Small Vehicle Detection
Detects small vehicles on satellite images with 0.5m GSD.
Small Vehicle Detection identifies small vehicles such as cars, vans, etc. in satellite images in both urban and rural settings. The block can detect vehicles in images with ground sampling distance (GSD) around 0.5 m. Output is provided as Geojson file containing detection results in Point feature format. The algorithm is trained on a data-set obtained from South-Eastern Asia.
- Catalog -> Pléiades Display -> Order and get the asset from storage of UP42
- In Projects workflows, Processing from Storage -> DIMAP GeoTIFF conversion -> Small Vehicle Detection
- Pléiades Display (Streaming) -> Small Vehicle Detection
Note: This block needs to be used without Raster Tiling. Pléiades Analytic is currently not supported.
The algorithm uses deep learning techniques and Faster R-CNN detection architecture to detect small vehicles such as cars, 3-wheelers and SUVs.
Traffic Monitoring, Transportation Infrastructure Design, Smart-City Application, Measuring Retail Traffic, Economic Activity, Hospital Traffic
|Supported input data||Input is required as a set of Tagged Image File|
|Format||(TIFF) image and the GeoJSON file. The image is expected to have Ground Sampling|
|Distance (GSD) less than 0.55 m.|
|Output data format||The output is point feature GeoJSON which contains points on detected vehicles.|
|Algorithm Training Data Details||The algorithm is trained on a dataset obtained from South Asia. Most of the settings are dense urban areas, neighborhoods, parking lots, industrial parks, etc.|
|Algorithm Performance||0.5 IoU and has detection of 0.5mAP on satellite images with GSD 0.55m|
Fore more information, visit the provider website here.
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