太阳能电池图像数据集.zip

# A Benchmark for Visual Identification of Defective Solar Cells in Electroluminescence Imagery This repository provides a dataset of solar cell images extracted from high-resolution electroluminescence images of photovoltaic modules.  ## The Dataset The dataset contains 2,624 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. ## Annotations 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`. ## Usage In Python, use `utils/elpv_reader` in this repository to load the images and the corresponding annotations as follows: ```python from elpv_reader import load_dataset images, proba, types = load_dataset() ``` The code requires NumPy and Pillow to work correctly. ## Citing If you use this dataset in scientific context, please cite the following publications: > Buerhop-Lutz, C.; Deitsch, S.; Maier, A.; Gallwitz, F.; Berger, S.; Doll, B.; Hauch, J.; Camus, C. & Brabec, C. J. A Benchmark for Visual Identification of Defective Solar Cells in Electroluminescence Imagery. European PV Solar Energy Conference and Exhibition (EU PVSEC), 2018. DOI: [10.4229/35thEUPVSEC20182018-5CV.3.15](http://dx.doi.org/10.4229/35thEUPVSEC20182018-5CV.3.15) > Deitsch, S.; Buerhop-Lutz, C.; Maier, A. K.; Gallwitz, F. & Riess, C. Segmentation of Photovoltaic Module Cells in Electroluminescence Images. CoRR, 2018, [abs/1806.06530](https://arxiv.org/abs/1806.06530) > Deitsch, S.; Christlein, V.; Berger, S.; Buerhop-Lutz, C.; Maier, A.; Gallwitz, F. & Riess, C. Automatic classification of defective photovoltaic module cells in electroluminescence images. Solar Energy, Elsevier BV, 2019, 185, 455-468. DOI: [10.1016/j.solener.2019.02.067](http://dx.doi.org/10.1016/j.solener.2019.02.067) BibTeX details: <details> ```bibtex @InProceedings{Buerhop2018, author = {Buerhop-Lutz, Claudia and Deitsch, Sergiu and Maier, Andreas and Gallwitz, Florian and Berger, Stephan and Doll, Bernd and Hauch, Jens and Camus, Christian and Brabec, Christoph J.}, title = {A Benchmark for Visual Identification of Defective Solar Cells in Electroluminescence Imagery}, booktitle = {European PV Solar Energy Conference and Exhibition (EU PVSEC)}, year = {2018}, eventdate = {2018-09-24/2018-09-28}, venue = {Brussels, Belgium}, doi = {10.4229/35thEUPVSEC20182018-5CV.3.15}, } @TechReport{Deitsch2018, Title = {Segmentation of Photovoltaic Module Cells in Electroluminescence Images}, Author = {Sergiu Deitsch and Claudia Buerhop-Lutz and Andreas K. Maier and Florian Gallwitz and Christian Riess}, Year = {2018}, Archiveprefix = {arXiv}, Eprint = {1806.06530}, Journal = {CoRR}, Url = {http://arxiv.org/abs/1806.06530}, Volume = {abs/1806.06530} } @Article{Deitsch2019, 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 = {2019}, volume = {185}, pages = {455--468}, month = jun, issn = {0038-092X}, doi = {10.1016/j.solener.2019.02.067}, publisher = {Elsevier {BV}}, } ``` </details> ## License <a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/">Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License</a>. For commercial use, please contact us for further information.