Dark Mode
Smart City Traffic Vision Dataset
Data Science and Analytics
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset is designed for computer vision applications focusing on city intersections. It enables the monitoring and analysis of traffic flow by detecting various vehicle types. This data is valuable for understanding traffic patterns, identifying congestion points, and determining peak hours. It supports city planning initiatives by providing insights for road design, public transportation infrastructure, and vehicular traffic regulation. Additionally, the dataset aids in the development of autonomous vehicles by helping them identify different vehicle types for safer and more efficient navigation. Advertising companies can use it to assess the types of vehicles passing through specific locations for targeted placements, and insurance companies can leverage it to analyse accident-prone areas and inform risk evaluations.
-
Columns
-
filename: The name of the image file, typically derived from raw video clips.
-
width: The width of the image in pixels.
-
height: The height of the image in pixels.
-
class: The classification of the detected object, such as 'car', 'motorcycle', or 'bus'.
-
xmin: The minimum X-coordinate of the bounding box around the detected vehicle.
-
ymin: The minimum Y-coordinate of the bounding box around the detected vehicle.
-
xmax: The maximum X-coordinate of the bounding box around the detected vehicle.
-
ymax: The maximum Y-coordinate of the bounding box around the detected vehicle.
-
Distribution
The dataset contains a total of 1902 files and is organised into five folders for test, training, and validation purposes, each accompanied by an annotation file. The 'test' folder alone includes 189 files. Version 1 of the dataset has a size of 155.7 MB. The data is structured in a tabular format, typically a CSV, detailing detections within associated image files.
-
Usage
-
Traffic Flow Analysis: Monitor and analyse traffic flow at busy intersections, identifying vehicle types, traffic patterns, congestion, and peak hours.
-
City Transportation Planning: Inform decisions related to road design, public transportation infrastructure, and vehicular traffic regulation.
-
Autonomous Vehicle Development: Aid in creating smarter self-driving cars by enabling correct identification of vehicle types, leading to safer and more efficient navigation.
-
Vehicle-Based Advertising: Assess vehicle types in specific locations to guide strategies for billboard placement or targeted advertisements.
-
Crash Analytics and Insurance Risk Evaluation: Analyse accident-prone areas by identifying vehicle types involved, which can assist in adjusting insurance premiums or identifying high-risk zones.
-
Coverage
This dataset focuses on urban areas and city intersections. The data primarily covers various vehicle types observed within these environments. Specific geographic regions, time ranges, or demographic details beyond vehicle classes are not detailed.
-
License
Attribution 4.0 International (CC BY 4.0)
-
Who Can Use It
-
City planning departments: For infrastructure and traffic regulation.
-
Autonomous vehicle developers: To enhance self-driving car algorithms.
-
Advertising companies: For strategic billboard placement and targeted ads.
-
Insurance companies: For risk assessment and crash analysis.
-
Traffic analysts and researchers: To study traffic patterns and urban mobility.
-
Computer vision engineers: For training and validating object detection models.
-
Dataset Name Suggestions
-
Urban Intersection Vehicle Analysis Dataset
-
Traffic Vehicle Classification Data
-
Smart City Traffic Vision Dataset
-
Intersection Object Detection Data
-
Attributes
Original Data Source: Smart City Traffic Vision Dataset
QUALITY