Comments (3)
Ldhlwh
commented on August 29, 2024
类似的现象遇到过，训练过程中如果mask比实际缺陷范围大，在填充mask内非实际缺陷部分的时候就可能会产生artifact
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Jeff0121
commented on August 29, 2024
@Ldhlwh 您好，幾個有關mask的問題請教您:
- 使用custom dataset時，有時候會產生類似氣泡的artifacts，像您paper p. 27這樣的圖例 ( defect位置不精確會跑到背景中且顏色開始發生變化，是否因為mask範圍過小，而discriminator層數多，卷積太多次後，feature map訊息丟失過多所導致的位置不精確
- augment的value在原始styleganv2ada中，建議要小於0.8以內，但我總是train 1200kimgs後 我的資料集才會有比較好的效果，這時augment已經是1.X了，這樣是否正常呢?
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Ldhlwh
commented on August 29, 2024
- 如果缺陷比较细小或者缺陷不是很明显的时候比较容易出现这种情况
- StyleGAN2ADA所用的数据集基本上至少有一百张图，如果图片更少的话过拟合情况更严重，所以p会更大。如果觉得augmentation太强影响了图像质量可以尝试不加augmentation
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Related Issues (20)
- 使用图片label作为生成条件的疑惑 HOT 2
- RuntimeError: DataLoader worker (pid(s) 68788) exited unexpectedly
- it doesn't make any pkls/ng.pkl HOT 1
- SDGAN, Defect-GAN HOT 1
- Supplementary material HOT 2
- RuntimeError: Ninja is required to load C++ extensions HOT 4
- “Discriminator.b16.conv1.weight”出现异常 HOT 1
- res_block_match_dis error HOT 5
- 预训练时报错 HOT 4
- hazelnut_good.pkl和hazelnut_hole.pkl是如何训练生成的 HOT 3
- 环境问题 HOT 2
- hazelnut hole defect train HOT 5
- 生成图像效果问题 HOT 1
- dataset_tool.py /gray scale image HOT 1
- 训练第二阶段显存不够 HOT 2
- 预训练时间 HOT 5
- Pytorch version Compatibility HOT 2
- Training MVTec Wood datasets & Different inference results HOT 3
- Training Issue with Transistor Class HOT 10
- 生成图像的mask可以自己指定吗，即使用自己的mask来生成图像 HOT 1
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