# stephansturges/WALDO

Whereabouts Ascertainment for Low-lying Detectable Objects. The SOTA in FOSS AI for drones!

Repository: https://github.com/stephansturges/WALDO
Canonical: https://ross.abutalabs.com/products/waldo
Language: Python
License Family: other
Last push: 2025-01-07T08:49:02+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1400, "days_push": 603, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1695, forks 199 (observed 2026-08-28T04:05:23.858398+00:00)

## What it is
WALDO is an open-source object detection model based on a YOLOv8 backbone, trained with a synthetic data pipeline to detect people, vehicles, buildings, boats, and other objects in aerial and satellite imagery. It is distributed as model weights (MIT licensed) with supporting Python tooling for drone and overhead imagery analysis.

## Use cases
- detect people and vehicles in drone footage
- run object detection on satellite imagery
- find obstacles like utility poles for drone flight safety
- count cars and trucks in aerial photos
- search and rescue person detection from the air
- identify solar panels and buildings in overhead imagery

## When to choose
- you need FOSS object detection for aerial or satellite imagery
- you want MIT-licensed model weights usable commercially
- you need detection across altitudes from 30 feet to satellite views

## When to avoid
- you need military-target detection capabilities
- you need a fully supported product with a license file and formal releases
- your imagery is ground-level rather than overhead

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, computer-vision, image-processing
- domain: computer-vision, machine-learning
- platform: python, cross-platform
- tags: object-detection, yolo, drone-imagery, aerial-imagery, synthetic-data, foss, drones

## Member repositories
- stephansturges/WALDO (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:23.858398+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:37:57.770047+00:00, confidence not recorded.
  - readme: https://github.com/stephansturges/WALDO (fetched 2026-08-28T04:05:23.858398+00:00, sha df342f11e3ef)
- Data as of 2026-08-30T08:39:29.467469+00:00.