Traffic Sign Detection

The goal of this project is to create a system that can identify a road sign's location in a picture and categorize it. We created functions to reduce dynamic range, modify image resolution, and convert RGB to grayscale for this purpose. Based on the outcomes of various clustering techniques, we chose to use the K-Means algorithm with five clusters. Additionally, 32x32 resolution photos have been selected as acceptable. A bounding box is created around the sign after selecting the appropriate structure to use. We created the code to operate on every input image because these procedures were initially performed on a single test image. Finally, by inheriting the feature extraction portion of VGG19, a transfer learning model has been created.