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https://github.com/aysark/sky-insight

Hack the Map 2018 Winning Entry: Easily train machine learning models using tile maps & ArcGIS.
https://github.com/aysark/sky-insight

arcgis esri hackathon image-classification machine-learning satellite sky-insight

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Hack the Map 2018 Winning Entry: Easily train machine learning models using tile maps & ArcGIS.

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README

        

# sky-insight
![Demo Video](src/assets/sky-insight-preview-small.gif)

sky-insight allows you to:
- Easily train image classification machine learning models using satellite/aerial tile imagery & ArcGIS.
- Enrich your existing GIS data with real world planetary data.
- Monitor the physical world with ease using automation & image classification.

It features two modus operandi:
### Search
![Preview](src/assets/preview.png)

Search mode allows you to use your trained models or any existing models to automatically infer/predict on an area of interest of tiles. You can then export your predictions as feature sets or geojson. Above image is a ship tile classifier.

### Train
![Preview](src/assets/preview2.png)

Train mode allows you to easily train your own image classification models using a simple tile annotation tool. So you can build ship, airplane, oil tank, pivot irrigation farm classifiers- or whatever you fancy. Above image is training of a pivot irrigation tile classifier.

## Build & Run

``` bash
# install dependencies
npm install

# rename sample.env.js to env.js and fill in tokens

# serve with hot reload at localhost:8080
npm run dev

# build for production with minification
npm run build
```

For detailed explanation on how things work, consult the [docs for vue-loader](http://vuejs.github.io/vue-loader).