Found 78 repositories(showing 30)
A Computer Vision based Traffic Signal Violation Detection System from video footage using YOLOv3 & Tkinter. (GUI Included)
alihadimoghadam
A Computer Vision based Traffic Signal Violation Detection System from video footage using YOLOv3 & Tkinter. (GUI Included)
modhisathvik7733
Due to the growing population and people's need for comfort, more automobiles are being purchased, particularly in urban areas. This can result in heavy traffic, indicating that traffic violations are becoming more dangerous in every corner of the world. As a result, people's awareness decreases, and there are more accidents, which may result in the loss of many lives. The existing system has less accuracy and slow detection of violations, here we are using YOLO and OCR algorithms for object and number plate detection, these algorithms can detect the violation at high speed with good accuracy. The proposed system can detect the most common types of traffic violations in real-time through computer vision techniques and it also leverages good results with an accuracy of 88.3%. The proposed traffic violation detector can identify signal violations, and the individuals are informed that they will be apprehended if they break a traffic law. The proposed system is faster and more efficient than human, as known already traffic police is the one who captures the image of individuals violating traffic rules but the traffic police will not be able to capture more than one violation simultaneously. When compared to other algorithms YOLO is found to be more advantageous and has higher efficiency and accuracy.
suryasagar12
Due to the growing population and people's need for comfort, more automobiles are being purchased, particularly in urban areas. This can result in heavy traffic, indicating that traffic violations are becoming more dangerous in every corner of the world. As a result, people's awareness decreases, and there are more accidents, which may result in the loss of many lives. The existing system has less accuracy and slow detection of violations, here we are using YOLO and OCR algorithms for object and number plate detection, these algorithms can detect the violation at high speed with good accuracy. The proposed system can detect the most common types of traffic violations in real-time through computer vision techniques and it also leverages good results with an accuracy of 88.3%. The proposed traffic violation detector can identify signal violations, and the individuals are informed that they will be apprehended if they break a traffic law. The proposed system is faster and more efficient than human, as known already traffic police is the one who captures the image of individuals violating traffic rules but the traffic police will not be able to capture more than one violation simultaneously. When compared to other algorithms YOLO is found to be more advantageous and has higher efficiency and accuracy.
pratyushnandi
Intelligent Traffic Signal and Violation Detection System
ranashardul
A traffic violation detection system using PyQt5 for GUI, OpenCV for image processing, and TensorFlow for machine learning. The project includes real-time detection of signal, parking, and direction violations, with features for adding cameras, managing records, and generating violation reports.
No description available
shraddha323
Traffic Signal Violation Detection System
Sameer12062003
Traffic Signal Violation Detection System
The goal of the project is to automate the traffic signal violation detection system and make it easy for the traffic police department and tracking the vehicle and their activities accurately is the main priority of the system.
No description available
No description available
Using computer vision and deep learning to develop a system that addresses road safety concerns by analyzing video and image data to detect vehicle violations of traffic signals. Leveraging advanced computer vision algorithms, object detection, and real-time video analysis, this system supports law enforcement and reduces accidents. SDG 11
No description available
Chandan9737
Traffic Violation Detection System using YOLOv8 and OpenCV to detect No-Helmet, Triple Riding, and Signal Jumping violations in video/images.
RagavBoobal
Automate traffic violation detection system This system is very helpful to traffic police to monitor the traffic and to find the vehicles which are violating the traffic rules Detecting the vehicles which are violating the traffic rules at signals such as crossing the white lanes and moving before the green signals etc..,
suzzzal
This project is a multimodal AI system that monitors live CCTV feeds to automatically detect: ; Traffic violations: wrong-way driving, signal jumping, no helmet ; Crimes & hazards: fights, fire, explosions, thefts ; Civic issues: roadblocks, garbage piles, damaged roads ,Emergencies: accidents, siren detection
NIHLA098
🚦 AutoGuard-AI is a real-time traffic violation detection system using YOLOv8 and OpenCV. It detects helmet violations, triple riding, and signal jumping, logs events with timestamps, and saves image evidence—ideal for smart city enforcement systems.
Traffic Signal Violation Detection System
srijasabarinathan
Traffic-signal-violation-detection-system
vinaychintu29
No description available
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blackdeltatechnologies
No description available
ShubhamP510
No description available
MichalSimko
Detection on Images traffic
No description available
KayalaDurgaEswar
This project is an AI-based Traffic Signal Violation Detection System that uses the YOLOv8 object detection model and OpenCV to detect vehicles violating traffic signals in real-time. The system monitors traffic lights, identifies active red lights, and flags vehicles that cross a designated region of interest (ROI) during a red signal.
No description available