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https://github.com/weiji14/actinspacenz

Developing a solution for maritime monitoring using ConvNets on Sentinel 1 radar imagery.
https://github.com/weiji14/actinspacenz

binder deep-learning jupyter-notebook quilt radar satellite sentinel-1 supervised-machine-learning u-net

Last synced: 11 days ago
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Developing a solution for maritime monitoring using ConvNets on Sentinel 1 radar imagery.

Host: GitHub
URL: https://github.com/weiji14/actinspacenz
Owner: weiji14
Created: 2018-05-24T04:11:26.000Z (over 6 years ago)
Default Branch: master
Last Pushed: 2021-04-03T05:01:49.000Z (almost 4 years ago)
Last Synced: 2025-01-07T00:18:15.065Z (about 1 month ago)
Topics: binder, deep-learning, jupyter-notebook, quilt, radar, satellite, sentinel-1, supervised-machine-learning, u-net
Language: Jupyter Notebook
Homepage:
Size: 1.55 MB
Stars: 4
Watchers: 2
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md

Awesome Lists containing this project

README

        # [Act In Space NZ 2018](https://actinspace.org)

Developing a solution for maritime monitoring

using Artificial Intelligence on Earth Observation data.

![Boats detected from Sentinel 1 radar imagery](https://user-images.githubusercontent.com/23487320/113465691-ac319a00-9492-11eb-8114-90a122642b97.png)

Left: Sentinel 1 radar imagery, Center: ConvNet detected ships, Right: Groundtruth labels of ships

# Getting started

## Quickstart

Launch Binder (Interactive jupyter notebook in the cloud).

Data will be loaded via [Quilt](https://github.com/quiltdata/quilt). Cheers to [data2binder](https://github.com/quiltdata/data2binder)!

[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/weiji14/actinspacenz/master)

## Installation

Start by cloning this [repo-url](/../../)

    git clone 

    cd nz_space_challenge

    conda env create -f environment.yml

## Running the jupyter lab/notebook session

    source activate actinspacenz

    python -m ipykernel install --user --name actinspacenz  #to install conda env properly

    jupyter kernelspec list --json  #see if kernel is installed

    jupyter lab