This repository provides a dataset of solar cell images extracted from high-resolution electroluminescence images of photovoltaic modules.
The dataset contains 2,426 samples of 300x300 pixels 8-bit grayscale images of functional and defective solar cells with varying degree of degradations extracted from 44 different solar modules. The defects in the annotated images are either of intrinsic or extrinsic type and are known to reduce the power efficiency of solar modules.
All images are normalized with respect to size and perspective. Additionally, any distortion induced by the camera lens used to capture the EL images was eliminated prior to solar cell extraction.
Every image is annotated with a defect probability (a floating point value between 0 and 1) and the type of the solar module (either mono- or polycrystalline) the solar cell image was originally extracted from.
The individual images are stored in the images directory and the corresponding
annotations in labels.csv.
In Python, use utils/elpv_reader in this repository to load the images and the
corresponding annotations as follows:
from elpv_reader import load_dataset
images, proba, types = load_dataset()The code requires NumPy and Pillow to work correctly.
If you use this dataset in scientific context, please cite the following publications:
@inproceedings{Buerhop2018,
author={Claudia Buerhop-Lutz and Sergiu Deitsch and Andreas Maier and Florian
Gallwitz and Christoph J. Brabec},
title={A Benchmark for Visual Identification of Defective Solar Cells in
Electroluminescence Imagery},
booktitle={35th European PV Solar Energy Conference and Exhibition},
year={2018},
note={accepted},
}
@article{Deitsch2018a,
author={Sergiu Deitsch and Claudia Buerhop-Lutz and Andreas Maier and Florian
Gallwitz and Christian Riess},
title={Segmentation of Photovoltaic Module Cells in Electroluminescence Images},
journal={Solar Energy},
year={2018},
note={submitted},
}
@article{Deitsch2018b,
author={Sergiu Deitsch and Vincent Christlein and Stephan Berger and Claudia Buerhop-Lutz and Andreas Maier and Florian
Gallwitz and Christian Riess},
title={Automatic Classification of Defective Photovoltaic Module Cells in
Electroluminescence Images},
journal={Solar Energy},
year={2018},
note={submitted},
}
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For commercial use, please contact us for further information.