Accident rates increased due to non-compliance with traffic signs and non-compliance with traffic rules. By using synthetic training data from images of train signs, we can overcome the problem of analysis of traffic data, which varies by country and region. This method is used to create files containing synthetic images to detect traffic signs from different perspectives. With this knowledge and a well-designed Convolutional Neural Network (CNN), we can create a data-driven train recognition and detection system that has accurate detection accuracy and still has action. This article presents the process of recognizing and classifying road signs and traffic signs to create their inventory to help great engineers replace and maintain them. It uses images captured by a camera from a moving car. The system is based on three main stages: color segmentation, recognition and classification. Many researchers in the world of artificial intelligence and technology and Tesla, Uber, Google, Mercedes-Benz, Toyota, Ford, Audi etc. big companies like self-driving cars and self-driving cars. Therefore, in order for this technology to be used correctly, vehicles must be able to interpret traffic signs and make decisions accordingly. This reduces accidents and also helps drivers concentrate on driving rather than looking at every traffic card. The purpose of this document is to provide an effective way of discovering and recognizing traffic signs in India.