An object detection dataset for satellite imagery of Jakarta, Indonesia. The dataset is formatted for the YOLO OBB (Oriented Bounding Box) model, suggesting annotations for buildings and trees. It was published on Kaggle, but details on the creator, size, and specific annotation counts are not provided.
Use Cases
- Train an oriented object detection model for building footprint extraction (inferred from domain, verify after download)
- Benchmark model performance on tree canopy detection in dense urban environments (inferred from domain, verify after download)
- Conduct urban land use and green space analysis from aerial imagery (inferred from domain, verify after download)
Strengths
- Published on Kaggle, a platform with established data sharing practices.
- Platform tags indicate a specific focus on oriented bounding boxes (OBB) for object detection.
Limitations
- Metadata is minimal; actual content requires verification after download.
- Row count, file size, and column definitions are unknown, which may limit suitability assessment.
- License and author information are unknown, affecting reproducibility and usage rights.
Provenance
- Source
- Kaggle
- Collection Method
- Likely derived from satellite or aerial imagery, but the specific annotation process is unknown.
- Time Range
- null
- Freshness
- Last updated date is unknown; freshness unverified.
- Geography
- Jakarta, Indonesia