Door Handle Detection Dataset
#Object Detection #Image Classification #Industrial Inspection #Quality Control #Manufacturing #Automation
- Records
- 5000 records
- Size
- 1.5G
- Format
- JPG/PNG/JSON
- Provider
MOBIUSI INC- Updated
- v1.02026-11-04
AI Analysis & Value Prop
In the current industrial landscape, the quality control of door handles is critical yet challenging due to the high variability in manufacturing processes. Existing solutions often rely on manual inspection, which is time-consuming and prone to human error. This dataset aims to address the technical issues related to automated detection and classification of door handles to enhance efficiency and accuracy. The dataset comprises images collected from various production lines, with a focus on different handle designs and assembly scenarios. Data collection involved using high-resolution cameras in controlled environments to ensure consistency. Quality control measures included multiple rounds of annotations by trained personnel and regular audits to maintain label accuracy. The images are stored in JPG format, organized by categories of door handles.
Overview
Dataset Insights
Preview
Sample Examples
1f0e468c**.png|2421*1500|1.00 MB
329a88fb**.png|2034*1500|837.20 KB
e3e0b67f**.png|2310*1500|988.33 KB
b2777435**.png|2244*1500|837.01 KB
25d4f116**.png|2303*1500|1.30 MB
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| object_type | string | This field is used to label the specific type of door handle in the image, such as knob type, lever type, etc. |
| object_count | int | This field is used to indicate the number of door handles in the image. |
| object_position | string | This field is used to label the coordinate information of the door handle's position in the image. |
| environment_context | string | This field is used to describe the background information of the environment where the door handle is located in the image, such as indoors or outdoors. |
| material_type | string | This field is used to label the material of the door handle, such as metal or plastic. |
| color | string | This field is used to specify the color of the door handle. |
| condition | string | This field is used to describe the condition of the door handle, such as new, old, or damaged. |
| installation_type | string | This field is used to describe the installation method of the door handle, such as recessed or exposed. |
| luminosity | float | This field is used to specify the light intensity on the door handle in the image. |
Trust
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
FAQ
Frequently Asked Questions
- What is the Door Handle Detection Dataset?
- The Door Handle Detection Dataset is an object detection dataset aimed at enhancing the efficiency and accuracy of door lock control systems.
- In which industries is the Door Handle Detection Dataset applied?
- The Door Handle Detection Dataset is primarily used in the industrial sector, particularly in industries related to door lock control systems.
- What modalities of data does the Door Handle Detection Dataset contain?
- The Door Handle Detection Dataset contains image data modality.
- What goals can be achieved using the Door Handle Detection Dataset?
- Using the Door Handle Detection Dataset can improve the detection efficiency and accuracy of door lock control systems.
- What is the primary use of the Door Handle Detection Dataset?
- The primary use of the Door Handle Detection Dataset is for training and testing the performance of object detection algorithms in door lock control systems.
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Cite this Work
@dataset{Mobiusi2025,
title={Door Handle Detection Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/ff5d13a1d330914133043b8190c651ed?dataset_scene_id=2},
urldate={2025-08-28},
keywords={Door Handle Detection,Industrial Quality Control,Image Dataset,Object Detection Dataset},
version={1.0}
}Using this in research? Please cite us.
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