Fuse Box Cover Detection Dataset
#Object detection #Image classification #After-sales maintenance #Circuit protection inspection
- 5000 records
- 1.5G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-04-16
AI Analysis & Value Prop
The current industrial sector faces significant challenges in ensuring the safety and reliability of electrical components, particularly in after-sales maintenance and circuit protection checks. Existing solutions often lack precision and fail to address the variability in fuse box designs, leading to inconsistent inspection results. This dataset aims to provide a robust foundation for developing advanced machine learning models that can accurately detect and classify various conditions of fuse box covers. Data is collected using high-resolution cameras in controlled environments, ensuring optimal lighting and minimal distractions. Quality control measures include multi-round annotations, consistency checks across different annotators, and expert reviews to verify labeling accuracy. The data is organized in JPG format with systematic folder structures for easy access and processing.
Dataset Insights
Sample Examples
1428a2cf**.jpg|1080*722|294.23 KB
3fd92f95**.jpg|1080*700|262.81 KB
13234984**.jpg|1080*723|401.99 KB
89f4bb10**.jpg|1080*1328|796.14 KB
11e13fe7**.jpg|1080*720|348.36 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| object_type | string | The type of object detected in the image, such as fuse box cover, screws, etc. |
| bbox_coordinates | string | The bounding box coordinates for object detection, formatted as x,y,width,height. |
| object_confidence | float | The confidence score of the object detection result. |
| image_brightness | string | The overall brightness value of the image, used to assess shooting quality. |
| image_contrast | string | The contrast information of the image, used to evaluate the prominence of different components. |
| image_sharpness | string | The sharpness of the image, used to determine the clarity of object edges. |
| defect_type | string | The type of defect detected on the fuse box cover, such as cracks, deformations, etc. |
| defect_severity | string | The severity level of the defect, such as minor, moderate, severe. |
| edge_detection_score | string | The clarity score of object edges evaluated using an edge detection algorithm. |
| material_texture | string | The surface texture description of the fuse box cover material, such as smooth, rough, etc. |
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 Fuse Box Cover Detection Dataset contain?
- This dataset contains image data for detecting fuse box covers, identifying and locating them using object detection models.
- What are the application scenarios for using the Fuse Box Cover Detection Dataset?
- This dataset can be used in industrial vision inspection systems to automatically identify and detect fuse box covers, enhancing efficiency on production lines.
- How does the Fuse Box Cover Detection Dataset help improve industrial inspection efficiency?
- By automating fuse box cover detection, this dataset makes the industrial inspection process faster and more accurate, significantly reducing human involvement.
- Which object detection models are suitable for the Fuse Box Cover Detection Dataset?
- Commonly used object detection models include YOLO, Faster R-CNN, and SSD, which can effectively identify and locate fuse box covers.
- What is the value of the Fuse Box Cover Detection Dataset in the industrial field?
- This dataset has significant economic value and quality assurance in the industrial field by reducing downtime and improving product quality.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Fuse Box Cover Detection Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/94e6950b3557fa6eae1cd338e0cbd0a7?dataset_scene_id=2},
urldate={2025-08-28},
keywords={Fuse Box Detection,Industrial Inspection Dataset,Image Classification,Machine Learning Dataset},
version={1.0}
}Using this in research? Please cite us.
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