Satellite imagery object detection using text prompts
I built a browser-based tool for detecting objects in satellite imagery using vision-language models (VLMs). You draw a polygon on the map and enter a text prompt such as "swimming pools", "oil tanks", or "buses". The system scans the selected area tile-by-tile and returns detections projected back onto the map as GeoJSON. Pipeline: select area and zoom level, split the region into mercantile tiles, run each tile with the prompt through a VLM, convert predicted bounding boxes to geographic coordinates (WGS84), and render the results back on the map. It works reasonably well for distinct…
In plain words
A browser-based tool for finding objects in satellite imagery using text prompts. Users draw a polygon on a map, enter a search term like "swimming pools" or "oil tanks," and the system scans the area tile-by-tile using vision-language models, returning detected objects as geographic coordinates overlaid on the map. The tool works well for distinct structures and requires no login. It is designed for researchers, analysts, and anyone needing to identify specific features across geographic regions from satellite data.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
I built a browser-based tool for detecting objects in satellite imagery using vision-language models (VLMs). You draw a polygon on the map and enter a text prompt such as "swimming pools", "oil tanks", or "buses". The system scans the selected area tile-by-tile and returns detections projected back onto the map as GeoJSON. Pipeline: select area and zoom level, split the region into mercantile tiles, run each tile with the prompt through a VLM, convert predicted bounding boxes to geographic coordinates (WGS84), and render the results back on the map. It works reasonably well for distinct structures in a zero-shot setting. occluded objects are still better handled by specialized detectors like YOLO models. There is a public demo and no login required. I am mainly interested in feedback on detection quality, performance tradeoffs between VLMs and specialized detectors, and potential real-world use cases.
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