night_v1 Computer Vision Project
Updated 2 years ago
Here are a few use cases for this project:
-
Night-time Traffic Monitoring: night_v1 can be used to monitor and analyze traffic at night by identifying different types of vehicles such as rear, front, heavy rear, or heavy front. This information can help manage traffic flow and detect potential issues like congestion or accidents during low light conditions.
-
Intelligent Adaptive Headlights: The model can be integrated into advanced driver-assistance systems (ADAS) in vehicles to improve headlight performance. By recognizing oncoming vehicles and their orientation, the system can automatically adjust the beam pattern, preventing glare for other drivers while maintaining optimal visibility for the user.
-
Surveillance and Security: night_v1 can be employed in security cameras to identify different types of vehicles in low light scenarios, providing valuable real-time data to law enforcement agencies and private security companies for crime prevention and rapid response during night operations.
-
Night-time Parking Management: The computer vision model can be used in smart parking systems to detect vacant parking spaces and monitor parked vehicles during the night, assisting drivers in finding available spots and improving overall parking management in urban areas.
-
Road Maintenance and Infrastructure: Authorities responsible for road maintenance can use night_v1 to analyze nighttime images and detect any road issues or potential hazards, such as poor sign visibility, that should be addressed to ensure road user safety. The model can detect rear, np (no parking), and front signs, as well as monitor the conditions of heavy rear and heavy front vehicles.
Build Computer Vision Applications Faster with Supervision
Visualize and process your model results with our reusable computer vision tools.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
night_v1_dataset,
title = { night_v1 Dataset },
type = { Open Source Dataset },
author = { SmartScan },
howpublished = { \url{ https://universe.roboflow.com/smartscan/night_v1 } },
url = { https://universe.roboflow.com/smartscan/night_v1 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { may },
note = { visited on 2024-11-08 },
}