Adaptive 3D Convolution for Remote Sensing Image Fusion (Ada3D)

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Datasets

• Datasets for pansharpening: PanCollection. We recommend downloading the dataset in h5py format.

• Datasets for hyper-spectral pansharpening: HyperPanCollection. We recommend downloading the dataset in h5py format.

• Dataset for HISR: the CAVE dataset. You can find this dataset on the Internet.

Installation

This project is suitable for all versions of PyTorch after 1.7.1. Besides, you need to install some other packages as below:

pip install einops h5py opencv-python torchinfo scipy numpy

Usage

• This repository is only for the hyper-spectral pansharpening task.

• The model weights can be found in the weights dir.

• Training and testing commands (with the WDC Dataset):

# train
python train.py --train_data_path ./path_to_data/Train_WDC.h5 --val_data_path ./path_to_data/Valid_WDC.h5
# test
python test.py --file_path ./path_to_data/name.h5 --save_dir ./path_to_dir --weight ./weights/hspansharpening/WDC/1200.pth