Distribution-aware Interactive Attention Network and Large-scale Cloud Recognition Benchmark on FY-4A Satellite Image

Paper

⭐ our article ⭐

Citation

@article{zhang2024distribution,
  title={Distribution-aware Interactive Attention Network and Large-scale Cloud Recognition Benchmark on FY-4A Satellite Image},
  author={Zhang, Jiaqing and Lei, Jie and Xie, Weiying and Jiang, Kai and Cao, Mingxiang and Li, Yunsong},
  journal={arXiv preprint arXiv:2401.03182},
  year={2024}
}

Products

Usage of the code for FYH dataset

Prepare the dataset

Download the FY4A L1 dataset for FY4A

Download the Himawari dataset for Himawari

├── fydatahimawari
│   ├── Himawari
......
│   │   ├── 202005
│   │   │   ├── 05
│   │   │   │   ├── 05
│   │   │   │   │   ├──NC_H08_20200505_0500_L2CLP010_FLDK.02401_02401.nc
│   │   │   │   │   ├──NC_H08_20200505_0510_L2CLP010_FLDK.02401_02401.nc
│   │   │   │   │   ├──NC_H08_20200505_0520_L2CLP010_FLDK.02401_02401.nc
......

│   ├── FY4A
......

│   │   ├── 20200104
│   │   │   ├── FY4A-_AGRI--_N_REGC_1047E_L1-_FDI-_MULT_NOM_20200104003000_20200104003417_4000M_V0001.HDF
│   │   │   ├── FY4A-_AGRI--_N_REGC_1047E_L1-_FDI-_MULT_NOM_20200104003418_20200104003835_4000M_V0001.HDF
......

Split the dataset

python split.py

Train the model

python tools/train.py

Test the production

python tools/test_production.py

The generation validation of the Cloud-38 dataset

Prepare the dataset

Download the Cloud detection dataset cloud-38 dataset

The directory tree of this dataset is as follows:

├── 38-Cloud_training
│   ├── train_red
│   ├── train_green
│   ├── train_blue
│   ├── train_nir
│   ├── train_gt
│   ├── Natural_False_Color
│   ├── Entire_scene_gts
│   ├── training_patches_38-Cloud.csv
│   ├── training_sceneids_38-Cloud.csv
├── 38-Cloud_test
│   ├── test_red
│   ├── test_green
│   ├── test_blue
│   ├── test_nir
│   ├── Natural_False_Color
│   ├── Entire_scene_gts
│   ├── test_patches_38-Cloud.csv
│   ├── test_sceneids_38-Cloud.csv

Train the model

python tools/train_cloud38.py

Test the model

python tools/test_cloud38.py

Evaluate the result

python tools/evaluate.py