Rainy Weather In-Car Driving Perspective Dataset
#target detection #scene understanding #intelligent transportation #autonomous driving #safety monitoring
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-03-19
AI Analysis & Value Prop
The current transportation industry faces numerous challenges in autonomous driving under rainy conditions, such as reduced visibility and slippery roads, resulting in decreased target detection accuracy. Existing solutions are mostly concentrated on sunny data, lacking rain-specific scene data, leading to insufficient model adaptability in rainy environments. This dataset aims to provide abundant rainy weather in-car driving perspective images to help improve the recognition capability of autonomous driving systems in complex weather conditions. Data collection is performed using high-definition cameras in rainy environments across different cities to ensure diverse traffic scenes coverage. The data has undergone multiple rounds of annotation, utilizing consistency checks and expert review to ensure annotation quality. The data is stored in JPG format, with each image accompanied by multiple annotation fields to facilitate subsequent processing and analysis. The dataset contains a total of 5000 images, with a total file size of approximately 1.2G.
Dataset Insights
Sample Examples
18efeba9**.jpg|3024*4032|664.99 KB
23cf9342**.jpg|3024*4032|780.09 KB
10bbbab7**.jpg|1927*2558|321.39 KB
47bb29be**.jpg|3072*4080|1.06 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| weather_condition | string | The weather condition shown in the image, such as light rain, moderate rain, or heavy rain. |
| visibility_level | string | The level of visibility from the driver's perspective in the image, such as high, low, or moderate. |
| road_condition | string | The condition of the road as shown in the image, such as waterlogged, slippery, or dry. |
| traffic_density | string | The traffic density shown in the image, such as congested or sparse. |
| vehicle_type | string | The types of vehicles identified in the image, such as car, truck, or motorcycle. |
| pedestrian_presence | boolean | Indicates whether pedestrians are present in the image. |
| traffic_signal_presence | boolean | Indicates whether there are traffic signals in the image. |
| wiper_activity | boolean | Indicates the presence of windshield wiper activity in the image. |
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 |
Frequently Asked Questions
- What are the applications of the Rainy Car Driving View Dataset?
- This dataset can be applied in fields such as autonomous driving, traffic monitoring, and weather impact analysis.
- What is the main goal of this dataset?
- The main goal of this dataset is to assist researchers in developing and testing vehicle object detection models under rainy conditions.
- What types of vehicle data does this dataset contain?
- The dataset primarily contains image data of various vehicles captured in rainy environments.
- How can rainy data be used to improve the safety of autonomous driving systems?
- By incorporating rainy data into models, autonomous driving systems can better recognize and respond to driving environments under adverse weather conditions, thus improving safety.
- Is the Rainy Car Driving View Dataset suitable for weather impact analysis?
- Yes, this dataset can be used to analyze how rainy weather affects traffic conditions and driving behavior.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Rainy Weather In-Car Driving Perspective Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/1ee291a11fd1365d2f486fc88083d9b5},
urldate={2025-09-15},
keywords={rainy dataset, in-car image, target detection, autonomous driving, traffic safety},
version={1.0}
}Using this in research? Please cite us.
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