Photovoltaic Module Hotspot Defect Detection and Localization Dataset

#Hotspot object detection #defect localization #bounding box regression #image classification #model evaluation #Solar farm module inspections #drone-based thermal screening #module fault prioritization #maintenance work-order localization #low-output anomaly screening

22352
1.17GB
piece
CATL
MOBIUSI INC

Updated:2026-11-05

AI Analysis & Value Prop

This dataset contains photovoltaic module images and corresponding location annotations for hotspot defects, supporting the development and evaluation of hotspot detection models. Each record provides an image identifier, image path, annotation file path, class ID, image width and height, and image format to help associate images with their annotations. The data can support solar farm inspections, module fault screening, and computer vision research; confirm the actual sample count, collection conditions, and annotation format from the dataset files.

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 to the image.
label_path	string	The file path to the image annotation.
category_id	array	The identifier for the annotated defect category.
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 module images and information related to hotspot defect localization annotations. Fields include an image identifier, image and annotation file paths, class ID, image dimensions, and image format.

How many samples are included, and what are the image dimensions?: The available information does not specify the total sample count or a standard resolution. Image width and height are provided as fields, allowing users to inspect or filter individual image dimensions; refer to the actual files for details.

Which models and tasks is the data suitable for?: The data can support photovoltaic hotspot detection, defect localization, image classification, model evaluation, and validation of module inspection workflows. Before training, check that the annotation file format matches your model requirements.

How can I obtain the data and check its license?: Check the dataset listing for available access methods, file details, and licensing terms. The information provided here does not specify download options or license scope, so consult the published terms before commercial use or redistribution.

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Cite this Work

@dataset{Mobiusi2026,
  title={Photovoltaic Module Hotspot Defect Detection and Localization Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/01cb4bbab1bdf5dbb54cd0e13e38eb1c},
  urldate={2026-11-03},
  keywords={photovoltaic hotspot dataset,solar panel defect detection,hotspot object detection,solar panel fault recognition,PV inspection images,module localization annotations,solar O and M AI,thermal defect data},
  version={1.0}
}

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