjU5ODUsIm5iZiI6MTcwNDc2NTY4NSwicGF0aCI6Ii8xNDc1NjgyMjIvMjk0OTQ1NzkzLTA0MTVlYzM1LWViOGMtNGY4ZC1hZDM3LWJkNzJhYmNmNDI3MS5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwMTA5JTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDEwOVQwMjAxMjVaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT1mMDA2YmNjY2NmNzExNTg0ZWY4ZDUyY2JhMGJlYWE2ZTZhYWU2ZjNjYjg0MDlhMjJkNTkwYjUwYTVhNzA3NTdmJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.uiLdeGtHYps6bYSylK8PDGUKZkF2Q-Ch7de_wIAyqn8) 自己写的 感谢你的反馈,我这边大概分析了一下。原因感觉还是数据差异的问题,具体来说的话:我们训练时候的数据是使用的公开数据集,笔画宽度是均匀的,你的数据似乎是平板采集的,具有更加真实的笔画宽度,由于跟训练数据的分布差异过大,导致模型倾向于给出一个平均化的风格,这个平均化的风格指的是训练集所有的风格的平均。想要提高效果的话,fine-tune一下应该会好很多,可以让模型适应一下你的数据。 另外,你的第一个问题,因为``user_generate.py``只生成你一个人的6733个文字,所以iteration是``6733/64=105.2`` (64是batchsize)的大小。``test.py``是生成测试集中60个书写者的6733个文字,然后每个书写者采样生成500个所以iteration是``60×500/64=468.75``。 你贴的最后一张图是SDT的一个拓展,我们引入了一个额外的装饰网络,为SDT生成的均匀笔画的文字增加了笔画宽度和颜色。

> 提问:按照作者给出的python user_generate.py --pretrained_model checkpoint_path --style_path style_samples运行后,再添加图片生成出来的字和原来所生成的字的字一模一样是什么原因:) 原来生成的字指的是什么?

> (base) C:\Windows\System32>python user_generate.py --pretrained_model checkpoint_path --style_path style_samples python: can't open file 'C:\Windows\System32\user_generate.py': [Errno 2] No such file or directory 下载的文件里没找到有user_generate.py诶 重新下载最新版的文件

> 感谢 @YZcat2023 分享经验。 > > 也分享一张生成结果。效果没有那么好,但也不算飞线飞得太厉害。 > > > 图中上半部分是二值化处理后的图片。 > > 笔画的线条可能还是偏粗,不确定是不是这个因素,导致推理结果还是往草书的方向去演化了? @dailenson > > 另外,私人化的一些步骤是: > > 1. 手写是在iPad上用 Notes 和 Apple Pencil(一代) 完成的,屏幕上选第3种笔,因为它的笔画粗细一致,不受压感影响;设置网格背景,选较大的那个方格。 > 2. 在iPad上截屏,然后沿着网格线裁剪,只保留包含文字的整片区域。...

> 针对个人之前的实验方式,做了些改进。 > > 取消了二值化处理,之前用只是为了去除网格线,但二值化处理会导致文字线条不平滑。 ![image](https://private-user-images.githubusercontent.com/229222/339299765-80999a80-a26d-4377-bf0d-132e25582f2e.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MjEyMTYxMDUsIm5iZiI6MTcyMTIxNTgwNSwicGF0aCI6Ii8yMjkyMjIvMzM5Mjk5NzY1LTgwOTk5YTgwLWEyNmQtNDM3Ny1iZjBkLTEzMmUyNTU4MmYyZS5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwNzE3JTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDcxN1QxMTMwMDVaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT1lYjJiNjczZWQyNjVlZjY2NDk3MmUzMjRmYjRiYzE4MWRiMWZjOGU5NTg2NDM2NzZhZDkwZmYzMDBhNmM5M2UyJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.B2k37iaogxp2JrOsVy1UuU2HEOYxdhJ04CiXtU7D3tA) ![image](https://private-user-images.githubusercontent.com/229222/339299814-61c4964b-22b6-46f7-8627-9513e6e18257.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MjEyMTYxMDUsIm5iZiI6MTcyMTIxNTgwNSwicGF0aCI6Ii8yMjkyMjIvMzM5Mjk5ODE0LTYxYzQ5NjRiLTIyYjYtNDZmNy04NjI3LTk1MTNlNmUxODI1Ny5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwNzE3JTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDcxN1QxMTMwMDVaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT1lOWNlZWU0ZTkzN2U1NWIzYjY2Nzc2OTM2YmI4YWQ4MDcxNWM5ZGJhOTdlZmMwZGZkNDI0ZjI5ZWQwYzYxZjA5JlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.5FQohqlMFlm08EzpAIvCgLg6gV4lpwaPEcrpRfH-DT4) ![image](https://private-user-images.githubusercontent.com/229222/339299869-e4892a06-af65-4e98-9ce5-de12b5db17b1.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MjEyMTYxMDUsIm5iZiI6MTcyMTIxNTgwNSwicGF0aCI6Ii8yMjkyMjIvMzM5Mjk5ODY5LWU0ODkyYTA2LWFmNjUtNGU5OC05Y2U1LWRlMTJiNWRiMTdiMS5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwNzE3JTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDcxN1QxMTMwMDVaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT0yODQ4NDUzYjU5YjBjYWM2MjA0MTliYzFmYzhlZDk4MzhkNjIxNDg5ZGRjMDcxZWQ3YTJjZjQ5YjZiMzUzMDhjJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.VqLgWGzEmtUGp0e-OXFAUdYdEggkMgta9CC46dTyIkY) > > 现在改为在裁剪图片前,提供同一组字的有网格和无网格背景的两张图片,先对有网格的选取截图区域,然后再用同样的截图区域,从无网格的图片中截取包含文字的部分。 > > 如此处理后,生成的文字,草书现象基本可以忽略了。 > > 但新问题是,输出与输入相比,真的很不像!特此请教两位,是哪个环节的问题呢,该如何优化? @dailenson @YZcat2023 > > > ![image](https://private-user-images.githubusercontent.com/229222/339298557-beeafe05-1f3d-4b07-befc-4347ea5086e6.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MjEyMTYxMDUsIm5iZiI6MTcyMTIxNTgwNSwicGF0aCI6Ii8yMjkyMjIvMzM5Mjk4NTU3LWJlZWFmZTA1LTFmM2QtNGIwNy1iZWZjLTQzNDdlYTUwODZlNi5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwNzE3JTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDcxN1QxMTMwMDVaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT0yNDAyMDgzZGJmMTFjMTBiMWZmYTczMWFjM2M1NzQwNzIyNTEyODQ2M2YxZWEzOWZiMzI2YzY3ZjM1MDA2Y2EwJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.Mp0drVNz2jFWLGB_vGehHJRBeWenIZtAxi_Ppz-8SCc) 上方是输入,下方是输出。 > > > 制作为字体后的输出效果。 我感觉可能是笔画宽度的问题。

