Drone Imagery Object Detection - YOLO

The dataset utilized in this study was meticulously collected using drone video footage captured across seven distinct locations in Lithuania (Eastern Europe), each characterized by varying altitudes, camera angles, and weather conditions to ensure a diverse range of visual perspectives. The videos was taken from three cities. These are Vilnius, Šiauliai and Telšiai. The locations included a variety of road types such as intersections (T and + forms), slip lanes, normal roads, roundabouts, crossroads, parking areas, controlled T-form intersections, and dirt road intersections. Vilnius, being the capital city, presented a more complex traffic structure with multi-lane roads and heavy vehicle density. In contrast, Šiauliai and Telšiai provided a mix of suburban and rural environments with fewer vehicles. This geographical diversity ensures that the dataset captures a wide range of real-world traffic scenarios.

Labels: Car, Bus, Truck, Padestrian
Note: The study is about semi supervised learning. Only labeled data was provided here