feipanir / IntraDA

Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision (CVPR 2020 Oral)
https://arxiv.org/pdf/2004.07703.pdf
MIT License
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目标域没有标签 #16

Open Reality-Dream7 opened 1 year ago

Reality-Dream7 commented 1 year ago

老师,如果一开始目标域有标签的话,代码是可以运行的,但是无监督域自适应不是要求目标域没有标签吗? 如果一开始目标域没有标签的话,代码就不能运行。 如果一开始目标域是有伪标签的话,那么刚开始的伪标签是怎么生成的?

feipanir commented 1 year ago

Hi thank you for your interests. Please prepare a validation set for your target domain. Your validation set shall contains a set of validate images and ground truth annotations.

Reality-Dream7 commented 1 year ago

老师,验证集val文件夹里面有标签,但是现在运行时报错,显示train文件夹里面没有标签“FileNotFoundError: [Errno 2] No such file or directory: 'E:\root\code\IntraDA\ADVENT\data\Cityscapes\gtFine\train\hamburg\hamburg_000000_087822_gtFine_labelIds.png'”

Reality-Dream7 commented 1 year ago

嗨,感谢您的关注。请为目标域准备验证集。您的验证集应包含一组验证图像和真实注释。

老师,验证集val文件夹里面有标签,但是现在运行时报错,显示train文件夹里面没有标签“FileNotFoundError: [Errno 2] 没有这样的文件或目录: 'E:\root\code\IntraDA\ADVENT\data\Cityscapes\gtFine\train\hamburg\hamburg_000000_087822_gtFine_labelIds.png'”

feipanir commented 1 year ago

I think the errors come from the loading path of your dataset. Could you double-check if your path is correctly pointed to the dataset?

Reality-Dream7 commented 1 year ago

我认为错误来自数据集的加载路径。您能否仔细检查您的路径是否正确指向数据集?

老师,数据集的加载路径应该是正确指向的,因为val文件夹里面有标签,而只要train文件夹里面有标签就可以执行,train文件夹里面没有标签就会报错。

feipanir commented 1 year ago

Thanks for the feedback. In this case, you can modify the loading function by deleting the code lines that read the labels of the train set.

bryanbocao commented 11 months ago

--如果一开始目标域是有伪标签的话,那么刚开始的伪标签是怎么生成的?

I have two similar questions as well.

(1) For saving the pseudo labels, which are the soft labels of pixel-wise class probabilities, should be generated and saved somewhere after the training stage from ADVENT.

(2) For loading the pseudo labels in the intra-domain training stage, they should be loaded in this line of code as labels: https://github.com/bryanbocao/IntraDA/blob/gh-pages/intrada/train_UDA.py#L116 but what I printed seemed to be the ground truth class label from 0 to 19.

It would be appreciated if you can help with these issues @feipanir.