Detecting-defects-in-solar-panels
Abstract
This project aims to detect defective solar panels in a solar array,by performing semantic segmentation. The panels are then segmented into
- Defect: LHS(Light Hot Spot)
- Defect: DHS(Dark Hot Spot)
- Defect: BP (ByPass diode)
- No defect: Normal
About Folders-Navigate easier:
- Final Notebook : Contains the finalized notebook which has all the models trained with information on errors and screenshots of predicted images.
- Annotation : Contains a text file about annotations used, steps taken and problems encountered.
- Preprocessing : Contains notebook used to generate the dataset and the details about steps taken during preprocessing , problems encountered and such.
- Training and results : Contains a summary of models trained and information on them.
Example of the defects:
