This vehicle identification project utilizes the YOLOv5 deep learning model for detecting and classifying vehicles from images, videos, and live streams. It supports real-time inference, saving outputs with bounding boxes, confidence scores, and class labels, making it ideal for traffic monitoring and smart surveillance systems.
computer-vision deep-learning image-processing pytorch video-processing object-detection traffic-monitoring vehicle-detection data-augmentation non-maximum-suppression tensorflow-lite yolov3 real-time-detection smart-surveillance yolov5 model-inference automated-labelling
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Updated
Dec 23, 2024 - Python