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https://github.com/neuralchen/rainnet
[NeurIPS 2022]RainNet: A Large-Scale Imagery Dataset and Benchmark for Spatial Precipitation Downscaling
https://github.com/neuralchen/rainnet
climate-change dataset deep-learning meteorology neurips-2022
Last synced: 14 days ago
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[NeurIPS 2022]RainNet: A Large-Scale Imagery Dataset and Benchmark for Spatial Precipitation Downscaling
- Host: GitHub
- URL: https://github.com/neuralchen/rainnet
- Owner: neuralchen
- License: apache-2.0
- Created: 2020-12-15T17:34:11.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2024-09-08T07:12:18.000Z (5 months ago)
- Last Synced: 2025-01-03T05:21:06.360Z (21 days ago)
- Topics: climate-change, dataset, deep-learning, meteorology, neurips-2022
- Language: Python
- Homepage:
- Size: 68.2 MB
- Stars: 52
- Watchers: 3
- Forks: 9
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# RainNet: A Large-Scale Imagery Dataset and Benchmark for Spatial Precipitation Downscaling
# Accepted by NeurIPS 2022
[Xuanhong Chen*](https://scholar.google.com/citations?user=UuCqlfEAAAAJ&hl=en), [Kairui Feng*](https://scholar.google.com/citations?user=4N5hE8YAAAAJ&hl=en), Naiyuan Liu, [Bingbing Ni**](https://scholar.google.com/citations?user=eUbmKwYAAAAJ&hl=en), Yifan Lu, Zhengyan Tong , Ziang Liu
\* Equal contribution
\*\* Corresponding author
[[Project Website]](https://neuralchen.github.io/RainNet) [[Paper]](https://arxiv.org/abs/2012.09700) [[NeurIPS2022 Presentation]](https://drive.google.com/file/d/14phfx_h0iLJAdKv_q13cO7c9NbJGC86H/view?usp=share_link)
[[Supplementary Material]](https://drive.google.com/file/d/1QmLompRY0WPnF90IDqKkKjOif_DLSyJy/view?usp=sharing)
**The official repository with Pytorch**
[](https://github.com/neuralchen/RainNet)
[](https://github.com/neuralchen/RainNet)
## Top News 
**`2024-09-08`**: We update the google drive of RainNet [[Google Driver] RainNet_HDF5.zip (13.6G)](https://drive.google.com/file/d/1YE9l7S6NNTCqwsaqXX607vUaLZeFRx8I/view?usp=sharing). We thank [SocialBook](https://socialbook.io/) for providing us with enough shared storage space to continue making this dataset available.
**`2024-01-21`**: We provide the [[Supplementary Material]](https://drive.google.com/file/d/1QmLompRY0WPnF90IDqKkKjOif_DLSyJy/view?usp=sharing).
**`2022-11-16`**: The download links are now avaliable: [[Google Driver] RainNet_HDF5.zip (13.6G)](https://drive.google.com/file/d/1cvzT3n9N7o06YhykdakOsboyqwTavkEP/view?usp=sharing) [[Baidu Driver] RainNet_HDF5.zip (13.6G)](https://pan.baidu.com/s/1hXa6Tr089KvBefCJIVQPuQ) [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)](https://drive.google.com/file/d/1YE9l7S6NNTCqwsaqXX607vUaLZeFRx8I/view?usp=sharing)
[[Download Via Baidu Drive] RainNet_HDF5.zip (13.6G)](https://pan.baidu.com/s/1hXa6Tr089KvBefCJIVQPuQ)
[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
[](https://github.com/neuralchen/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]([email protected]), Xuanhong Chen [email]([email protected]), Naiyuan Liu [email]([email protected]) and Yifan Lu [email]([email protected]) for questions about the dataset.
## Related Projects
**Please visit ou popular face swapping project**
[](https://github.com/neuralchen/SimSwap)
[](https://github.com/neuralchen/SimSwap)
**Please visit our high-quality style transfer project**
[](https://github.com/neuralchen/ASMAGAN)
[](https://github.com/neuralchen/ASMAGAN)
**Please visit our AAAI2021 sketch based rendering project**
[](https://github.com/TZYSJTU/Sketch-Generation-with-Drawing-Process-Guided-by-Vector-Flow-and-Grayscale)
[](https://github.com/TZYSJTU/Sketch-Generation-with-Drawing-Process-Guided-by-Vector-Flow-and-Grayscale)
**Please visit our high resolution face dataset VGGFace2-HQ**
[](https://github.com/NNNNAI/VGGFace2-HQ)
Learn about our other projects
[[VGGFace2-HQ]](https://github.com/NNNNAI/VGGFace2-HQ);
[[RainNet]](https://neuralchen.github.io/RainNet);
[[Sketch Generation]](https://github.com/TZYSJTU/Sketch-Generation-with-Drawing-Process-Guided-by-Vector-Flow-and-Grayscale);
[[CooGAN]](https://github.com/neuralchen/CooGAN);
[[Knowledge Style Transfer]](https://github.com/AceSix/Knowledge_Transfer);
[[SimSwap]](https://github.com/neuralchen/SimSwap);
[[ASMA-GAN]](https://github.com/neuralchen/ASMAGAN);
[[SNGAN-Projection-pytorch]](https://github.com/neuralchen/SNGAN_Projection)
[[Pretrained_VGG19]](https://github.com/neuralchen/Pretrained_VGG19).