Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds
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Updated
Aug 27, 2020 - Python
Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
Download and process satellite imagery in Python using Sentinel Hub services.
Search and download Copernicus Sentinel satellite images
A ready-to-use curated list of Spectral Indices for Remote Sensing applications.
Data Preparation for Satellite Machine Learning
Helper package with multiple U-Net implementations in Keras as well as useful utility tools helpful when working with image semantic segmentation tasks. This library and underlying tools come from multiple projects I performed working on semantic segmentation tasks
Open solution to the Mapping Challenge 🌎
Satellite imagery for dummies.
Small-Object Detection in Remote Sensing (satellite) Images with End-to-End Edge-Enhanced GAN and Object Detector Network
A python package that extends Google Earth Engine.
Code for a winning model (3 out of 419) in a Dstl Satellite Imagery Feature Detection challenge
Satellite Stereo Pipeline
Pytorch implementation of ResUnet and ResUnet ++
A python Two Source Energy Balance model for estimation of evapotranspiration with remote sensing data
Kitware's system for 3D building reconstruction for the IARPA CORE3D program
[IGARSS'22]: A Transformer-Based Siamese Network for Change Detection
🔥TorchSat 🌏 is an open-source deep learning framework for satellite imagery analysis based on PyTorch.
Earth Observation Data Access Gateway
YOLO/YOLOv2 inspired deep network for object detection on satellite images (Tensorflow, Numpy, Pandas).
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