manideep2510/eye-in-the-sky
Satellite Image Classification using semantic segmentation methods in deep learning
This tool helps urban planners, environmental analysts, or agricultural specialists classify regions in satellite images. It takes raw satellite imagery and outputs segmented images where different land cover types like buildings, roads, or vegetation are clearly identified. The primary users are professionals who need to understand land use and geographical features from aerial perspectives.
317 stars. No commits in the last 6 months.
Use this if you need to automatically identify and delineate different land cover classes within satellite imagery, even with a relatively small dataset.
Not ideal if you require highly detailed segmentation of very small objects or are working with extremely limited computational resources, as it still involves deep learning models.
Stars
317
Forks
86
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 24, 2023
Commits (30d)
0
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