https://github.com/dbuscombe-usgs/EarthAnnotator

Rapid image labeling for data-driven Earth science discovery.
https://github.com/dbuscombe-usgs/EarthAnnotator

Last synced: 2 months ago
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Rapid image labeling for data-driven Earth science discovery.

• Host: GitHub
• URL: https://github.com/dbuscombe-usgs/EarthAnnotator
• Owner: dbuscombe-usgs
• License: lgpl-3.0
• Archived: true
• Created: 2018-09-30T00:10:53.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2019-05-20T19:46:09.000Z (over 5 years ago)
• Last Synced: 2024-08-03T18:15:35.609Z (6 months ago)
• Language: Python
• Homepage:
• Size: 27.2 MB
• Stars: 7
• Watchers: 2
• Forks: 6
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-coastal - dbuscombe-usgs/EarthAnnotator - based image annotation and efficient labeling pixels in images using Python (By topic / Satellite remote sensing)

README

        
# EarthAnnotator

> Rapid image labeling for data-driven Earth science discovery.

A tool for web-based image annotation and efficient labeling pixels in images 

Implements a rapid technique, described by [Buscombe & Ritchie, (2018)](https://www.mdpi.com/2076-3263/8/7/244), for dense image labeling based on limited manual annotations.

Credits: Thanks to code contributions from [Colin Talbert](https://github.com/talbertc-usgs) and [Rich Signell](https://github.com/rsignell-usgs)  

## Run online through your browser:

[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/dbuscombe-usgs/EarthAnnotator/master?filepath=EarthAnnotator.ipynb)

Example instructional video [here](https://www.youtube.com/watch?v=oGKWWCb_Bvs&feature=youtu.be)

## Install on your own computer

First, if you're a regular conda user, you should start by doing some housekeeping:

```

conda clean --all

conda update anaconda

conda update conda

conda update --all

```

Clone the repository:

```

git clone https://github.com/dbuscombe-usgs/EarthAnnotator.git

```

```

conda config --remove channels conda-forge

```

Create a conda environment:

```

conda config --add channels conda-forge

conda env create -f binder\environment.yml

```

Activate the conda environment (called ```EA```):

```

conda activate EA

```

```

conda config --remove channels conda-forge

```

Add the kernel to jupyter:

```

python -m ipykernel install --user --name EA --display-name "Python (earthannotator)"

```

Have a look at the kernels 

```

jupyter kernelspec list

```

Run the notebook (shows up in your web browser):

```

jupyter notebook

```