the Real-World Scenarios Dataset (RWSD)

A custom training dataset, called the Real-World Scenarios Dataset (RWSD), was created by merging multiple existing datasets, e.g., QUADCOPTER, Drone Detection, MID-GARD dataset, and supplementing them with challenging conditions. Specifically, for the acquisition of the RWSD dataset, a DJI Matrice M600 Pro UAV platform was used to collect experimental data, with the UAV flown at varying altitudes to capture the images. Specifically, the dataset was collected from an aerial perspective, where a camera integrated into the UAV captured images of various ground objects and backgrounds. The proposed dataset comprises 14,592 images, including diverse backgrounds such as urban, indoor, outdoor, meadow, bright, and gloomy conditions. In addition, in our dataset, the UAV distributions are dispersed with a relatively uniform horizontal and vertical spread, which enhances the robustness of models trained on this data. The resulting dataset includes multiple UAV types, such as fixed-wing, medium, and micro rotor drones. To ensure the robustness of models trained on our dataset, we paid special attention to scale diversity. The RWSD dataset contains UAVs captured at various distances, resulting in a wide range of object scales from 30x30 to 600x600 pixels, which poses a significant challenge for multi-scale detection algorithms.