This is the official repository of SolarDK: A high-resolution urban solar panel image classification and localization dataset
The structure of the dataset is as follows:
solardk_dataset_neurips_v2/
├── bbr
│ └── positive
├── gentofte_trainval
│ ├── train
│ │ ├── mask
│ │ ├── negative
│ │ └── positive
│ └── val
│ ├── mask
│ ├── negative
│ └── positive
└── herlev_test
└── test
├── mask
├── negative
└── positive
Recommended download instructions
- Simply
pip install osfclient
- Download all the files using:
osf -p aj539 clone <output_directory>
cd into downloaded folder- Concat & Extract:
cat solardk_dataset_part_* | tar -xvzf -
Note: You do not need to register as a contributor to download these files
If you found this dataset useful please consider citing our works:
Khomiakov, M., Radzikowski, J.H., Schmidt, C.A., Sørensen, M.B., Andersen, M., Andersen, M.R. and Frellsen, J., 2022. SolarDK: A high-resolution urban solar panel image classification and localization dataset. arXiv preprint arXiv:2212.01260.
