Datasets
Standard Dataset
Photovoltaic cell anomaly detection dataset
- Citation Author(s):
- Submitted by:
- Binyi Su
- Last updated:
- Tue, 03/15/2022 - 10:40
- DOI:
- 10.21227/pz6t-3s77
- License:
- Categories:
- Keywords:
Abstract
The anomaly detection in photovoltaic (PV) cell electroluminescence (EL) image is of great significance for the vision-based fault diagnosis. Many researchers are committed to solving this problem, but a large-scale open-world dataset is required to validate their novel ideas. We build a PV EL Anomaly Detection (PVEL-AD) dataset for polycrystalline solar cell, which contains 36,543 near-infrared images with various internal defects and heterogeneous background. This dataset contains anomaly-free images and anomalous images with 10 different categories. Moreover, 37,380 ground truth bounding boxes are provided for 8 types of defects. We also carry out a comprehensive evaluation of the state-of-the-art object detection methods based on deep learning. The evaluation results on this dataset provide the initial benchmark, which is convenient for follow-up researchers to conduct experimental comparisons. To the best of our knowledge, this is the first public dataset for PV solar cell anomaly detection that provides box-wise ground truth and focuses on industrial application. Furthermore, this dataset can also be used for the evaluation of many computer vision tasks such as few-shot detection, one-class classification and anomaly generation. More details are presented in https://github.com/binyisu/PVEL-AD
All researchers need to follow the instructions below to access the datasets.
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Download and fill the Datasets Request Form (MUST be hand signed with date). Please use institutional email address(es). Commercial emails such as Gmail and QQmail are NOT allowed.
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Email the signed Datasets Request Form to Subinyi@buaa.edu.cn
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Annotation for boudning boxes are provided to train YOLO-v4-5/EfficientDet D1-7 based detectors
Dataset Files
- annotation_classes.txt (76 bytes)
- train_PVELAD.zip (596.61 MB)
- test_PVELAD.zip (1.80 GB)
- othertypes_PVELAD.zip (1.53 GB)
Documentation
Attachment | Size |
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README_PVELAD.md | 2.27 KB |
Comments
I can't find annotation (Ground truth) For testing dataset