/Automatic-Faults-Detection-of-Photovoltaic-Farms-using-Thermal-Images

This project employs YOLOv5, a state-of-the-art deep learning model, to detect temperature-based faults in PV modules using thermal imagery. YOLOv5 accurately identifies photovoltaic arrays, single PV modules, and faulted PV modules. This model is integrated into a UAV quadcopter for real-time fault detection at the VITC campus

Primary LanguagePythonMIT LicenseMIT

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