Photovoltaic Solar Panel Surface Defect Detection and Localization Dataset

#object detection #defect localization #image classification #model evaluation #Photovoltaic module quality control #solar farm drone inspection #module maintenance screening #defect sample management

5153
0.4GB
piece
CATL
MOBIUSI INC

Updated:2026-11-05

AI Analysis & Value Prop

This dataset is designed for identifying surface defects on photovoltaic solar panels and includes images with corresponding annotations for training and evaluating visual detection models. Each record provides fields such as an image identifier, image and annotation file paths, class ID, image width and height, and image format, supporting data organization, annotation parsing, and training pipeline setup. It is suitable for photovoltaic module quality inspection, defect localization, and intelligent inspection system development.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
image_id	string	A unique identifier for the image record.
image_path	string	The file path or location of the image.
label_path	string	The file path or location of the annotation associated with the image.
category_id	array	The identifier for the annotated defect class.
image_width	number	The image width in pixels.
image_format	string	The image file format.
image_height	number	The image height in pixels.

Compliance Statement

Authorization Type	Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What does the dataset contain?: It contains photovoltaic solar panel images and related annotation information, with fields for image identifiers, image paths, annotation file paths, class IDs, image dimensions, and image formats.

Which model tasks can it support?: It can support surface defect detection and localization for photovoltaic modules. It may also serve as a starting point for defect classification, model validation, and quality inspection workflow prototyping.

What are the dataset size and image specifications?: The available information does not specify the sample count, exact resolution range, or complete defect class list. Each record includes image width, height, and format fields; verify the specifications against the delivered files and annotations.

How can I access the data, and what are the licensing terms?: Check the dataset product page for available access methods, delivery details, and licensing terms. Confirm the applicable license scope and restrictions before using the data in commercial projects or redistributing it.

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Cite this Work

@dataset{Mobiusi2026,
  title={Photovoltaic Solar Panel Surface Defect Detection and Localization Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/dd347458e2e355ec20424acd0b3777d8},
  urldate={2026-11-03},
  keywords={photovoltaic defect detection dataset,solar panel defects,PV module images,surface defect annotations,object detection data,defect localization data,solar panel inspection,automated PV inspection},
  version={1.0}
}

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