neuralchen / RainNet

[NeurIPS 2022]RainNet: A Large-Scale Imagery Dataset and Benchmark for Spatial Precipitation Downscaling

RainNet: A Large-Scale Imagery Dataset and Benchmark for Spatial Precipitation Downscaling

Accepted by NeurIPS 2022

Xuanhong Chen*, Kairui Feng*, Naiyuan Liu, Bingbing Ni**, Yifan Lu, Zhengyan Tong , Ziang Liu

* Equal contribution ** Corresponding author

[Project Website] [Paper] [NeurIPS2022 Presentation] [Supplementary Material]

The official repository with Pytorch

Top News

2024-01-21: We provide the [Supplementary Material].

2022-11-16: The download links are now avaliable: [Google Driver] RainNet_HDF5.zip (13.6G) [Baidu Driver] RainNet_HDF5.zip (13.6G) [Password: sjtu].

2022-11-16: We are working for metric tools and annotation of events.

Download RainNet

[Download Via Google Drive] RainNet_HDF5.zip (13.6G)

[Download Via Baidu Drive] RainNet_HDF5.zip (13.6G) [password: sjtu]

Resources in Zip:

RainNet_HDF5.zip

  ├  $year$_07.hdf5

  ├  $year$_08.hdf5

  ├  $year$_09.hdf5

  ├  $year$_10.hdf5

  └  $year$_11.hdf5

$year$=2002~2018

• 85 HDF5 files in total;
• 322GB of hard disk space is required to extract the dataset.

Dependencies

• python3.6+
• pytorch1.5+
• torchvision
• h5py
• numpy

Usage

• Data preparation. Run the 'dataset_prepare_hdf5.py' to process the dataset into patches. In 'dataset_prepare_hdf5.py', variable 'dataset_path' sets the hdf5 file path of RainNet; 'patch_hdf5_root' sets the target path to save processed dataset:

• python dataset_prepare_hdf5.py

• We provide a example dataloader (pytorch script) to read the processed dataset:

• dataloader_hdf5.py

• python scripts are archived in fold 'scripts'

Samples in RainNet

High Resolution Precipitation Map:

### Low Resolution Precipitation Map:

### High Resolution Precipitation Map:

### Low Resolution Precipitation Map:

### High Resolution Precipitation Map:

### Low Resolution Precipitation Map:

Citation

If you find this Dataset useful in your research, please consider citing:

@misc{chen2020rainnet,
  title={RainNet: A Large-Scale Dataset for Spatial Precipitation Downscaling},
  author={Xuanhong Chen and Kairui Feng and Naiyuan Liu and Yifan Lu and Zhengyan Tong and Bingbing Ni and Ziang Liu and Ning Lin},
  year={2020},
  eprint={2012.09700},
  archivePrefix={arXiv},
  primaryClass={cs.CV}
} 

Contact

Please concat Kairui Feng email, Xuanhong Chen email, Naiyuan Liu email and Yifan Lu email for questions about the dataset.

Related Projects

Please visit ou popular face swapping project

Please visit our high-quality style transfer project

Please visit our AAAI2021 sketch based rendering project

Please visit our high resolution face dataset VGGFace2-HQ

Learn about our other projects

[VGGFace2-HQ];

[RainNet];

[Sketch Generation];

[CooGAN];

[Knowledge Style Transfer];

[SimSwap];

[ASMA-GAN];

[SNGAN-Projection-pytorch]

[Pretrained_VGG19].