Closed dusongjie closed 5 months ago
Firstly, the dataset structure will be like the followings, while images
contain {filename}.jpg
or other image format, and labels
contain {filename}.txt
, and the label txt format is cls, cx, cy, w, h
and cx, cy, w, h
are normalized value:
── dataset root
├─train
│ ├─fog
│ │ ├─images
│ │ └─labels
│ ├─fog_rain
│ │ ├─images
│ │ └─labels
│ ├─night
│ │ ├─images
│ │ └─labels
│ ├─rain
│ │ ├─images
│ │ └─labels
│ └─snow
│ ├─images
│ └─labels
└─val
├─fog
│ ├─images
│ └─labels
├─night
│ ├─images
│ └─labels
├─rain
│ ├─images
│ └─labels
└─snow
├─images
└─labels
You'll have to download the rgb_anon_trainvaltest.zip
and gt_detection_trainval.zip
in ACDC website if I had remember it correctly.
Secondly, this framework requires all domains to be annotated, meaning both train/{source domain}
and train/{target domain}
must have annotations. And of course, all valid/*
datasets must include object detection labels.
Thank you very much for your detailed response. I appreciate the clarification on the dataset structure and the requirements for the experiment. If I want to experiment on other datasets, they should follow the same structure, and both the source and target domain training images need labels, while the validation images of the target domain should also have labels.I appreciate your insights and the time you've taken to explain this. I will proceed with the labeled data approach as recommended and explore the potential modifications for unlabeled target domain data in future experiments.Thank you once again for your guidance and support. Best regards
Could you please provide more information about the data set download, which data set is required for this experiment on the official ACDC website? And if I want to experiment on other data sets, how should the data set be organized? The training images of the target domain have no labels, and the validation images of the target domain have labels. Do I understand this correctly?