Omkar2118/datasets huggingface dataset:
Songdo Traffic
Full name: Songdo Traffic: High Accuracy Georeferenced Vehicle Trajectories from a Large-Scale Study in a Smart City

The **Songdo Traffic** dataset delivers **precisely georeferenced vehicle trajectories** captured through **high-altitude bird's-eye view (BeV) drone footage** over **Songdo International Business District, South Korea**. Comprising **approximately 700,000 unique trajectories**, this resource represents one of the most extensive aerial traffic datasets publicly available, distinguishing itself through **exceptional temporal resolution** that captures vehicle movements at **29.97 points per second**, enabling unprecedented granularity for advanced urban mobility analysis.

Introducing paper: Advanced computer vision for extracting georeferenced vehicle trajectories from drone imagery
Songdo Vision
Full name: Songdo Vision: Vehicle Annotations from High-Altitude BeV Drone Imagery in a Smart City

The **Songdo Vision** dataset provides **high-resolution (4K, 3840×2160 pixels) RGB images** annotated with categorized **axis-aligned bounding boxes (BBs)** for vehicle detection from a **high-altitude bird’s-eye view (BeV)** perspective. Captured over **Songdo International Business District, South Korea**, this dataset consists of **5,419 annotated video frames**, featuring approximately **300,000 vehicle instances** categorized into **four classes**:  

- **Car** (including vans and light-duty vehicles)  
- **Bus**  
- **Truck**  
- **Motorcycle**

Introducing paper: Advanced computer vision for extracting georeferenced vehicle trajectories from drone imagery