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* [YOLT](https://github.com/avanetten/yolt) - You Only Look Twice: Rapid Multi-Scale Object Detection In Satellite Imagery.
* [SIMRDWN](https://github.com/avanetten/simrdwn) - The Satellite Imagery Multiscale Rapid Detection with Windowed Networks (SIMRDWN) codebase combines some of the leading object detection algorithms into a unified framework designed to detect objects both large and small in overhead imagery.
* [Pixel Decoder](https://github.com/Geoyi/pixel-decoder) - A machine learning python package to run deep learning with satellite imagery.
* [LightNet](https://github.com/ansleliu/LightNet) - LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)
## Python
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* [INPE Database](http://www.dgi.inpe.br/CDSR/) - Download free satellite data including MODIS, Landsat (1-7), ResourceSat (1-2) and CBERS (2, 2B and 4) data.
* [Sentinel 2 AWS](http://sentinel-pds.s3-website.eu-central-1.amazonaws.com/) - Sentinel 2 data on Amazon S3.
* [Copernicus Open Access Hub](https://scihub.copernicus.eu/dhus/#/home) - Sentinel data from scihub.
* [Cityscapes Dataset](https://www.cityscapes-dataset.com/) - large-scale dataset that contains a diverse set of stereo video sequences recorded in street scenes from 50 different cities, with high quality pixel-level annotations of 5000 frames in addition to a larger set of 20000 weakly annotated frames.
## Resources
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* [Geopython](https://github.com/urschrei/Geopython) - Notebooks and libraries for spatial/geo Python explorations.
## Conferences
* [FOSS4G](http://foss4g.org/) - Free and Open Source Software for Geospatial.