Traffic-Sign-Detection and traffic-sign-detection

These are **competitors** — both implement deep neural network-based traffic sign detection systems with similar real-time inference capabilities, requiring users to choose one codebase over the other rather than use them together.

Traffic-Sign-Detection
50
Established
traffic-sign-detection
50
Established
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 24/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 24/25
Stars: 292
Forks: 114
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 336
Forks: 101
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About Traffic-Sign-Detection

hoanglehaithanh/Traffic-Sign-Detection

Traffic signs detection and classification in real time

This system helps analyze video footage to identify and categorize traffic signs in real-time. It takes a video file as input and outputs the video with detected traffic signs highlighted and classified. This is useful for researchers or developers working on autonomous driving features or traffic monitoring systems.

autonomous-vehicles traffic-monitoring computer-vision video-analysis

About traffic-sign-detection

aarcosg/traffic-sign-detection

Traffic Sign Detection. Code for the paper entitled "Evaluation of deep neural networks for traffic sign detection systems".

This project provides pre-trained models and code for automatically identifying traffic signs in images or video. It takes raw image data as input and outputs the location and type of traffic signs present. This is designed for researchers and engineers developing advanced driver-assistance systems (ADAS) or autonomous vehicle technology.

autonomous-driving traffic-management computer-vision ADAS object-detection

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