##Create Environment:
pip install -r requirements.txt##Prepare Dataset:
Download cave_1024_28 (One Drive), CAVE_512_28 (Baidu Disk, code: ixoe | One Drive), KAIST_CVPR2021 (Baidu Disk, code: 5mmn | One Drive), TSA_simu_data (One Drive), TSA_real_data (One Drive), and then put them into the corresponding folders of datasets/ and recollect them as the following form:
|--MAUNSS
|--real
|-- test_code
|-- train_code
|--simulation
|-- test_code
|-- train_code
|--visualization
|--datasets
|--cave_1024_28
|--scene1.mat
|--scene2.mat
：
|--scene205.mat
|--CAVE_512_28
|--scene1.mat
|--scene2.mat
：
|--scene30.mat
|--KAIST_CVPR2021
|--1.mat
|--2.mat
：
|--30.mat
|--TSA_simu_data
|--mask.mat
|--Truth
|--scene01.mat
|--scene02.mat
：
|--scene10.mat
|--TSA_real_data
|--mask.mat
|--Measurements
|--scene1.mat
|--scene2.mat
：
|--scene5.matFollowing TSA-Net and DGSMP, we use the CAVE dataset (cave_1024_28) as the simulation training set. Both the CAVE (CAVE_512_28) and KAIST (KAIST_CVPR2021) datasets are used as the real training set.
cd ./simulation/train_code/
# MAUNSS_3stg
python train.py --outf ./exp/MAUNSS_3stg/ --method OLU_3stg
# MAUNSS_5stg
python train.py --outf ./exp/MAUNSS_5stg/ --method OLU_5stg
# MAUNSS_7stg
python train.py --outf ./exp/MAUNSS_7stg/ --method OLU_7stg
# MAUNSS_9stg
python train.py --outf ./exp/MAUNSS_9stg/ --method OLU_9stg
The training log, trained model, and reconstrcuted HSI will be available in ./simulation/train_code/exp/ .
Run the following command to test the model on the simulation dataset.
cd ./simulation/test_code/
# MAUNSS_3stg
python test.py --outf ./exp/MAUNSS_3stg/ --method OLU_3stg --pretrained_model_path ./MAUNSS_3stg.pth
# MAUNSS_5stg
python test.py --outf ./exp/MAUNSS_5stg/ --method OLU_5stg --pretrained_model_path ./MAUNSS_5stg.pth
# MAUNSS_7stg
python test.py --outf ./exp/MAUNSS_7stg/ --method OLU_7stg --pretrained_model_path ./MAUNSS_7stg.pth
# MAUNSS_9stg
python test.py --outf ./exp/MAUNSS_9stg/ --method OLU_9stg --pretrained_model_path ./MAUNSS_9stg.pth
- The reconstrcuted HSIs will be output into
MAUNSS/simulation/test_code/exp/
cd ./real/train_code/
# MAUNSS_3stg
python train.py --outf ./exp/MAUNSS_3stg/ --method OLU_3stg
The training log, trained model, and reconstrcuted HSI will be available in `MAUNSS_3stg/real/train_code/exp/` . cd ./real/test_code/
# MAUNSS_3stg
python test.py --outf ./exp/MAUNSS_3stg/ --method OLU_3stg --pretrained_model_path ./MAUNSS_3stg.pth
The reconstrcuted HSI will be output into `MAUNSS_3stg/real/test_code/exp/`