YOLO Solid Waste Analysis for Spatial Grid (SWAG)

This repo contains the labels and scripts for the YOLO Solid Waste Analysis for Spatial Grid (SWAG) for detecting solid waste piles from UAV imagery. The model is based on a previous work, that can be found here.

YOLO SWAG (Solid Waste Analysis on spatial Grids) is a pretrained YOLO26x-cls model for semantic segmentation of solid waste piles in UAV (drone) imagery. The model classifies 5m x 5m grid cells as either "waste" or "background" based on polygon labels, enabling efficient waste detection in OpenAerialMap (OAM) scenes and other aerial datasets.

How to use the data

The GPKG-files in ./data/labels are following this naming schema: {continent}_{country}_{city}_{openaerialmap_id}_tiles.gpkg. The original labels from the previous work are included aswell and follow the schema {openaerialmap_id}_tiles.gpkg Download the aerial images from OpenAerialMap. After that run:

uv run python scripts/create_labeling_grid.py <path/to/oam_files> <path/to/output/directoy>

The content of the output directory can be loaded into QGIS or similar applications for labelling. Tiles containing waste piles are labelled with class "1" and background with class "2".