Pytorch codes for 'LANet: Local Attention Embedding to Improve the Semantic Segmentation of Remote Sensing Images'
How to Use
- Split the data into training, validation and test set and organize them as follows:
YOUR_DATA_DIR
- Train
- image
- label
- Val
- image
- label
- Test
- image
- label
-
Change the training parameters in train_PD.py, especially the data directory.
-
To evaluate, change also the parameters in eval_PD.py, especially the data directory and the checkpoint path.
If you find this work useful, please consider to cite:
'Ding L, Tang H, Bruzzone L. LANet: Local Attention Embedding to Improve the Semantic Segmentation of Remote Sensing Images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020.'