/SDM

Codes and dataset (iSAID-5i) for Scale-aware Detailed Matching for Few-Shot Aerial Image Semantic Segmentation

Primary LanguagePython

Scale-aware Detailed Matching for Few-Shot Aerial Image Semantic Segmentation

Codes and dataset (iSAID-5i) for Scale-aware Detailed Matching for Few-Shot Aerial Image Semantic Segmentation, and the work has been accepted by TGRS

the overall network:

the overall network

some visualization results: the overall network:

the results

Training

cd scripts
sh train_group0.sh

Inference

If you want to test all of the saved models, you can use:

python test_all_frame.py

Environment

  • python == 3.7

  • pytorch1.0

  • torchvision,

  • pillow,

  • opencv-python,

  • pandas,

  • matplotlib,

  • scikit-image

Datasets and Data Preparation

The newly provied dataset iSAID-5i
(Password:nwpu) or iSAID-5i