> > > 针对个人之前的实验方式,做了些改进。 > > > 取消了二值化处理,之前用只是为了去除网格线,但二值化处理会导致文字线条不平滑。 ![image](https://private-user-images.githubusercontent.com/229222/339299765-80999a80-a26d-4377-bf0d-132e25582f2e.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MjEyMTYxMDUsIm5iZiI6MTcyMTIxNTgwNSwicGF0aCI6Ii8yMjkyMjIvMzM5Mjk5NzY1LTgwOTk5YTgwLWEyNmQtNDM3Ny1iZjBkLTEzMmUyNTU4MmYyZS5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwNzE3JTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDcxN1QxMTMwMDVaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT1lYjJiNjczZWQyNjVlZjY2NDk3MmUzMjRmYjRiYzE4MWRiMWZjOGU5NTg2NDM2NzZhZDkwZmYzMDBhNmM5M2UyJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.B2k37iaogxp2JrOsVy1UuU2HEOYxdhJ04CiXtU7D3tA) ![image](https://private-user-images.githubusercontent.com/229222/339299814-61c4964b-22b6-46f7-8627-9513e6e18257.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MjEyMTYxMDUsIm5iZiI6MTcyMTIxNTgwNSwicGF0aCI6Ii8yMjkyMjIvMzM5Mjk5ODE0LTYxYzQ5NjRiLTIyYjYtNDZmNy04NjI3LTk1MTNlNmUxODI1Ny5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwNzE3JTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDcxN1QxMTMwMDVaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT1lOWNlZWU0ZTkzN2U1NWIzYjY2Nzc2OTM2YmI4YWQ4MDcxNWM5ZGJhOTdlZmMwZGZkNDI0ZjI5ZWQwYzYxZjA5JlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.5FQohqlMFlm08EzpAIvCgLg6gV4lpwaPEcrpRfH-DT4) ![image](https://private-user-images.githubusercontent.com/229222/339299869-e4892a06-af65-4e98-9ce5-de12b5db17b1.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MjEyMTYxMDUsIm5iZiI6MTcyMTIxNTgwNSwicGF0aCI6Ii8yMjkyMjIvMzM5Mjk5ODY5LWU0ODkyYTA2LWFmNjUtNGU5OC05Y2U1LWRlMTJiNWRiMTdiMS5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwNzE3JTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDcxN1QxMTMwMDVaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT0yODQ4NDUzYjU5YjBjYWM2MjA0MTliYzFmYzhlZDk4MzhkNjIxNDg5ZGRjMDcxZWQ3YTJjZjQ5YjZiMzUzMDhjJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.VqLgWGzEmtUGp0e-OXFAUdYdEggkMgta9CC46dTyIkY) > > > 现在改为在裁剪图片前,提供同一组字的有网格和无网格背景的两张图片,先对有网格的选取截图区域,然后再用同样的截图区域,从无网格的图片中截取包含文字的部分。 > > > 如此处理后,生成的文字,草书现象基本可以忽略了。 > > > 但新问题是,输出与输入相比,真的很不像!特此请教两位,是哪个环节的问题呢,该如何优化? @dailenson @YZcat2023 > > > ![image](https://private-user-images.githubusercontent.com/229222/339298557-beeafe05-1f3d-4b07-befc-4347ea5086e6.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MjEyMTYxMDUsIm5iZiI6MTcyMTIxNTgwNSwicGF0aCI6Ii8yMjkyMjIvMzM5Mjk4NTU3LWJlZWFmZTA1LTFmM2QtNGIwNy1iZWZjLTQzNDdlYTUwODZlNi5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwNzE3JTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDcxN1QxMTMwMDVaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT0yNDAyMDgzZGJmMTFjMTBiMWZmYTczMWFjM2M1NzQwNzIyNTEyODQ2M2YxZWEzOWZiMzI2YzY3ZjM1MDA2Y2EwJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.Mp0drVNz2jFWLGB_vGehHJRBeWenIZtAxi_Ppz-8SCc) 上方是输入,下方是输出。...

> 没有英伟达显卡有办法用吗 没有显卡的话就用Cpu啦,会慢一点。

试试把``test.py``中的31行直接删掉?

> 请问您3分钟可以执行一遍的`gpu`配置是?我用T4跑一遍需要12分钟 > > > checkpoint_path要从网盘里面下载,readme里面有给下载链接,checkpoint在网盘的`saved_weights/Chinese/`路径下面。我测了一下,有`gpu`的情况下,3分钟左右就可以生成6763个中文字符,生成的字符存放在`Generated/Chinese_User`路径。 我的是``RTX 3090``