/LANet

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

Primary LanguagePython

LANet

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

alt text

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

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

  2. 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.'