SeafloorMapping_PointNet2

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SeafloorMapping_PointNet2

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A seafloor mapping model based on PointNet++

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# Seafloor_mapping_PointNet2
A seafloor mapping model based on PointNet++ using Pytorch

### Usage
#### Model training
Firstly, make sure you have at least one ICESat-2 h5 file in you data directory, then change mode to 'train', and run:
```commandline
./preprocessing_script.sh
```

Then, annotate the data in the 'split_data' folder. Remember to put your annotated data in a folder called 'input_data'.

Lastly, when your data is ready, run:
```commandline
./train_script.sh
./test_script.sh
```

#### Model prediction
Make sure you have at least one ICESat-2 h5 file in you data directory, then change mode to 'test', and run:
```commandline
./preprocessing_script.sh
./predict_script.sh
```

#### Data
We have provided the training data as "data_8192.zip".

And we've also provided the trained model "model.pth" in the "trained_model" folder.

### Published Paper 
@article{,
      Author = {Yiwen lin, Anders Jensen Knudby},
      Title = {Global automated extraction of bathymetric photons from ICESat-2 data based on a PointNet++ model},
      Journal = {International Journal of Applied Earth Observation and Geoinformation},
      Year = {2023}
}

### Acknowlegements
@article{Pytorch_Pointnet_Pointnet2,
      Author = {Xu Yan},
      Title = {Pointnet/Pointnet++ Pytorch},
      Journal = {https://github.com/yanx27/Pointnet_Pointnet2_pytorch},
      Year = {2019}
}

SeafloorMapping_PointNet2

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