saizk/Deep-Learning-for-Solar-Panel-Recognition
CNN models for Solar Panel Detection and Segmentation in Aerial Images.
This project helps solar energy analysts, urban planners, or utility managers automatically identify and map solar panels from overhead imagery. By feeding the system aerial photos or satellite images, you can get precise outlines and locations of solar panel installations. This allows for quick assessments of solar adoption, energy infrastructure, or compliance.
125 stars.
Use this if you need to rapidly detect and precisely outline solar panels across large areas using aerial or satellite imagery for planning or analysis.
Not ideal if your primary goal is to predict solar energy output or analyze system performance, as this tool focuses solely on panel identification and mapping.
Stars
125
Forks
48
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Feb 20, 2026
Commits (30d)
0
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