Datasets:
task_categories:
- object-detection
language:
- en
tags:
- computer vision
- code
- python
- traffic
- singapore
- roadway
pretty_name: Traffic Images for Object Detection
size_categories:
- 10K<n<100K
Traffic Image Data Extraction Through Singapore Government API
Description
The Singapore government offers real-time images from traffic cameras across the nation through its API. This dataset compiles a comprehensive image dataset in the form of a DataFrame by extracting data for the month of January 2024 from 6 pm to 7 pm each day using the API.
Use Cases
The resulting dataset will facilitate easy integration into various use cases including:
Object Detection
Utilize the dataset for training object detection models to identify and analyze vehicles, pedestrians, and other objects in the traffic images.
Traffic Trend Analysis
Leverage time-series analysis to identify and analyze traffic trends over specific periods. This can provide valuable insights into peak traffic times, congestion patterns, and potential areas for infrastructure improvement.
Road Safety Assessment
Implement computer vision algorithms to assess road safety by analyzing traffic images for potential hazards, unusual road conditions, or non-compliance with traffic rules. This use case aims to enhance road safety monitoring and contribute to the development of intelligent transportation systems.
Dataset Details
The dataset will comprise the following columns:
- Timestamp: Date and time of the image acquisition from LTA's Datamall.
- Camera_ID: Unique identifier assigned by LTA to each traffic camera.
- Latitude: Geographic coordinate of the camera's location (latitude).
- Longitude: Geographic coordinate of the camera's location (longitude).
- Image_URL: URL providing direct access to the captured traffic image.
- Image_Metadata: Metadata of the image file including height, width, and MD5 hash.
API Documentation
For more details on accessing the traffic camera images, visit the API Documentation.
Refer to the attached use_case.py file to understand how this dataset can be used for analysis and object detection.