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The ICEBERG Penguin colony usecase package

Project description

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Build Status

Software Dependencies

  • boost==1.66.0
  • gdal==2.1.4
  • geotiff==1.4.2
  • matplotlib==2.1.0
  • opencv==2.4.13
  • openjpeg==2.1.2
  • pillow==4.2.1
  • python==2.7.15
  • pytorch==0.3.1
  • rasterio==0.36.0
  • scikit-learn==0.19.1
  • scipy==1.2.1
  • scipy==0.19.0
  • torchvision==0.2.0
  • visdom==0.1.8.9

Installation

PSC Bridges

From source:

$ git clone https://github.com/iceberg-project/Penguins.git
$ module load cuda
$ module load python3
$ virtualenv iceberg_penguins
$ source iceberg_penguins/bin/activate
[iceberg_penguins] $ export PYTHONPATH=<path>/iceberg_penguins/lib/python3.5/site-packages
[iceberg_penguins] $ pip install . --upgrade

From PyPi:

$ module load cuda
$ module load python3
$ virtualenv iceberg_penguins
$ source iceberg_penguins/bin/activate
[iceberg_penguins] $ export PYTHONPATH=<path>/iceberg_penguins/lib/python3.5/site-packages
[iceberg_penguins] $ pip install iceberg_penguins.search

To test

[iceberg_penguins] $ iceberg_penguins.detect

Prediction

  • Download a pre-trained model at:

https://drive.google.com/file/d/149j5rlynkO1jQTLOMpL5lextHY0ozw6N/view?usp=sharing

Please put the model file to: <checkpoints_dir>/<model_name>/

The one provided here is at the epoch 300 of the model named "v3weakly_unetr_bs96_main_model_ignore_bad"

  • The script to run the testing for a single PNG image:

iceberg_penguins.detect [--params ...]

params:

  • --name: name of the model used for testing
  • --gpu_ids: the gpu used for testing
  • --checkpoints_dir: path to the folder containing the trained models
  • --epoch: which epoch we use to test the model
  • --input_im: path to the input image
  • --output: directory to save the outputs

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