This is the official code for AMS_Former.
python==3.8
einops==0.3.0
cryptography==43.0.0
torch==2.3.0
numpy==1.24.4
pandas==2.0.3
matploylib==3.7.5
opencv-python==4.4.0.46
timm==1.0.3
Download weights : https://pan.baidu.com/s/1g5qGGKq3DLQFX1d-NoUPUQ (password：p1iq). Please extract it and place it in the main directory.
Download datasets：https://pan.baidu.com/s/1hB4KJF8zs20SLdgBDV9-vw (password: 9y3t). Please extract it and place it in the main directory.
You can run test.py to generate test results.
python test.py --ref_dir dataset/rs_rgb_map/rgb --sen_dir dataset/rs_rgb_map/map --json_path dataset/rs_rgb_map/trans_info.json --result_dir results/rs_rgb_map --mode mode2 --device cuda
You can run the following commands to generate other results.
python test.py --ref_dir dataset/rs_rgb_nir/rgb --sen_dir dataset/rs_rgb_nir/nir --json_path dataset/rs_rgb_nir/trans_info.json --result_dir results/rs_rgb_nir --mode mode1 --device cuda
python test.py --ref_dir dataset/cv_rgb_inf/rgb --sen_dir dataset/cv_rgb_inf/inf --json_path dataset/cv_rgb_inf/trans_info.json --result_dir results/cv_rgb_inf --mode mode3 --device cuda
python test.py --ref_dir dataset/cv_rgb_nir/rgb --sen_dir dataset/cv_rgb_nir/nir --json_path dataset/cv_rgb_nir/trans_info.json --result_dir results/cv_rgb_nir --mode mode4 --device cuda
The following command is provided to allow you to test your own dataset!
python test_singlepair.py -ref_path your_ref_image_path -sen_path your_sen_iamge_path -result_path match_result_path --mode mode1 --device cuda
Choices of mode: mode1, mode2, mode3, mode4.
Good luck!