Decentralized solar electricity production has become common in Syria due to unreliability and inconsistent delivery from the national electric grid. Estimating output from decentralized solar is vital for grid integration and reconstruction efforts currently underway in Syria. Our goal in this project was to develop a deep learning model capable of detecting panels (bounding box), estimating their area (segmentation), and predicting the bottom corners of the panel assembly (corner prediction).