pnaclcu / FSAUNET

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Pytorch Implement for Full-spectrum attention U-Net

Repo architecture

unet/unet_parts.py and unet_model.py include the U-Net model.

unet/full_freq_att.py includes the proposed full-spectrum model.

utils/dataset.py is used to process dataloader.

dice_loss.py is used to compute the dice scores.

plz see the details in the following introduction.

Dataset preparation

The CAMUS echocardiography dataset is recommended !!

If you do not want to rewrite the utils/dataset.py, please using the following dataset structure.

  • CAMUS |
    • training >
      • patinet0001 >
        • img >
          • img0001.png, img0002.png.....
        • mask >
          • img0001.png, img0002.png.....
  • testing >
    As same as the training.

The name of image and its correspongding mask should be same.

Training the model

run python train.py

Predicting the model

run python predict.py

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