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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: 7 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 (over 3 years ago)
- Last Synced: 2024-10-23T04:25:25.729Z (13 days 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