robosat
Image feature extractor
An end-to-end pipeline for extracting features from aerial and satellite imagery using convolutional neural networks
Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds
2k stars
198 watching
384 forks
Language: Python
last commit: over 4 years ago
Linked from 3 awesome lists
aerial-imagerymachine-learningopenstreetmapsatellite-imagerysegmentation
Related projects:
Repository | Description | Stars |
---|---|---|
| Automates satellite image extraction and storage from public constellations at scale. | 76 |
| Develops deep learning models to classify and annotate pixel-level details in satellite images | 21 |
| An aerial imagery segmentation tool using deep learning techniques to identify buildings and roads from satellite images. | 27 |
| A custom Home Assistant component that extracts and displays live maps from Xiaomi vacuum devices | 1,179 |
| Automatically annotates satellite images with OpenStreetMap data | 461 |
| A tool to extract hidden data from images by detecting embedded files and strings. | 116 |
| Semantic segmentation using convolutional neural networks for aerial and satellite images | 260 |
| An implementation of a deep learning model for semantic segmentation of high-resolution urban scene images. | 13 |
| A tool to extract tiles from compressed GeoTIFF files without decompression. | 65 |
| A tool for manually segmenting images from satellite data with AI assistance | 141 |
| A computer vision tool for analyzing map images at scale. | 97 |
| A Python package for analyzing and processing remote sensing data | 126 |
| Provides tools for processing and analyzing satellite imagery using Google Earth Engine (GEE) data | 3 |
| A Pythonic library for semantic tree segmentation from aerial imagery | 243 |
| A PyTorch-based toolbox for building and training semantic segmentation models | 408 |