uav-traffic-vision is an open-source object detection model based on YOLO, designed for analyzing UAV (drone) aerial imagery using the VisDrone2019-DET dataset. It enables researchers to detect and classify small objects in aerial images, supporting academic and research applications in surveillance and remote sensing.
In the Other AI space, Uav Traffic Vision takes a focused approach. It focuses on detecting and classifying objects in UAV aerial imagery for research and surveillance tasks. Uav Traffic Vision is an open-source project aimed at computer vision researchers. The project is open source (Open Source). Uav Traffic Vision is available on the web, API, and the command line.
Behind Uav Traffic Vision is steven0226, and the product first shipped in 2019. The project is developed in the open on GitHub with 2.4k stars. Among its 5 catalogued features are object detection, aerial imagery support, and small object detection.
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