Underground Parking Lot Vehicle Passage and Identification Scene Image Dataset
#Target Detection #Image Recognition #Intelligent Traffic #Vehicle Monitoring #Parking Management
- 30000 records
- 5G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
The current transportation industry faces challenges of accurate identification and real-time management in smart parking and vehicle monitoring. Existing solutions often rely on manual monitoring, which is inefficient and prone to errors. This dataset aims to solve the technical difficulties of target detection and identification by providing high-quality parking lot vehicle images. Data collection uses high-resolution cameras under various lighting conditions to ensure diversity. Quality control is enhanced through multiple rounds of labeling and expert review to ensure annotation accuracy. Data is stored in JPG format, organized with each image accompanied by corresponding annotation information. The core advantage of the dataset lies in its annotation consistency of up to 95% and annotation accuracy of over 90%, using advanced data augmentation techniques to enhance model generalization ability. By using this dataset, the vehicle identification accuracy in related applications can increase by more than 20%, significantly improving the efficiency of intelligent parking management.
Dataset Insights
Sample Examples
276f0429**.jpg|4032*3024|797.36 KB
6297db46**.jpg|4032*3024|627.70 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| vehicle_count | int | The total number of vehicles appearing in the image. |
| license_plate_visibility | bool | Indicates whether the license plates in the image are clearly visible. |
| vehicle_types | string | The different types of vehicles appearing in the image, such as cars, trucks, etc. |
| obstruction_count | int | The number of objects in the image that obstruct vehicles or signs. |
| light_condition | string | The lighting condition when the image was taken, such as bright, dim, etc. |
| vehicle_color | string | The primary color of the vehicle in the image. |
| parking_slot_occupancy | bool | Indicates whether the parking slots in the image are occupied. |
| signage_presence | bool | Indicates whether there are traffic-related signs present in the image. |
| camera_angle | string | The overhead or low angle of the camera from which the image was taken. |
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 are the potential applications of the underground parking vehicle passage and identification scene image dataset?
- This dataset is mainly suitable for applications such as vehicle detection and recognition in intelligent traffic management systems, development of parking management systems, and traffic flow monitoring.
- What are the features of the images in this dataset?
- The image features of this dataset include diverse parking lot environments, various traffic situations, and multi-angle captures of vehicles and identification signs.
- How can this dataset be used to improve traffic management efficiency?
- By using this dataset to train models, systems can automatically detect and recognize vehicle identification, thereby improving the automation, accuracy, and efficiency of traffic flow analysis and management.
- How does this dataset contribute to the development of intelligent parking lots?
- With identification recognition and vehicle passage data, developers can build intelligent parking lot solutions that enable automatic billing, space navigation, and optimized parking management.
- Does this dataset include identification data for multiple vehicle types?
- Yes, this dataset includes identification data for various vehicle types, supporting recognition and classification of different vehicle categories.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Underground Parking Lot Vehicle Passage and Identification Scene Image Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/b57f306e22ea8d44a713b86cef11511d},
urldate={2025-09-15},
keywords={Underground Parking Lot Dataset, Vehicle Identification Dataset, Target Detection, Traffic Data},
version={1.0}
}Using this in research? Please cite us.
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