iceberg-penguins.search 0.2.6

Quality Metrics

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