Mobiusi/Dust-Cup-Not-Closed-Detection-Dataset-for-Vacuum-Cleaners

Dust Cup Not Closed Detection Dataset for Vacuum Cleaners

In the current industrial sector, vacuum cleaners, as important cleaning equipment, can have their suction and sealing performance severely affected if the dust cup is not closed, leading to a decrease in user experience. Existing detection methods mainly rely on manual inspection, which is inefficient and prone to misjudgment. This dataset aims to enhance the detection accuracy of dust cup closure status through machine vision technology, meeting the industrial need for efficient and accurate detection. The dataset is captured using high-resolution cameras in a standard environment to ensure image quality. We ensure the consistency and accuracy of annotations through multiple rounds of labeling and expert review, and it is ultimately stored in JPG format for ease of subsequent model training and testing.

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
cup_status	string	Checking whether the dust cup of the vacuum cleaner is closed.
confidence_score	float	The confidence score of the model's judgment on the dust cup's closed status.
bounding_box	string	The bounding box coordinates identifying the dust cup area, formatted as (x, y, width, height).
image_quality	float	The sharpness or quality rating of the picture.
illumination_level	float	The brightness level of lighting in the image.
image_clarity	float	The level of clarity of the image.
object_count	int	The number of objects (dust cups) detected in the image.

Compliance Statement

Authorization Type	CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
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

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com