Traffic signal identification using Keras LeNet architecture. Identify 43 different classes of images with over 90% accuracy.
-
Updated
Aug 24, 2020 - Jupyter Notebook
Traffic signal identification using Keras LeNet architecture. Identify 43 different classes of images with over 90% accuracy.
Creation of a model based on yolov8 that uses the file downloaded from https://www.kaggle.com/datasets/valentynsichkar/traffic-signs-dataset-in-yolo-format/data as a custom dataset to detect traffic signs. The detected signals can be recognized using the project https://github.com/ablanco1950/RecognizeTrafficSign.
Add a description, image, and links to the traffic-signal-identification topic page so that developers can more easily learn about it.
To associate your repository with the traffic-signal-identification topic, visit your repo's landing page and select "manage topics."