Pytorch codes for 'LANet: Local Attention Embedding to Improve the Semantic Segmentation of Remote Sensing Images'

How to Use

1. 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

2. Change the training parameters in train_PD.py, especially the data directory.

3. 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.'