venkanna37/Label-Pixels
Label-Pixels is the tool for semantic segmentation of remote sensing images using Fully Convolutional Networks. Initially, it is designed for extracting the road network from remote sensing imagery and now, it can be used to extract different features from remote sensing imagery.
No commits in the last 6 months.
Stars
73
Forks
27
Language
Python
License
—
Category
Last pushed
Nov 07, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/venkanna37/Label-Pixels"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
mapbox/robosat
Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings,...
ucam-eo/tessera
[CVPR26] TESSERA is a foundation model that can process time-series satellite imagery for...
arplaboratory/satellite-thermal-geo-localization
[IROS 2023] Official repository for "Long-range UAV Thermal Geo-localization with Satellite Imagery"
HakaiInstitute/habitat-mapper
Segmentation Tools for Remotely Sensed RPAS Imagery
WangLibo1995/BuildFormer
Building Extraction from remote sensing image using Vision Transformer, IEEE Transactions on...