Comments (5)
chairc
commented on July 20, 2024
仅类别划分就行，比如狗的放一个文件夹，猫的放一个文件夹，一个类别放一个文件夹就可以。不用划分训练集和验证集。生成都是随机的，全靠肉眼看👀
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zhongsir771
commented on July 20, 2024
好的，谢谢作者！还想咨询一个问题就是我跑了代码，但是我发现只能跑64X64分辨率的，如果我想跑其他分辨率的图片请问要如何修改代码呢？
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钟浩
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***@***.***
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---- 回复的原邮件 ----
| 发件人 | Yu ***@***.***> |
| 发送日期 | 2023年9月28日 10:25 |
| 收件人 | ***@***.***> |
| 抄送人 | ***@***.***> ,
***@***.***> |
| 主题 | Re: [chairc/Industrial-Defect-Diffusion-Model] 数据集是否需要划分 (Issue #3) |
仅类别划分就行，比如狗的放一个文件夹，猫的放一个文件夹，一个类别放一个文件夹就可以。不用划分训练集和验证集。生成都是随机的，全靠肉眼看👀
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chairc
commented on July 20, 2024
修改image_size为32的倍数
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chairc
commented on July 20, 2024
好的，谢谢作者！还想咨询一个问题就是我跑了代码，但是我发现只能跑64X64分辨率的，如果我想跑其他分辨率的图片请问要如何修改代码呢？
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钟浩
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@.***
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---- 回复的原邮件 ----
| 发件人 | Yu @.> |
| 发送日期 | 2023年9月28日 10:25 |
| 收件人 | @.> |
| 抄送人 | @.> ,
@.> |
| 主题 | Re: [chairc/Industrial-Defect-Diffusion-Model] 数据集是否需要划分 (Issue #3) |仅类别划分就行，比如狗的放一个文件夹，猫的放一个文件夹，一个类别放一个文件夹就可以。不用划分训练集和验证集。生成都是随机的，全靠肉眼看👀
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现在的网络为标准的unet网络，参数较大，如果显存允许可以跑更大尺寸，例如40GB显存可以跑128的，后期的话我会升级网络结构，使用参数量更小的模型
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zhongsir771
commented on July 20, 2024
oo,好的，谢谢！
在2023年10月2日 17:18，Yu ***@***.***> 写道：
修改image_size为32的倍数
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Related Issues (17)
- cifar-10 调参 HOT 1
- 咨询 HOT 4
- 生成出来的图片是噪点图 HOT 5
- 如有任何问题，可以加入群聊交流，Q群号：949120343 HOT 2
- A summary of issues (问题总结) HOT 11
- 可以用来生成工业上的缺陷图片吗？ HOT 4
- 写地太神了, 作为新手仍然想慢慢读源码 HOT 1
- 关于训练更大尺寸需要的显存 HOT 9
- 输入的是灰度图像 能输出灰度图像吗 HOT 3
- 租用的GPU训练时出现socket has failed to listen on any local network address HOT 1
- 恢复训练 HOT 1
- 請問支援prompt輸入嗎? HOT 1
- 关于训练集和验证集 HOT 2
- Loading Unconditional Model Failure!!! HOT 1
- Why MES loss is nan in training? HOT 2
- 关于test_module.py HOT 4
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