Skip to main content

The ICEBERG Penguin colony usecase package

Project description

## Quality Metrics

[![Build Status](https://travis-ci.com/iceberg-project/Penguins.svg?branch=devel)](https://travis-ci.com/iceberg-project/Penguins)

## 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: `bash $ 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: `bash $ 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 `bash [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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

iceberg_penguins.search-0.2.4.4.tar.gz (39.4 kB view details)

Uploaded Source

Built Distribution

iceberg_penguins.search-0.2.4.4-py3-none-any.whl (64.8 kB view details)

Uploaded Python 3

File details

Details for the file iceberg_penguins.search-0.2.4.4.tar.gz.

File metadata

  • Download URL: iceberg_penguins.search-0.2.4.4.tar.gz
  • Upload date:
  • Size: 39.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/20.10.1 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.5.2

File hashes

Hashes for iceberg_penguins.search-0.2.4.4.tar.gz
Algorithm Hash digest
SHA256 771bf72403b56e2d4b31d4ea2dfe5fd2127450c1a8711e1b8a137a64f5af0e38
MD5 2eefb2d1da81f044bc0ac21f94476ba7
BLAKE2b-256 49d8968f91f6c45c47ed4054357ff2ff6490ac08507c5340d65caa2b49e31714

See more details on using hashes here.

File details

Details for the file iceberg_penguins.search-0.2.4.4-py3-none-any.whl.

File metadata

  • Download URL: iceberg_penguins.search-0.2.4.4-py3-none-any.whl
  • Upload date:
  • Size: 64.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/20.10.1 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.5.2

File hashes

Hashes for iceberg_penguins.search-0.2.4.4-py3-none-any.whl
Algorithm Hash digest
SHA256 f589b35699d664efe4b6c6ff43901323f5090538cc7590b8f140b1b64b13bbc1
MD5 38285b83049a0f42abbda1a6221e21e5
BLAKE2b-256 736eb45911f61f337b0841ee31d7b3e89ccb5ba9a492696dfa8997db9fe144ac

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page