We categorized road signs into four distinct categories using the YOLOv4 model. To fasten the training process, we employed transfer learning, leveraging pre-trained YOLOv4 weights that had already undergone training for 137 convolutional layers. Subsequently, we utilized these pre-trained model weights to classify road signs in images and videos by analyzing each frame individually with our YOLOv4 model. Moreover, we successfully incorporated our YOLOv4 model into a Flask website, enabling road sign detection from images, videos, and even webcam streams.
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Rupesh-Kataria/Road_Sign_Detection
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Creating a project for road sign detection using yolov4 to detect road sign on images and using DeepSort algorithim to detect road sign on a video
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