Using Deeplearning to locate the Synthetic Aperture Radar(SAR) images to the counterpart of Optical images.
Model backbone: CSP + Dense Block CNN Loss: Arc loss and l2 loss
run: python location_demo.py
image pairs in 'test_image' will be loaded into model and predict the location of SAR images in optical images. The matching results will save as images.
利用CSP Block 和 Dense Block 搭建的CNN网络实现对光学图像和合成孔径雷达图像的位置匹配。
通过使用模型提取的图像关键点特征描述子进行异源图像匹配
示例: python location_demo.py 读入'test_image'中待匹配的图像进行匹配,结果以图片形式保存
python >= 3.6
pytorch >= 1.0
opencv
torchvision
tqdm