Tail Light Detection Dataset
#Object Detection #Image Classification #Tail Light Misinstallation Recognition #Maintenance Scene Lighting Positioning
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
In the current industrial landscape, the proper installation and functionality of tail lights are critical for vehicle safety. However, misinstallation often leads to accidents and maintenance issues. Existing solutions such as manual inspections are time-consuming and prone to human error. This dataset aims to address the pressing need for automated tail light misinstallation detection systems by providing labeled images that can be used to train machine learning models. The data is collected using high-resolution cameras in controlled lighting conditions to ensure clarity and consistency. Quality control measures include multi-round annotations and expert reviews to maintain high standards. The dataset is organized in a JPG format, with images stored in designated folders according to their labels.
Dataset Insights
Sample Examples
ba29cb46**.jpg|1280*1494|116.92 KB
c0288d0b**.jpg|1280*1494|167.57 KB
c28d18b5**.jpg|1280*1494|125.89 KB
0a0246ac**.jpg|1280*1494|170.94 KB
854de1f9**.jpg|1280*910|95.31 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| taillight_type | string | The specific type of vehicle tail light, such as brake lights, turn signals, etc. |
| taillight_color | string | The color of the tail light's illumination, such as red, yellow, etc. |
| defect_presence | boolean | Whether there is a tail light defect, such as bulb failure or physical damage. |
| defect_type | string | Specific defect types, such as bulb not lighting or casing cracking. |
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 |
Frequently Asked Questions
- What types of images are included in the Taillight Detection Dataset?
- The Taillight Detection Dataset primarily includes various images of vehicle taillights in the industrial sector for automated recognition and detection.
- What is the application of the Taillight Detection Dataset in the industry?
- This dataset is used to enhance the efficiency of automatic recognition of vehicle taillights in industrial inspections, reducing the need for human intervention.
- How can the Taillight Detection Dataset be used for training object detection models?
- The Taillight Detection Dataset can be used to train object detection models, enabling them to recognize different types of taillights and improve detection accuracy.
- What annotation format does the Taillight Detection Dataset use?
- The dataset typically uses common object detection annotation formats such as Pascal VOC or COCO to facilitate model training and evaluation.
- What are the challenges in the object detection task of the Taillight Detection Dataset?
- Challenges in the taillight detection task include variations in lighting conditions, taillight styles, and angles, which require enhancing the model's robustness.
Can't find the data you need?
Post a request and let data providers reach out to you.
Get this Dataset
Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Tail Light Detection Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/8c31affa02f6c0d324d09262b0799d5a},
urldate={2025-08-28},
keywords={tail light detection,industrial dataset,image classification,object detection,automotive safety},
version={1.0}
}Using this in research? Please cite us.
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder