Datasets:
file_name stringclasses 5
values | quality stringclasses 5
values | vehicle_type stringclasses 3
values | license_plate_number stringclasses 4
values | parking_location stringclasses 2
values | violation_type stringclasses 2
values | vehicle_color stringclasses 4
values | direction_of_park stringclasses 4
values | obstruction_status stringclasses 5
values | image_quality stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|
0d6cc4e65e83a067dbba73d4ba5eb898.jpg | 1920*2560 | Small car | Unrecognizable | On sidewalk | Parking on sidewalk | Blue, white | Parallel parking | Causes partial obstruction | Clear |
1f55dbc6454cc289c6e903ca7c883eb5.jpg | 2447*1352 | Small vehicle | Unrecognizable | On the sidewalk | Parking on the sidewalk | White | Perpendicular to the road | Causes obstruction | Clear |
bce936ed68b452c1298e4691a1ee117f.jpg | 1295*1727 | Small car | Unrecognized | On the sidewalk | Parking on the sidewalk | Black | Parallel to the road | Causing some obstruction to road traffic | Clear |
cb66b5b0018657647bcfc4466c634dc9.jpg | 2422*1199 | Small vehicle | License plate partially obscured | On the sidewalk | Parking on the sidewalk | Left: Black, Right: White | Perpendicular to the road | Causing obstruction to sidewalk traffic | Clear |
fec73b95ba71c46cf1666ffa5b1d7ff4.jpg | 4032*2268 | Small Vehicle | 鄂A L6815, 浙F 3PT68 | On the sidewalk | Parking on the sidewalk | White | Front facing out | Causes obstruction to road traffic | Clear |
Illegal Parking Automatic Recognition Dataset
The current transportation industry faces challenges such as low efficiency and high omission rates in monitoring illegal parking. Traditional monitoring often relies on manual inspections, leading to resource waste and potential hazards. Existing solutions usually cannot adapt to complex urban environments such as lighting changes and obstructions, limiting the accuracy and timeliness of recognition. This dataset aims to provide a high-quality image dataset for illegal parking, solving the technical problems of automatically recognizing illegally parked vehicles to meet the needs of intelligent transportation systems. The dataset is collected by surveillance cameras in multiple cities, organized and annotated using a standardized image processing workflow. The data collection process includes capturing under different lighting and weather conditions to ensure data diversity. We implemented multiple rounds of annotation, consistency checks, and expert reviews as quality control measures to ensure high data quality. Data is stored in JPG format, with metadata corresponding to each image file recorded in a JSON file.
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| vehicle_type | string | The type of vehicle identified, such as a passenger car, truck, motorcycle, etc. |
| license_plate_number | string | The license plate number of the identified vehicle. |
| parking_location | string | The specific parking location where the vehicle is identified. |
| violation_type | string | The type of parking violation committed by the vehicle, such as parking on a sidewalk or in a no-parking zone. |
| vehicle_color | string | The color of the identified vehicle. |
| direction_of_park | string | The orientation in which the vehicle is parked. |
| obstruction_status | boolean | Determines whether the parked vehicle is causing an obstruction to traffic. |
| image_quality | string | An assessment of the image quality, such as clear, unclear, etc. |
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
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